Distributed Sources Optimal Sites and Sizes Search in Large Power Systems

*Mustafa Mosbah, Redha Djamel Mohammedi and Salem Arif*

## **Abstract**

The integration of renewable sources into the power system has now become an unavoidable necessity for these technical and economic advantages and for the protection of the environment. In this chapter, a study is given for the integration of the Distributed Source (DS) in an optimal way and this by looking for the best location (sites) and the best power to be injected (size). The optimization technique used is based on genetic algorithms under technical and safety constraints, with the aim of minimizing active network losses and maximizing voltage stability. These objective functions are handled as a single and multi-objective problem. This study is applied on the standard IEEE 30 bus network under the MATLAB code.

**Keywords:** distributed source, optimal site and size, active power losses, voltage stability improvement, genetic algorithm

## **1. Introduction**

Non-conventional or clean production is increasing rapidly around the world, thanks to it's advantages such as reduced environmental impact, small size and it is a renewable energy [1]. The traditional power system is characterized by the unidirectional of the power flow because the energy comes from centralized sources [2]. These sources are generally based on fossil resources that are exhaustible and polluting for the environment.

The transmission power system spreads on long distances, which leads to losses in the lines by Joule effect on the one hand, and on the other hand, it requires huge investments and waste lands with long achievement times, which has led researchers to think about other solutions to face these problems [3].

Among these solutions is to have sources of electrical energy close to the consumers (local production). With the liberalization of the electricity market and the evolution of decentralized source (DS) technology in recent years, an increased trend towards their use has emerged. DS is defined as small producers based on renewable or conventional sources installed at different points in the power system, either at the transmission or distribution level [4]. The rate of DS integration tends to increase progressively in several countries [5].

In spite of the various advantages of DS, its sources present disadvantages when they are inserted into the power system, such as frequency instability caused by the intermittency of some renewable sources (e.g. photovoltaic and wind power) [6]. They also present some constraints, such as exceeding the thermal limits of power lines, increased Joule effect losses and the dysfunctioning of electrical protection devices and the exceeding of voltages at connection points. These constraints are due to the wrong choice of size (maximum power) and site of the DS, which requires the search for the best sites and adequate sizes [7].

*2.1.1 First objective: minimization of active power losses*

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

losses in the line, this is expressed by the following equation:

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

The first concern of the power system operator is to minimize active power

NB

k¼1 rkI 2

<sup>k</sup> (1)

Vi sin <sup>θ</sup>ij � <sup>δ</sup>ij � � � � <sup>2</sup> <sup>≤</sup><sup>1</sup> (2)

FMO ¼ α1ð Þþ TPLIk α2ð Þ LVSIk (3)

TPLIk <sup>¼</sup> <sup>X</sup>

respectively. TPLI represent the Total Power Losses Index of the network.

LVSIk <sup>¼</sup> 4XijQj

critical line and may lead to the network collapse.

the line voltage stability index, respectively.

power equality constraints can be expressed as follows [33]:

QGi <sup>þ</sup><sup>X</sup> NDS

PGi <sup>þ</sup><sup>X</sup> NDS

i¼1

i¼1

X NG

i¼1

X NG

8 >>>>><

>>>>>:

i¼1

where Xij, Qj, Vi, θij, and δij are the line reactance, is the reactive power at receiving end, the voltage at receiving end, is the line impedance angle between bus i and j and voltage phase angle difference between bus i and busj, respectively. The line which represents an LVSI value close to 1 will be considered, the most

For multiobjective optimization, the two objectives functions are combined in a single linear function using weighting factors. Mathematically, this is given in the

where α<sup>1</sup> and α<sup>2</sup> represent the weighting factors of active power losses index and

Equality constraints represent power balance equations between generation and demand. For a transmission power system in presence of DS, the active and reactive

> PDSi �<sup>X</sup> ND

QDSi �<sup>X</sup> ND

i¼1

i¼1

where Pð Þ G, QG is the active and reactive power of the conventional generator, PDS, QDS ð Þ is the active and reactive power produced by DS. This source is capable of delivering the active and reactive power. Pð Þ D, QD represent the active and

PDi �<sup>X</sup> NB

QDi �<sup>X</sup> NB

i¼1

i¼1

Pli ¼ 0

(4)

Qli ¼ 0

*2.1.2 Second objective: improvement of the line voltage stability index*

equation:

following form:

**379**

**2.2 Equality constraints**

where rk and Ik, are the resistance and the current of the transmission line k

To assure that the operating point of the power system is far from the voltage collapse point, the voltage stability index must be improved. Among the effective indices that have been proposed in the literature is the Line Voltage Stability Index (LVSI) [32]. The LVSI of the line between bus i and jis given by the following

A number of researchers have studied the problem of optimal site and size of DS to distribution networks [4, 8]. Example, in researchers [9] presented a technique a review of optimal DS placement in distribution network. DS site and size search techniques can be based on artificial intelligence techniques, metaheuristic techniques or deterministic techniques [10]. While most papers deal with this problem as a single-objective problem and some papers have focused on the problem of multi-objective optimizations [11]; these studies have considered a variety of objective functions including voltage profile improvement, losses minimization, reliability index minimization (SAIFI, SAIDI and END), fuel cost minimization, greenhouse gas emission minimization, maximization of DS penetration rate and maximization of voltage stability [12–18]. Some researchers have examined the problem of optimal sitting and size of DS to transmission networks [19–29].

Based on the literature search carried out, it was noted that the optimal integration of DS into distribution networks is largely discussed, however, there is less literature on the integration of DS into transmission networks.

The objective of this chapter is to study the problem of determining the Optimal Sites and Sizes of DS (OSSDS) in the transmission power system while taking into account the various constraints of the system (technical and security constraints). This is achieved by using a metaheuristic optimization technique such as the Genetic Algorithm (GA) technique. The objective functions considered in this work are the minimization of active power losses and the voltage stability improvement. These objective functions are treated as mono-objective and multi-objective (the objective functions are combined to a single objective function via weighting factors). This study has been applied on the IEEE 30 bus network under MATLAB code. For this reason, this chapter is organized according to the following plan: Section 2 will present the mathematical formulas of the OSSDS problem, i.e. the objective functions, the different constraints. Section 3 will present definitions on the method used (GA) and their application on OSSDS. Section 4 will give the description of the IEEE 30 node network and the limitations of the study framework. Section 5 will present the simulation, interpretation and analysis of the results obtained. Finally, the conclusion of the chapter and some perspectives.

## **2. Formulation of the OSSDS problem**

The objective of this work is to research what is the optimal power to be injected by DS and the bus of their insertions that gives us the best performance of the power system considering the imposed constraints. To reach this objective we must define the fitness function and the constraints of equality and inequality which will be detailed in the following sections [30, 31].

#### **2.1 Objective function (OF)**

The OSSDS is formulated as a single and multi-objective problem using two objective functions.

#### *2.1.1 First objective: minimization of active power losses*

intermittency of some renewable sources (e.g. photovoltaic and wind power) [6]. They also present some constraints, such as exceeding the thermal limits of power lines, increased Joule effect losses and the dysfunctioning of electrical protection devices and the exceeding of voltages at connection points. These constraints are due to the wrong choice of size (maximum power) and site of the DS, which

A number of researchers have studied the problem of optimal site and size of

Based on the literature search carried out, it was noted that the optimal integration of DS into distribution networks is largely discussed, however, there is less

The objective of this chapter is to study the problem of determining the Optimal Sites and Sizes of DS (OSSDS) in the transmission power system while taking into account the various constraints of the system (technical and security constraints). This is achieved by using a metaheuristic optimization technique such as the Genetic Algorithm (GA) technique. The objective functions considered in this work are the minimization of active power losses and the voltage stability improvement. These objective functions are treated as mono-objective and multi-objective (the objective functions are combined to a single objective function via weighting factors). This study has been applied on the IEEE 30 bus network under MATLAB code. For this reason, this chapter is organized according to the following plan: Section 2 will present the mathematical formulas of the OSSDS problem, i.e. the objective functions, the different constraints. Section 3 will present definitions on the method used (GA) and their application on OSSDS. Section 4 will give the description of the IEEE 30 node network and the limitations of the study framework. Section 5 will present the simulation, interpretation and analysis of the results

DS to distribution networks [4, 8]. Example, in researchers [9] presented a technique a review of optimal DS placement in distribution network. DS site and

size search techniques can be based on artificial intelligence techniques, metaheuristic techniques or deterministic techniques [10]. While most papers deal with this problem as a single-objective problem and some papers have focused on the problem of multi-objective optimizations [11]; these studies have considered a variety of objective functions including voltage profile improvement, losses minimization, reliability index minimization (SAIFI, SAIDI and END), fuel cost minimization, greenhouse gas emission minimization, maximization of DS penetration rate and maximization of voltage stability [12–18]. Some researchers have examined the problem of optimal sitting and size of DS to transmission

requires the search for the best sites and adequate sizes [7].

*Renewable Energy - Technologies and Applications*

literature on the integration of DS into transmission networks.

obtained. Finally, the conclusion of the chapter and some perspectives.

The objective of this work is to research what is the optimal power to be injected

by DS and the bus of their insertions that gives us the best performance of the power system considering the imposed constraints. To reach this objective we must define the fitness function and the constraints of equality and inequality which will

The OSSDS is formulated as a single and multi-objective problem using two

**2. Formulation of the OSSDS problem**

be detailed in the following sections [30, 31].

**2.1 Objective function (OF)**

objective functions.

**378**

networks [19–29].

The first concern of the power system operator is to minimize active power losses in the line, this is expressed by the following equation:

$$\text{TPPLI}\_{\mathbf{k}} = \sum\_{\mathbf{k}=1}^{N\_{\text{B}}} \mathbf{r}\_{\mathbf{k}} \mathbf{I}\_{\mathbf{k}}^{2} \tag{1}$$

where rk and Ik, are the resistance and the current of the transmission line k respectively. TPLI represent the Total Power Losses Index of the network.

## *2.1.2 Second objective: improvement of the line voltage stability index*

To assure that the operating point of the power system is far from the voltage collapse point, the voltage stability index must be improved. Among the effective indices that have been proposed in the literature is the Line Voltage Stability Index (LVSI) [32]. The LVSI of the line between bus i and jis given by the following equation:

$$\text{LVSI}\_{\text{k}} = \frac{4 \mathbf{X}\_{\text{ij}} \mathbf{Q}\_{\text{j}}}{\left[ \mathbf{V}\_{\text{i}} \sin \left( \theta\_{\text{ij}} - \delta\_{\text{ij}} \right) \right]^{2}} \le \mathbf{1} \tag{2}$$

where Xij, Qj, Vi, θij, and δij are the line reactance, is the reactive power at receiving end, the voltage at receiving end, is the line impedance angle between bus i and j and voltage phase angle difference between bus i and busj, respectively.

The line which represents an LVSI value close to 1 will be considered, the most critical line and may lead to the network collapse.

For multiobjective optimization, the two objectives functions are combined in a single linear function using weighting factors. Mathematically, this is given in the following form:

$$\mathbf{F\_{MO}} = \mathbf{a\_1}(\mathbf{TPLI\_k}) + \mathbf{a\_2}(\mathbf{LVSI\_k}) \tag{3}$$

where α<sup>1</sup> and α<sup>2</sup> represent the weighting factors of active power losses index and the line voltage stability index, respectively.

#### **2.2 Equality constraints**

Equality constraints represent power balance equations between generation and demand. For a transmission power system in presence of DS, the active and reactive power equality constraints can be expressed as follows [33]:

$$\begin{cases} \sum\_{i=1}^{\mathcal{N}\_{\rm Gi}} \mathbf{P}\_{\rmGi} + \sum\_{i=1}^{\mathcal{N}\_{\rm DS}} \mathbf{P}\_{\rm DSi} - \sum\_{i=1}^{\mathcal{N}\_{\rm Di}} \mathbf{P}\_{\rmDi} - \sum\_{i=1}^{\mathcal{N}\_{\rm B}} \mathbf{P}\_{\rm li} = \mathbf{0} \\\\ \sum\_{i=1}^{\mathcal{N}\_{\rm Gi}} \mathbf{Q}\_{\rmGi} + \sum\_{i=1}^{\mathcal{N}\_{\rm DS}} \mathbf{Q}\_{\rm DSi} - \sum\_{i=1}^{\mathcal{N}\_{\rm D}} \mathbf{Q}\_{\rmDi} - \sum\_{i=1}^{\mathcal{N}\_{\rm B}} \mathbf{Q}\_{\rm li} = \mathbf{0} \end{cases} \tag{4}$$

where Pð Þ G, QG is the active and reactive power of the conventional generator, PDS, QDS ð Þ is the active and reactive power produced by DS. This source is capable of delivering the active and reactive power. Pð Þ D, QD represent the active and

reactive power demand at the load bus, Pl, Ql ð Þ represent the active and reactive power losses.

### **2.3 Inequality constraints**

These constraints represent the physical limits of the lines, conventional generators and DS as also the security limits of the voltages of the network busses. They are expressed by the following equations:

$$\mathbf{S}\_{\rm bi} \le \mathbf{S}\_{\rm binax} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \dots \dots \dots \dots \dots N\_{\rm B} \tag{5}$$

where kp, kV and ks are the penalty factors of the active power produced by the

The limits of the various variables are determined by the following equation:

The values of the penalty factors are determined by empirical means. After

approach. Consequently, in order to solve practical problems, it is necessary to use

model to solve real size problems is practically not possible with a classical

From the above mathematical formulation, it can be noted that the use of such a

GA is a metaheuristic optimization technique inspired by natural selection, and genetics developed by Holland-John, who conceived and realized an idea on how to transform the characteristics of natural evolution into a computer program [35]. The algorithm is based on a set of possible solutions randomly initialized in the search space. Individuals are represented by their design variables or by chromosome coding. Some solutions from the first population are used to form a new population based on genetic operators (crossover, mutation and selection). The goal is for the new population to be better than the previous one. The solutions that will be used to form new solutions are randomly selected according to their merit represented by an objective function specific to the problem posed, which should be minimized or maximized, so the better the individual, the greater his chances of

The goal of the GA method is to determine the optimal site and size of the DS to be integrated into the power system while minimizing the objective function under imposed constraints. Initially the vector of state variables and the vector of control

The vector χ<sup>T</sup> of state variables is composed of the active generation power at the reference bus PG1 the load bus voltages VLi, the reactive power produced by

The vector vT of the control variables shows the active power outputs of the DS

(size) SDS and the site or location of the DS LDS. Hence, this vector can be

, the apparent power transiting through transmission

<sup>χ</sup><sup>T</sup> <sup>¼</sup> PG1 , VL1 … VLNL , QG1 … QGNG , Sl1 … SlNl � � (14)

vT <sup>¼</sup> SDS1 , SDS2 … … *:*SDSNDS , LDS1 , LDS2 … *::*LDSNDS ½ � (15)

Tmin

Ti >Tmax i Ti <Tmin i

<sup>i</sup> ≤Ti ≤Tmax i

(13)

reference generator (slack bus), the voltage at the load nodes and the penalty

Tmax <sup>i</sup> if Tmin <sup>i</sup> if Ti if

8 ><

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

>:

several tests it is decided that, kV=ks ¼10,000 and kp=1000.

metaheuristic methods, that is, the genetic algorithms method.

surviving and reproducing, until the stop criterion is satisfied.

constrained of the thermal limit of the lines, respectively.

Tlim i ¼

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

T, represents the variables Pslack, VLi and Sbi*:*

**3. Genetic algorithm method**

**3.1 Application of the GA method**

variables are expressed as below:

lines Sli. This vector χ<sup>T</sup> can be expressed by:

conventional generators QGi

represented by:

**381**

$$\mathbf{P\_{Gimn}} \le \mathbf{P\_{Gi}} \le \mathbf{P\_{Gimn}} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \dots \dots \dots \dots N\_{\mathbb{G}} \tag{6}$$

$$\mathbf{Q\_{Gmin}} \le \mathbf{Q\_{Gi}} \le \mathbf{Q\_{Gmax}} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \dots \dots \dots \dots N\_{\mathbf{G}} \tag{7}$$

$$\mathbf{V}\_{\text{imin}} \le \mathbf{V}\_{\text{i}} \le \mathbf{V}\_{\text{i}\text{max}} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \dots \dots \dots \dots \dots \dots N} \tag{8}$$

$$\mathbf{S}\_{\rm imin}^{\rm DS} \le \mathbf{S}\_{\rm i}^{\rm DS} \le \mathbf{S}\_{\rm imax}^{\rm DS} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \dots \dots \dots \dots \dots \dots N\_{\rm DS} \tag{9}$$

$$\sum\_{\mathbf{i}=1}^{\text{N\_{DS}}} \mathbf{P\_{DSi}} \le \mathbf{\tau} \* \sum\_{\mathbf{i}=1}^{\text{N\_D}} \mathbf{P\_{Di}} \text{ for } \mathbf{i} = \mathbf{1} \dots \dots \mathbf{N\_{DS}} \text{ and } \mathbf{i} = \mathbf{1} \dots \dots \mathbf{N\_D} \tag{10}$$

where Sbi is the apparent power that transits via the line between the nodes i and j. Sbimax, is the maximum limit of the line (thermal limit). PGimin, PGimax, PGimin and PGimax are the minimum and maximum active and reactive powers of the ith conventional generator. SDS min and SDS max are the minimum and maximum production powers of the DS. N, ND, NG, NB and NDS are the number of network busses, number of load busses, the number of generators, the number of branches and the number of DS, respectively. Vimin and Vimax are minimum and maximum voltage in bus i.

For reasons of power system security, the network operator has limited the penetration rate (τ%) of DS. This limit is set depending on the robustness of the network (each network has its specific). This rate is calculated by the ratio of the total active power of the DS to the total active power demanded or the total power generated by conventional sources multiplied by one hundred; this is given by the following Equation [34]:

$$\tau\_{\bowtie} = \frac{\sum\_{i=1}^{N\_{\rm DS}} \mathbf{P\_{DSi}}}{\sum\_{i=1}^{N\_{\rm D}} \mathbf{P\_{Di}}} \ast \mathbf{100} \tag{11}$$

#### **2.4 Constraint processing**

To optimize the site and size of the DS, it is important to mention that the control variables are generated within their allowable limits using a random strategy using a metaheuristic technique. During the optimization process, it is possible to come across solutions that are unfeasible due to exceeding the voltage limit, the thermal limit of the lines or the power limit of the reference generator, in this case the OF is penalized. This OF is reformulated as follows [33]:

$$\mathbf{F}^{\rm p} = \sum\_{i=1}^{\mathbf{n}\_{\rm OF}} \mathbf{f}\_{i} + \mathbf{k}\_{\rm P} \left(\mathbf{P}\_{\rm slack} - \mathbf{P}\_{\rm slack}^{\rm lim}\right)^{2} + \mathbf{k}\_{\rm V} \sum\_{i=1}^{\rm NL} \left(\mathbf{V}\_{\rm L\_{i}} - \mathbf{V}\_{\rm L\_{i}}^{\rm lim}\right)^{2} + \mathbf{k}\_{\rm s} \sum\_{i=1}^{\rm NB} \left(\mathbf{S}\_{\rm b\_{i}} - \mathbf{S}\_{\rm b\_{i}}^{\rm lim}\right)^{2} \tag{12}$$

where kp, kV and ks are the penalty factors of the active power produced by the reference generator (slack bus), the voltage at the load nodes and the penalty constrained of the thermal limit of the lines, respectively.

The limits of the various variables are determined by the following equation:

$$\mathbf{T}\_{\mathbf{i}}^{\text{lim}} = \begin{cases} \mathbf{T}\_{\mathbf{i}}^{\text{max}} & \text{if } & \mathbf{T}\_{\mathbf{i}} > \mathbf{T}\_{\mathbf{i}}^{\text{max}} \\ \mathbf{T}\_{\mathbf{i}}^{\text{min}} & \text{if } & \mathbf{T}\_{\mathbf{i}} < \mathbf{T}\_{\mathbf{i}}^{\text{min}} \\ \mathbf{T}\_{\mathbf{i}} & \text{if } & \mathbf{T}\_{\mathbf{i}}^{\text{min}} \le \mathbf{T}\_{\mathbf{i}} \le \mathbf{T}\_{\mathbf{i}}^{\text{max}} \end{cases} \tag{13}$$

T, represents the variables Pslack, VLi and Sbi*:*

The values of the penalty factors are determined by empirical means. After several tests it is decided that, kV=ks ¼10,000 and kp=1000.

From the above mathematical formulation, it can be noted that the use of such a model to solve real size problems is practically not possible with a classical approach. Consequently, in order to solve practical problems, it is necessary to use metaheuristic methods, that is, the genetic algorithms method.

## **3. Genetic algorithm method**

reactive power demand at the load bus, Pl, Ql ð Þ represent the active and reactive

These constraints represent the physical limits of the lines, conventional generators and DS as also the security limits of the voltages of the network busses. They

where Sbi is the apparent power that transits via the line between the nodes i and j. Sbimax, is the maximum limit of the line (thermal limit). PGimin, PGimax, PGimin and PGimax are the minimum and maximum active and reactive powers of the ith con-

powers of the DS. N, ND, NG, NB and NDS are the number of network busses, number of load busses, the number of generators, the number of branches and the number of DS, respectively. Vimin and Vimax are minimum and maximum voltage in

τ% ¼

the OF is penalized. This OF is reformulated as follows [33]:

slack � �<sup>2</sup>

þ kV

X NL

VLi � Vlim Li � �<sup>2</sup> þ ks X NB

i¼1

Sbi � Slim bi � �<sup>2</sup>

(12)

i¼1

fi <sup>þ</sup> kP Pslack � <sup>P</sup>lim

For reasons of power system security, the network operator has limited the penetration rate (τ%) of DS. This limit is set depending on the robustness of the network (each network has its specific). This rate is calculated by the ratio of the total active power of the DS to the total active power demanded or the total power generated by conventional sources multiplied by one hundred; this is given by the

> PNDS <sup>i</sup>¼<sup>1</sup> PDSi PND <sup>i</sup>¼<sup>1</sup>PDi

To optimize the site and size of the DS, it is important to mention that the control variables are generated within their allowable limits using a random strategy using a metaheuristic technique. During the optimization process, it is possible to come across solutions that are unfeasible due to exceeding the voltage limit, the thermal limit of the lines or the power limit of the reference generator, in this case

Sbi ≤ Sbimax for i ¼ 1 ………… *:* … … *:*NB (5)

PGimin ≤PGi ≤ PGimax for i ¼ 1 …………… *:* … NG (6)

QGimin ≤ QGi ≤ QGimax for i ¼ 1 …………… *::* … NG (7)

Vimin ≤ Vi ≤ Vimax for i ¼ 1 ………………… N (8)

imax for i ¼ 1 …………… *:* … … NDS (9)

PDi for i ¼ 1 … … NDS and i ¼ 1 … *::*ND (10)

max are the minimum and maximum production

∗ 100 (11)

power losses.

**2.3 Inequality constraints**

are expressed by the following equations:

*Renewable Energy - Technologies and Applications*

SDS imin ≤SDS

PDSi ≤τ ∗

X NDS

i¼1

ventional generator. SDS

following Equation [34]:

**2.4 Constraint processing**

<sup>F</sup><sup>p</sup> <sup>¼</sup> <sup>X</sup>nOF i¼1

**380**

bus i.

<sup>i</sup> ≤SDS

X ND

i¼1

min and SDS

GA is a metaheuristic optimization technique inspired by natural selection, and genetics developed by Holland-John, who conceived and realized an idea on how to transform the characteristics of natural evolution into a computer program [35]. The algorithm is based on a set of possible solutions randomly initialized in the search space. Individuals are represented by their design variables or by chromosome coding. Some solutions from the first population are used to form a new population based on genetic operators (crossover, mutation and selection). The goal is for the new population to be better than the previous one. The solutions that will be used to form new solutions are randomly selected according to their merit represented by an objective function specific to the problem posed, which should be minimized or maximized, so the better the individual, the greater his chances of surviving and reproducing, until the stop criterion is satisfied.

## **3.1 Application of the GA method**

The goal of the GA method is to determine the optimal site and size of the DS to be integrated into the power system while minimizing the objective function under imposed constraints. Initially the vector of state variables and the vector of control variables are expressed as below:

The vector χ<sup>T</sup> of state variables is composed of the active generation power at the reference bus PG1 the load bus voltages VLi, the reactive power produced by conventional generators QGi , the apparent power transiting through transmission lines Sli. This vector χ<sup>T</sup> can be expressed by:

$$\mathbf{x}^{\mathrm{T}} = \begin{bmatrix} \mathbf{P}\_{\mathrm{G}\_{1}}, \mathbf{V}\_{\mathrm{L}\_{1}} \dots \mathbf{V}\_{\mathrm{L}\_{\mathrm{NL}}}, \mathbf{Q}\_{\mathrm{G}\_{1}} \dots \mathbf{Q}\_{\mathrm{G}\_{\mathrm{NG}}}, \mathbf{S}\_{\mathrm{l}\_{1}} \dots \mathbf{S}\_{\mathrm{l}\_{\mathrm{ll}}} \end{bmatrix} \tag{14}$$

The vector vT of the control variables shows the active power outputs of the DS (size) SDS and the site or location of the DS LDS. Hence, this vector can be represented by:

$$\mathbf{v}^{T} = \begin{bmatrix} \mathbf{S}\_{\text{DS}\_{1}}, \mathbf{S}\_{\text{DS}\_{2}} \dots \dots \mathbf{S}\_{\text{DS}\_{\text{NDS}}}, \mathbf{L}\_{\text{DS}\_{1}}, \mathbf{L}\_{\text{DS}\_{2}} \dots \dots \mathbf{L}\_{\text{DS}\_{\text{NDS}}} \end{bmatrix} \tag{15}$$


#### **Figure 1.**

*Control variable vector structure.*

**Figure 1** indicates the chromosome structure employed in this study.

**Step 1:** In determining the site and size of DS, the genetic algorithm method was suggested. The main steps for researching the site and size of DS are as follows:

**Step 2:** Run a power flow and determine the various network parameters in the absence and presence of DS, using the Newton Raphson method.

**Step 3:** Select the GA parameters (number of generations, population size, crossover and mutation probability) and randomly generate the values of the sites and sizes between their limits using Eqs. E16, E17 and E18 (creation of the initial population P0).

$$\mathbf{P\_0} = \begin{bmatrix} \mathbf{X\_1}, \mathbf{X\_2} \dots \dots \mathbf{X\_i} \dots \mathbf{X\_n} \text{ population} \end{bmatrix} \tag{16}$$

$$\mathbf{L}\_{\rm wi} = round(2 + rand(\mathbf{N}\_{\rm bus} - \mathbf{2})) \tag{17}$$

$$\mathbf{S}\_{\rm wi} = \mathbf{P}\_{\rm min}^{\rm DSi} + rand \left( \mathbf{P}\_{\rm max}^{\rm DSi} - \mathbf{P}\_{\rm min}^{\rm DSi} \right) \tag{18}$$

**4.1 Study framework**

*DS site and size search flowchart.*

**Figure 2.**

**383**

Before beginning the presentation of the simulation results, it is necessary to cite the limitations of the study framework under consideration. The Newton Raphson method is used via the MATPOWER software to calculate the power flow. For the GA method the existing Toolbox in the MATLAB library (GA function) will be used. The voltage limits of the network busses are limited between 0.95 pu- 1.1 pu. DS are considered as sources capable of delivering active and reactive power, using a power factor of 0.8. DS integration are modeled as PQ busses (negative loads). It is important to note that all load nodes are considered candidate busses for DS sites. It is important to note that the number of DS to be integrated into the network is

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

where *round*ð Þ• represents the value of a number that is rounded to the next integer, and *rand* represents a random number uniformly distributed between 0 and 1 [24].

Start the iteration meter t ¼ 0.

**Step 4:** Run the power flow in the presence of the DS and evaluate the objective function for each individual.

**Step 5:** Examine all network constraints using Eqs. E4 to E8. If the latter are satisfied, go to the next step. If not, penalize the OF using Eq. E12 and go to the next step.

**Step 6:** Generate new populations following the laws of GA (crossover, mutation and selection), increase the generation meter kð Þ ¼ k þ 1 and repeat steps 4 to step 6up to the stop criteria (maximum number of generations).

**Step 7:** Extract the best individual and show the results (site, size and various network parameters).

**Figure 2** shows the flowchart of the search for the site and size of DS to be incorporated into the power system.

## **4. Description of the studied network**

The IEEE 30 bus network is used by power system researchers to test the effectiveness of their programs simulation. This system is composed of 30 buss, 41 transmission lines, 04 transformers, 06 conventional generators with a total generating capacity of 435 MW with a reactive capacity of �95 MVAr to 520 MVAr and 21 loads with a total power demand of 283.4 MW and 126.2 MVAr [35]. Bus No. 1 is taken as the reference (slack bus). **Figure 3** shows the single line diagram of the network studied.

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems DOI: http://dx.doi.org/10.5772/intechopen.95266*

**Figure 2.** *DS site and size search flowchart.*

## **4.1 Study framework**

Before beginning the presentation of the simulation results, it is necessary to cite the limitations of the study framework under consideration. The Newton Raphson method is used via the MATPOWER software to calculate the power flow. For the GA method the existing Toolbox in the MATLAB library (GA function) will be used. The voltage limits of the network busses are limited between 0.95 pu- 1.1 pu. DS are considered as sources capable of delivering active and reactive power, using a power factor of 0.8. DS integration are modeled as PQ busses (negative loads). It is important to note that all load nodes are considered candidate busses for DS sites. It is important to note that the number of DS to be integrated into the network is

**Figure 1** indicates the chromosome structure employed in this study.

absence and presence of DS, using the Newton Raphson method.

Swi <sup>¼</sup> <sup>P</sup>DSi

step 6up to the stop criteria (maximum number of generations).

Start the iteration meter t ¼ 0.

incorporated into the power system.

**4. Description of the studied network**

function for each individual.

**Figure 1.**

*Control variable vector structure.*

*Renewable Energy - Technologies and Applications*

network parameters).

**382**

suggested. The main steps for researching the site and size of DS are as follows: **Step 2:** Run a power flow and determine the various network parameters in the

and mutation probability) and randomly generate the values of the sites and sizes between their limits using Eqs. E16, E17 and E18 (creation of the initial population P0).

P0 ¼ X1, X2 … … Xi … *:*Xn population

min <sup>þ</sup> *rand* PDSi

where *round*ð Þ• represents the value of a number that is rounded to the next integer, and *rand* represents a random number uniformly distributed between 0 and 1 [24].

**Step 4:** Run the power flow in the presence of the DS and evaluate the objective

**Step 5:** Examine all network constraints using Eqs. E4 to E8. If the latter are satisfied,

**Step 6:** Generate new populations following the laws of GA (crossover, mutation and selection), increase the generation meter kð Þ ¼ k þ 1 and repeat steps 4 to

**Step 7:** Extract the best individual and show the results (site, size and various

The IEEE 30 bus network is used by power system researchers to test the effectiveness of their programs simulation. This system is composed of 30 buss, 41 transmission lines, 04 transformers, 06 conventional generators with a total generating capacity of 435 MW with a reactive capacity of �95 MVAr to 520 MVAr and 21 loads with a total power demand of 283.4 MW and 126.2 MVAr [35]. Bus No. 1 is taken as the reference

(slack bus). **Figure 3** shows the single line diagram of the network studied.

**Figure 2** shows the flowchart of the search for the site and size of DS to be

go to the next step. If not, penalize the OF using Eq. E12 and go to the next step.

**Step 1:** In determining the site and size of DS, the genetic algorithm method was

**Step 3:** Select the GA parameters (number of generations, population size, crossover

(16)

(18)

Lwi ¼ *round*ð Þ 2 þ *rand*ð Þ Nbus � 2 (17)

max � PDSi min

**5. Simulation results and interpretations**

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

Total Conventional Active

Total Conventional Reactive

Production

Production

DS Size (MW, MVAr)

TPLI (MW)

**Table 1.**

**385**

*\*\* without DS integration.*

*Summary of network simulation results for the various cases.*

After the execution of the elaborated program, the simulation results achieved are shown bellow. **Table 1**, represents all the simulation results obtained for the five

**Parameters Limits Case 01 Case 02 Case 03 Case 04**

PG1(MW) 200 50 182.64 52.47 60.61 50.46 PG2(MW) 80 20 50.58 50.58 50.58 50.58 PG3(MW) 50 15 18.52 18.52 18.52 18.52 PG4(MW) 35 10 18.09 18.09 18.09 18.09 PG5(MW) 30 10 10.40 10.40 10.40 10.40 PG6(MW) 40 10 13.26 13.26 13.26 13.26 QG1(MVAr) 200 20 8.56 16.94 6.16 17.97 QG2(MVAr) 100 20 23.47 8.88 15.30 8.98 QG3(MVAr) 50 15 32.04 3.22 23.75 5.10 QG4(MVAr) 60 15 49.29 5.34 2.80 4.82 QG5(MVAr) 50 10 5.39 10.00 6.98 7.92 QG6(MVAr) 60 15 2.74 14.26 15.00 12.29

435 115 293.49 163.33 171.46 161.31

520 15 104.37 18.32 10.16 21.14

\*\* (46.96, 35.22) (36.40,

(38.58, 28.93) (52.97,

10.89 2.798 4.620 2.945

9 12 17 12 20 20 18 23 23 30 29 30

27.30)

39.73)

(5.63, 4.22) (6.07, 4.55) (10.36, 7.77) (18.09, 13.56) (11.37, 8.52) (4.60, 3.45) (13.60, 10.20) (9.73, 7.30) (15.05, 11.28)

(67.52, 50.64)

(27.48, 20.61)

cases studied, as also the physical power limits of conventional generators.

**Max Min**

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

Total Load (MW, MVAr) (283.40, 126.20)

DS Site(Best Location) \*\* \*\* \*\* 7 4 7

LVSI 0.181 0.158 0.067 0.149 Loading Parameter (pu) 2.1 4.4 5.7 5.2

**Figure 3.** *Schematic diagram of the IEEE 30 bus network.*

chosen in advance. After integration of a DS up to 10 DS, it is observed that, the best number from the viewpoint of improving the network parameters is 05 DS. For this reason, this study considers the insertion of five DS. The limits of the active power delivered by each DS are between 0 and 100 MW. And the penetration level limit of the total power delivered by the DS is 0*:*5 ∗ PND <sup>i</sup>¼<sup>1</sup>PDi � � MW that is PNDS <sup>i</sup>¼<sup>1</sup> PDSi <sup>≤</sup>0*:*<sup>5</sup> <sup>∗</sup> <sup>P</sup>ND <sup>i</sup>¼<sup>1</sup>PDi � �. After several tests on the studied network, it is noted that, the optimal parameters of the GA method are: the number of chromosomes (population size) is fixed at 100, the maximum number of generations is 50, the probability of mutation is 0.01 and the probability of crossover is 0.9. The multiobjective optimization considered in this study is based on the method of aggregate objectives through the weighting factors. It is important to note that, the choice of the values of these factors are dependent on the network operator and on the importance of the index to be improved. For this reason, the values of the weighting factors are set as follows: α1=0.8 and α<sup>2</sup> =0.2. In this study four cases are considered: the first case shows the simulation results for the base case (Execute the optimal power flow without DS). Second case, presents the results of the minimization of active losses only. Third case, presents the results of the voltage stability index improvement. Fourth case, presents the simulation results of the multi-objective case, it is the minimization of the bi-objectives at the simultaneous (minimization of losses and voltage stability index improvement).

## **5. Simulation results and interpretations**

After the execution of the elaborated program, the simulation results achieved are shown bellow. **Table 1**, represents all the simulation results obtained for the five cases studied, as also the physical power limits of conventional generators.


#### **Table 1.**

*Summary of network simulation results for the various cases.*

chosen in advance. After integration of a DS up to 10 DS, it is observed that, the best number from the viewpoint of improving the network parameters is 05 DS. For this reason, this study considers the insertion of five DS. The limits of the active power delivered by each DS are between 0 and 100 MW. And the penetration

that, the optimal parameters of the GA method are: the number of chromosomes (population size) is fixed at 100, the maximum number of generations is 50, the probability of mutation is 0.01 and the probability of crossover is 0.9. The multiobjective optimization considered in this study is based on the method of aggregate objectives through the weighting factors. It is important to note that, the choice of the values of these factors are dependent on the network operator and on the importance of the index to be improved. For this reason, the values of the weighting factors are set as follows: α1=0.8 and α<sup>2</sup> =0.2. In this study four cases are considered: the first case shows the simulation results for the base case (Execute the

optimal power flow without DS). Second case, presents the results of the

(minimization of losses and voltage stability index improvement).

minimization of active losses only. Third case, presents the results of the voltage stability index improvement. Fourth case, presents the simulation results of the multi-objective case, it is the minimization of the bi-objectives at the simultaneous

<sup>i</sup>¼<sup>1</sup>PDi � �

. After several tests on the studied network, it is noted

MW that is

level limit of the total power delivered by the DS is 0*:*5 ∗ PND

<sup>i</sup>¼<sup>1</sup>PDi � �

*Schematic diagram of the IEEE 30 bus network.*

*Renewable Energy - Technologies and Applications*

PNDS

**384**

**Figure 3.**

<sup>i</sup>¼<sup>1</sup> PDSi <sup>≤</sup>0*:*<sup>5</sup> <sup>∗</sup> <sup>P</sup>ND

**Figure 4**, shows the situation of apparent power transmitted via transmission lines in all the cases studied. **Figure 5** shows the voltage profile of several different cases.

From the results obtained by running the optimal power flow without DS (case 01), it is found that the total active losses are 10.89 MW, the LVSI is 0.181 and loading parameter (LP) is 2.1 pu.

In the case of the minimization the TPLI only (case 2), it can be seen that the total active losses are reduced to 2.798 MW, which represents a reduction rate of 74.3%, the LVSI has been improved with 12.7% and loading parameter represents a rate of 52.27%, that is after the integration of 05 DS with a total active power of 122.86 MW and reactive power of 92.13 MVAr distributed to the different sites (busses 7, 9, 12, 18 and 30) respecting all the constraints of the network.

When improving the LVSI only (case 3), the simulation results show that busses 4, 12, 20, 23 and 29 are selected as the best sites for DS power installations producing a total power of 116.54 MW and 87.4 MVAr. This implementation has enhanced the LVSI parameter from the value 0.181 to 0.067, which represents a rate of 62.9%, the losses are reduced to 4.62 MW, which is 57.5% and a loading parameter improvement rate of 63.15%.

The multiobjective optimization (case 04) proved that the results give a compromise between the different values of the minimized objective functions. In this case, the TPLI is improved by 72.9%, LVSI has been minimized by 17.67% and loading parameter has been increased by 59.61%. The advantage of Multi-objective

optimization consists in improving several parameters of the electrical network and

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

**Figure 4** shows that all line powers are below the thermal limit power, which

**Figure 5** shows that all the bus voltages are included between the limits 0.95 pu and 1.1 pu. **Figure 6** illustrates the PV curves before and after the integration of the

**Figure 6** shows the positive influence of DS integration on the voltage stability margin of the IEEE 30 bus network. This figure also shows that case 3 represents the best value of LM, because the objective function only maximizes the voltage

This chapter solves the problem of searching for the optimal location and size of DS in the transmission power system considering the required constraints, using the GA technique. In this work, various objective functions are targeted, minimizing active losses and voltage stability improvement. The last ones are treated as a mono and multi objective problem. The simulations carried out have shown that the results are dependent on the minimized objective function. The results achieved show the efficiency of the GA method. The perspective of this study is to include the constraint related to the transient stability of the rotor angles of conventional generators, in order to maintain the stability of the system during DS disconnection.

having the best compromise.

*(a) LP in case 2, (b) LP in case 3 (c) LP in case 4.*

DS for the three cases.

stability.

**387**

**Figure 6.**

**6. Conclusion**

demonstrates the consideration of line stresses.

**Figure 4.** *Apparent power of the transmission lines for several cases.*

**Figure 5.** *Voltage values of the network bus for several cases.*

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems DOI: http://dx.doi.org/10.5772/intechopen.95266*

**Figure 6.** *(a) LP in case 2, (b) LP in case 3 (c) LP in case 4.*

optimization consists in improving several parameters of the electrical network and having the best compromise.

**Figure 4** shows that all line powers are below the thermal limit power, which demonstrates the consideration of line stresses.

**Figure 5** shows that all the bus voltages are included between the limits 0.95 pu and 1.1 pu. **Figure 6** illustrates the PV curves before and after the integration of the DS for the three cases.

**Figure 6** shows the positive influence of DS integration on the voltage stability margin of the IEEE 30 bus network. This figure also shows that case 3 represents the best value of LM, because the objective function only maximizes the voltage stability.

### **6. Conclusion**

**Figure 4**, shows the situation of apparent power transmitted via transmission lines in all the cases studied. **Figure 5** shows the voltage profile of several different cases. From the results obtained by running the optimal power flow without DS (case 01), it is found that the total active losses are 10.89 MW, the LVSI is 0.181 and

In the case of the minimization the TPLI only (case 2), it can be seen that the total active losses are reduced to 2.798 MW, which represents a reduction rate of 74.3%, the LVSI has been improved with 12.7% and loading parameter represents a rate of 52.27%, that is after the integration of 05 DS with a total active power of 122.86 MW and reactive power of 92.13 MVAr distributed to the different sites (busses 7, 9, 12, 18 and 30) respecting all the constraints of the network.

When improving the LVSI only (case 3), the simulation results show that busses 4, 12, 20, 23 and 29 are selected as the best sites for DS power installations producing a total power of 116.54 MW and 87.4 MVAr. This implementation has enhanced the LVSI parameter from the value 0.181 to 0.067, which represents a rate of 62.9%,

The multiobjective optimization (case 04) proved that the results give a compromise between the different values of the minimized objective functions. In this case, the TPLI is improved by 72.9%, LVSI has been minimized by 17.67% and loading parameter has been increased by 59.61%. The advantage of Multi-objective

the losses are reduced to 4.62 MW, which is 57.5% and a loading parameter

loading parameter (LP) is 2.1 pu.

*Renewable Energy - Technologies and Applications*

improvement rate of 63.15%.

**Figure 4.**

**Figure 5.**

**386**

*Apparent power of the transmission lines for several cases.*

*Voltage values of the network bus for several cases.*

This chapter solves the problem of searching for the optimal location and size of DS in the transmission power system considering the required constraints, using the GA technique. In this work, various objective functions are targeted, minimizing active losses and voltage stability improvement. The last ones are treated as a mono and multi objective problem. The simulations carried out have shown that the results are dependent on the minimized objective function. The results achieved show the efficiency of the GA method. The perspective of this study is to include the constraint related to the transient stability of the rotor angles of conventional generators, in order to maintain the stability of the system during DS disconnection.

## **Acknowledgements**

I thank very sincerely the members of the laboratory of LACoSERE, Electrical Department of the Amar Telidji University, Laghouat, Algeria and laboratory of LAADI, Electrical Department of Djelfa University, Djelfa, Alegria for their participations in the realization of this work.

**Bus i Type Pd(MW) Qd(MVAr) Gs Bs Area Vm Va BaseKV Zone Vmax Vmin** 29 1 2.4 0.9 0 0 1 1.003 17.06 33 1 1.1 0.95 30 1 10.6 1.9 0 0 1 0.992 17.94 33 1 1.1 0.95

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

**(Slim MVA)**

**RateB RateC Ratio Angle Status**

*Base MVA = 100*

*Bus data of IEEE 30 bus power system.*

**Busi Busj R(pu) x(pu) b(pu) RateA**

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

**Table 2.**

**389**

## **Appendix**

The data (lines, consumptions, generators) of the IEEE 30 bus network used in this study are shown below [36]. **Table 2** shows the bus data of the IEEE network studied. **Table 3** represents the line data. **Table 4** shows the data of the conventional generators.


*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems DOI: http://dx.doi.org/10.5772/intechopen.95266*


#### **Table 2.**

**Acknowledgements**

conventional generators.

**Appendix**

**388**

participations in the realization of this work.

*Renewable Energy - Technologies and Applications*

I thank very sincerely the members of the laboratory of LACoSERE, Electrical Department of the Amar Telidji University, Laghouat, Algeria and laboratory of LAADI, Electrical Department of Djelfa University, Djelfa, Alegria for their

The data (lines, consumptions, generators) of the IEEE 30 bus network used in this study are shown below [36]. **Table 2** shows the bus data of the IEEE network

**Bus i Type Pd(MW) Qd(MVAr) Gs Bs Area Vm Va BaseKV Zone Vmax Vmin** 1\* 3 0 0 0 0 1 1.06 0 132 1 1.1 0.95 2 2 21.7 12.7 0 0 1 1.043 5.48 132 1 1.1 0.95 3 1 2.4 1.2 0 0 1 1.021 7.96 132 1 1.1 0.95 4 1 7.6 1.6 0 0 1 1.012 9.62 132 1 1.1 0.95 5 2 94.2 19 0 0 1 1.01 14.37 132 1 1.1 0.95 6 1 0 0 0 0 1 1.01 11.34 132 1 1.1 0.95 7 1 22.8 10.9 0 0 1 1.002 13.12 132 1 1.1 0.95 8 2 30 30 0 0 1 1.01 12.1 132 1 1.1 0.95 9 1 0 0 0 0 1 1.051 14.38 1 1 1.1 0.95 10 1 5.8 2 0 19 1 1.045 15.97 33 1 1.1 0.95 11 2 0 0 0 0 1 1.082 14.39 11 1 1.1 0.95 12 1 11.2 7.5 0 0 1 1.057 15.24 33 1 1.1 0.95 13 2 0 0 0 0 1 1.071 15.24 11 1 1.1 0.95 14 1 6.2 1.6 0 0 1 1.042 16.13 33 1 1.1 0.95 15 1 8.2 2.5 0 0 1 1.038 16.22 33 1 1.1 0.95 16 1 3.5 1.8 0 0 1 1.045 15.83 33 1 1.1 0.95 17 1 9 5.8 0 0 1 1.04 16.14 33 1 1.1 0.95 18 1 3.2 0.9 0 0 1 1.028 16.82 33 1 1.1 0.95 19 1 9.5 3.4 0 0 1 1.026 17 33 1 1.1 0.95 20 1 2.2 0.7 0 0 1 1.03 16.8 33 1 1.1 0.95 21 1 17.5 11.2 0 1 1 1.033 16.42 33 1 1.1 0.95 22 1 0 0 0 0 1 1.033 16.41 33 1 1.1 0.95 23 1 3.2 1.6 0 0 1 1.027 16.61 33 1 1.1 0.95 24 1 8.7 6.7 0 4.3 1 1.021 16.78 33 1 1.1 0.95 25 1 0 0 0 0 1 1.017 16.35 33 1 1.1 0.95 26 1 3.5 2.3 0 0 1 1 16.77 33 1 1.1 0.95 27 1 0 0 0 0 1 1.023 15.82 33 1 1.1 0.95 28 1 0 0 0 0 1 1.007 11.97 132 1 1.1 0.95

studied. **Table 3** represents the line data. **Table 4** shows the data of the

*Bus data of IEEE 30 bus power system.*



**References**

(ICSRESA), 2019.

28, Apr. 1999.

Wiley ISTE, 2011.

2017.

[1] Y. Bakelli, M. Mosbah, A. Kaabeche,

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

[9] U.Sultana, al, "A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system" Renewable and Sustainable Energy Reviews, vol. 63,

[10] A. R. Jordehi, "Allocation of distributed generation units in electric power systems: A review" Renewable and Sustainable Energy Reviews, Vol.56,

distributed generation" IEEE

capacitor banks and distributed

[13] K. H.Truong et al, "A Quasi-Oppositional-Chaotic Symbiotic

[14] Adel A. Abou El-Ela, R. A. El-Sehiemy, A. S. Abbas, "Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm" IEEE Systems Journal, vol.

12, pp. 3629–3636, 2018.

[15] S. H. Lee, J. W. Park, "Optimal placement and sizing of multiple DGs in a practical distribution system by considering power loss"IEEE

Transactions on Industry Applications,

vol. 49, pp. 2262–2270, 2013.

[11] R. S. Al Abri, E. F. El-Saadany, Y. M. Atwa, "Optimal placement and sizing method to improve the voltage stability margin in a distribution system using

Transactions on Power Systems" vol. 28,

[12] M. Dehghani, Z. Montazeriand O. P. Malik, "Optimal sizing and placement of

generation in distribution systems using spring search algorithm" International Journal of Emerging Electric Power

Organisms Search algorithm for optimal allocation of DG in radial distribution networks" Applied Soft Computing, vol.

pp. 363–378, 2016.

pp.893–905, 2016.

pp. 326–334, 2012.

Systems, vol. 21, 2020.

88, 2020.

and M. Acimi, 'Voltage stability improvement by optimal location of wind sources', 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications

[2] N. Hadjsaid, J. F. Canard, and F. Dumas, "Dispersed generation impact on distribution networks," IEEE Comput. Appl. Power, vol. 12, pp. 22–

[3] N. Hadjsaïd, J. C. Sabonnadière, Electrical distribution networks.

optimizing PV-DG allocation in power system and solar energy resource potential assessments, Energy Reports,

[5] V. Mytilinou, A. J. Kolios, "A multiobjective optimisation approach applied

selection" Journal of Ocean Engineering and Marine Energy vol. 3, pp. 265–284,

[6] P. Barker, T. Leskan, H. Zaininger

distributed resources in electric utility systems: current interconnection practice and unified approach" EPRI

[7] W. El-khattam, et al, "Optimal investment planning for distributed generation in a competitive electricity markets" IEEE Tran Power Sys, vol. 19,

[8] P. Kayal, C.K. Chanda, "Placement of

[4] R. O. Bawazir, N. S.Cetin, "Comprehensive overview of

Vol. 6, pp. 173–208, 2020.

to offshore wind farm location

and D. Smith, "Integration of

TR-111489, Nov 1998.

pp. 1674–84, 2004.

**391**

wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement" Int J Electr Power Energy Syst, vol. 53, pp. 795–809 2013.

#### **Table 3.**

*Line data of IEEE 30 bus power system.*


#### **Table 4.**

*Generator data of IEEE 30 bus power system.*

## **Author details**

Mustafa Mosbah<sup>1</sup> \*, Redha Djamel Mohammedi<sup>2</sup> and Salem Arif<sup>1</sup>

1 Laboratoire d'Analyse et de Commande des Systèmes d'Energie et Réseaux Electriques (LACoSERE), Amar Telidji University, Laghouat, Alegria

2 Laboratoire d'Automatique Appliquée et Diagnostic Industriel (LAADI), Djelfa University, Djelfa, Alegria

\*Address all correspondence to: m.mosbah@lagh-univ.dz

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems DOI: http://dx.doi.org/10.5772/intechopen.95266*

## **References**

[1] Y. Bakelli, M. Mosbah, A. Kaabeche, and M. Acimi, 'Voltage stability improvement by optimal location of wind sources', 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA), 2019.

[2] N. Hadjsaid, J. F. Canard, and F. Dumas, "Dispersed generation impact on distribution networks," IEEE Comput. Appl. Power, vol. 12, pp. 22– 28, Apr. 1999.

[3] N. Hadjsaïd, J. C. Sabonnadière, Electrical distribution networks. Wiley ISTE, 2011.

[4] R. O. Bawazir, N. S.Cetin, "Comprehensive overview of optimizing PV-DG allocation in power system and solar energy resource potential assessments, Energy Reports, Vol. 6, pp. 173–208, 2020.

[5] V. Mytilinou, A. J. Kolios, "A multiobjective optimisation approach applied to offshore wind farm location selection" Journal of Ocean Engineering and Marine Energy vol. 3, pp. 265–284, 2017.

[6] P. Barker, T. Leskan, H. Zaininger and D. Smith, "Integration of distributed resources in electric utility systems: current interconnection practice and unified approach" EPRI TR-111489, Nov 1998.

[7] W. El-khattam, et al, "Optimal investment planning for distributed generation in a competitive electricity markets" IEEE Tran Power Sys, vol. 19, pp. 1674–84, 2004.

[8] P. Kayal, C.K. Chanda, "Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement" Int J Electr Power Energy Syst, vol. 53, pp. 795–809 2013.

[9] U.Sultana, al, "A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system" Renewable and Sustainable Energy Reviews, vol. 63, pp. 363–378, 2016.

[10] A. R. Jordehi, "Allocation of distributed generation units in electric power systems: A review" Renewable and Sustainable Energy Reviews, Vol.56, pp.893–905, 2016.

[11] R. S. Al Abri, E. F. El-Saadany, Y. M. Atwa, "Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation" IEEE Transactions on Power Systems" vol. 28, pp. 326–334, 2012.

[12] M. Dehghani, Z. Montazeriand O. P. Malik, "Optimal sizing and placement of capacitor banks and distributed generation in distribution systems using spring search algorithm" International Journal of Emerging Electric Power Systems, vol. 21, 2020.

[13] K. H.Truong et al, "A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for optimal allocation of DG in radial distribution networks" Applied Soft Computing, vol. 88, 2020.

[14] Adel A. Abou El-Ela, R. A. El-Sehiemy, A. S. Abbas, "Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm" IEEE Systems Journal, vol. 12, pp. 3629–3636, 2018.

[15] S. H. Lee, J. W. Park, "Optimal placement and sizing of multiple DGs in a practical distribution system by considering power loss"IEEE Transactions on Industry Applications, vol. 49, pp. 2262–2270, 2013.

**Author details**

**Table 3.**

**Table 4.**

**390**

**Bus Pg (MW)**

*Line data of IEEE 30 bus power system.*

**Qg (MVAr)**

*Generator data of IEEE 30 bus power system.*

**Qmax (MVAr)**

**Qmin (MVAr)**

1 0 0 200 20 1.06 100 1 200 50 2 50.5846 0 100 20 1.045 100 1 80 20 5 18.5227 0 50 15 1.02 100 1 50 15 8 18.0865 0 60 15 1.029 100 1 35 10 11 10.4038 0 50 10 1.06 100 1 30 10 13 13.2553 0 60 15 1.06 100 1 40 12

Mustafa Mosbah<sup>1</sup>

University, Djelfa, Alegria

\*, Redha Djamel Mohammedi<sup>2</sup> and Salem Arif<sup>1</sup>

2 Laboratoire d'Automatique Appliquée et Diagnostic Industriel (LAADI), Djelfa

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

1 Laboratoire d'Analyse et de Commande des Systèmes d'Energie et Réseaux

Electriques (LACoSERE), Amar Telidji University, Laghouat, Alegria

\*Address all correspondence to: m.mosbah@lagh-univ.dz

**Busi Busj R(pu) x(pu) b(pu) RateA**

*Renewable Energy - Technologies and Applications*

**(Slim MVA)**

24 25 0.1885 0.3292 0 16 0 0 0 0 1 25 26 0.2544 0.38 0 16 0 0 0 0 1 25 27 0.1093 0.2087 0 16 0 0 0 0 1 28 27 0 0.396 0 65 0 0 0.968 0 1 27 29 0.2198 0.4153 0 16 0 0 0 0 1 27 30 0.3202 0.6027 0 16 0 0 0 0 1 29 30 0.2399 0.4533 0 16 0 0 0 0 1 8 28 0.0636 0.2 0.0428 32 0 0 0 0 1 6 28 0.0169 0.0599 0.013 32 0 0 0 0 1

**RateB RateC Ratio Angle Status**

**Vg S Base Status Pmax**

**(MW)**

**Pmin (MW)**

provided the original work is properly cited.

[16] A. Picciariello, et al, "Distributed generation and distribution pricing: why do we need new tariff design methodologies?" Electr Power Sys Rev, vol. 6, pp. 119–370, 2015.

[17] M. S. Syed, S. V. Chintalapudi, S. Sirigiri, "Optimal power flow solution in the presence of renewable energy sources" Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. xx, pp. xxx–xxx, 2020.

[18] Phung DangHuy, al, "Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage" Energy,vol. 195, pp. 110–117, 2020.

[19] A. Tamimi, A. Pahwa, S. Starrett, "Maximizing wind penetration using voltage stability based methods for sizing and locating new wind farms in power system" In: Power and Energy Society General Meeting, vol. xx, pp. 1– 7, 2010.

[20] S. Ghosh, et al, "Optimal sizing and placement of distributed generation in a network system" Electrical Power and Energy Systems,vol.32, pp. 849–856, 2010.

[21] R.K. Singh, S.K. Goswami, "Optimum allocation of distributed generations based on nodal pricing for profit,loss reduction, and voltage improvement including voltage rise issue" Electrical Power and Energy Systems, vol. 32,pp. 637–644, 2010.

[22] M. Mosbah., A. Khattara, M. Becherif, S. Arif, "Optimal PV location choice considering static and dynamic constraints" Int. J. Emerg Electr Power Syst, vol. 18, 2016.

[23] A. Shuaibu Hassan, Y. Sun, Z. Wang, "Multi-objective for optimal placement and sizing DG units in reducing loss of power and enhancing voltage profile using BPSO-SLFA"

Energy Reports, vol. 6, pp. 1581–1589, 2020.

[31] R. Bawazir, N. Çetin M. Mosbah, S. Arif, "Genetic algorithm for improving voltage stability by optimal integration

*DOI: http://dx.doi.org/10.5772/intechopen.95266*

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems*

Conference on Electrical Engineering (ICEE) September 25–27, Istanbul,

[33] M. Mosbah, R. D. Mohammedi, S. Arif, "Differential evolution method for

optimal size and localization of photovoltaic in the algerian transmission power system" In: Proceedings of 2019 Algerian Large Electrical Network Conference (CAGRE-2019), pp. 1–6, 2019.

[34] M. Reza et al, "Impacts of distributed generation penetration levels on power systems transient stability" In Proceedings of the IEEE Power Engineering Society General Meeting, Denver, USA, June 2004.

of Michigan Press, 1975.

system data," October 2017.

**393**

[35] J. H. Holland "Adaptation in Nature and Artificial Systems" The University

[36] The University of Washington Electrical Engineering, "Power system test case archive, the IEEE 30-bus test

of wind source" International

[32] M. Moghavvemi, F. Omar, "Transmission, and Distribution, "Technique for contingency monitoring and voltage collapse prediction" vol.

145, pp. 634–640, 1998.

Turkey, 2020.

[24] A. S. O. Ogunjuyigbe, T. R. Ayodele, O. O. Akinola, "Impact of distributed generators on the power loss and voltage profile of sub-transmission network" J. Electr. Syst. Inf. Technol, vol. 3, pp. 94–107, 2016.

[25] H. C. Nejad et al, "Reliability based optimal allocation of distributed generations in transmission systems under demand response program" Electric Power Systems Research, vol. 176, 2019.

[26] C. Wang, M. H. Nehrir, Analytical approaches for optimal placement of distributed generation sources in power systems, IEEE Trans. Power Syst, vol. 19, pp. 2068–2076, 2004.

[27] S. Kabir, O. Krause, S. Bartlett, "Impact of large-scale photovoltaic system on short and long term voltage stability in sub transmission networl, Australas. Univ. Power Eng. Conf. AUPEC (October) (2013) 1–6.

[28] A. A. Sadiq, S. S. Adamu, M. Buhari, "Optimal distributed generation planning in distribution networks: A comparison of transmission network models with FACTS" Engineering Science and Technology, an International Journal, vol. 22, pp. 33–46, 2019.

[29] A. Ogunjuyigbe, T. Ayodele, O. Akinola, "Impact of distributed generators on the power loss and voltage profile of sub-transmission network" J. Electr. Syst. Inf. Technol, vol. 3, pp. 94– 107, 2016.

[30] M. Mosbah, et al, "Optimal location and size of wind source in large power system for losses minimization" International Conference in Artificial Intelligence in Renewable Energetic Systems ICAIRES 2019: Smart Energy Empowerment in Smart and Resilient Cities, vol. 102, pp 566–574, 2019.

*Distributed Sources Optimal Sites and Sizes Search in Large Power Systems DOI: http://dx.doi.org/10.5772/intechopen.95266*

[31] R. Bawazir, N. Çetin M. Mosbah, S. Arif, "Genetic algorithm for improving voltage stability by optimal integration of wind source" International Conference on Electrical Engineering (ICEE) September 25–27, Istanbul, Turkey, 2020.

[16] A. Picciariello, et al, "Distributed generation and distribution pricing: why

*Renewable Energy - Technologies and Applications*

Energy Reports, vol. 6, pp. 1581–1589,

[24] A. S. O. Ogunjuyigbe, T. R. Ayodele, O. O. Akinola, "Impact of distributed generators on the power loss and voltage profile of sub-transmission network" J. Electr. Syst. Inf. Technol, vol. 3,

[25] H. C. Nejad et al, "Reliability based optimal allocation of distributed generations in transmission systems under demand response program" Electric Power Systems Research, vol.

[26] C. Wang, M. H. Nehrir, Analytical approaches for optimal placement of distributed generation sources in power systems, IEEE Trans. Power Syst, vol.

[27] S. Kabir, O. Krause, S. Bartlett, "Impact of large-scale photovoltaic system on short and long term voltage stability in sub transmission networl, Australas. Univ. Power Eng. Conf. AUPEC (October) (2013) 1–6.

[28] A. A. Sadiq, S. S. Adamu, M. Buhari,

"Optimal distributed generation planning in distribution networks: A comparison of transmission network models with FACTS" Engineering Science and Technology, an International

Journal, vol. 22, pp. 33–46, 2019.

107, 2016.

[29] A. Ogunjuyigbe, T. Ayodele, O. Akinola, "Impact of distributed

generators on the power loss and voltage profile of sub-transmission network" J. Electr. Syst. Inf. Technol, vol. 3, pp. 94–

[30] M. Mosbah, et al, "Optimal location and size of wind source in large power system for losses minimization" International Conference in Artificial Intelligence in Renewable Energetic Systems ICAIRES 2019: Smart Energy Empowerment in Smart and Resilient Cities, vol. 102, pp 566–574, 2019.

19, pp. 2068–2076, 2004.

2020.

pp. 94–107, 2016.

176, 2019.

methodologies?" Electr Power Sys Rev,

[17] M. S. Syed, S. V. Chintalapudi, S. Sirigiri, "Optimal power flow solution in the presence of renewable energy sources" Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. xx, pp. xxx–xxx, 2020.

[18] Phung DangHuy, al, "Optimal placement, sizing and power factor of

comprehensive study spanning from the planning stage to the operation stage" Energy,vol. 195, pp. 110–117, 2020.

[19] A. Tamimi, A. Pahwa, S. Starrett, "Maximizing wind penetration using voltage stability based methods for sizing and locating new wind farms in power system" In: Power and Energy Society General Meeting, vol. xx, pp. 1–

[20] S. Ghosh, et al, "Optimal sizing and placement of distributed generation in a network system" Electrical Power and Energy Systems,vol.32, pp. 849–856,

[21] R.K. Singh, S.K. Goswami, "Optimum allocation of distributed generations based on nodal pricing for profit,loss reduction, and voltage improvement including voltage rise issue" Electrical Power and Energy Systems, vol. 32,pp. 637–644, 2010.

[22] M. Mosbah., A. Khattara, M. Becherif, S. Arif, "Optimal PV location choice considering static and dynamic constraints" Int. J. Emerg Electr Power

[23] A. Shuaibu Hassan, Y. Sun, Z. Wang, "Multi-objective for optimal placement and sizing DG units in reducing loss of power and enhancing voltage profile using BPSO-SLFA"

Syst, vol. 18, 2016.

**392**

distributed generation: A

7, 2010.

2010.

do we need new tariff design

vol. 6, pp. 119–370, 2015.

[32] M. Moghavvemi, F. Omar, "Transmission, and Distribution, "Technique for contingency monitoring and voltage collapse prediction" vol. 145, pp. 634–640, 1998.

[33] M. Mosbah, R. D. Mohammedi, S. Arif, "Differential evolution method for optimal size and localization of photovoltaic in the algerian transmission power system" In: Proceedings of 2019 Algerian Large Electrical Network Conference (CAGRE-2019), pp. 1–6, 2019.

[34] M. Reza et al, "Impacts of distributed generation penetration levels on power systems transient stability" In Proceedings of the IEEE Power Engineering Society General Meeting, Denver, USA, June 2004.

[35] J. H. Holland "Adaptation in Nature and Artificial Systems" The University of Michigan Press, 1975.

[36] The University of Washington Electrical Engineering, "Power system test case archive, the IEEE 30-bus test system data," October 2017.

**395**

**Chapter 23**

**Abstract**

**1. Introduction**

and lower fuel consumption.

corresponding CEAP specified.

*Jushan Chin and Jin Dang*

New Generation Aero Combustor

The purpose of this study is to identify the technology for next generation aero combustors, and to propose totally new combustor design approaches. Next generation aero combustors need very high combustion air fraction, that brings idle lean blow out (LBO) problem. The present study suggests several measures to solve this problem, including: pilot and main two concentric combustion zones with separation, aerodynamic design to have main air slipping by pilot combustion zones, etc. For high fuel air ratio (FAR) combustor, the present authors propose using angled main fuel co-axial air plain jet injection. Make use of different penetration to meet the need for low power and high power conditions. For low emissions combustor, the present authors use small scale close contact fuel-air mixing with fuel staging to have low emissions at the same time to have good idle, good high altitude ignition, etc. Brand new cooling designs are proposed for outliner and inner liner. This chapter is mainly a survey of present author's own research. The results of this study will provide guideline for the development of next generation aero combustors.

**Keywords:** low emissions combustor, high FAR combustor, fuel air module design,

Aero gas turbine engine combustors have been developed over 80 years. It does not matter if it is a civil engine combustor, or military engine combustor. They are all developed under one line, that is, towards higher performance, higher reliability,

On 1977, International Civil Aviation Organization (ICAO) published a document named "Control of Aircraft Engine Emissions". Since then aero combustors have entered a new era, it is that of low emissions combustors. The requirements for low emissions are different for civil aero combustor versus military aero combustor. For civil aero combustors, their emissions are regulated by ICAO Committee on Aviation Environmental Protection (CEAP) [1]. The standard has been developed from CEAP 1, CEAP 2, CEAP 4, CEAP 6, now it is CEAP 8. It is getting more and more restrictive. Now-a-days, any civil aero engine thrust higher than 26.7 KN must be in accordance with the CEAP 8 standard. Their emissions of nitrous oxide (NOx), carbon monoxide (CO), unburnt hydrocarbon (UHC), and smoke shall all be controlled. Actually, an aero engine company is required to report the percentage their engine combustor will produce of each type of emission lower than the

liner cooling design, lean direct mixing combustion, idle LBO

What are new generation aero combustors?

## **Chapter 23**

## New Generation Aero Combustor

*Jushan Chin and Jin Dang*

## **Abstract**

The purpose of this study is to identify the technology for next generation aero combustors, and to propose totally new combustor design approaches. Next generation aero combustors need very high combustion air fraction, that brings idle lean blow out (LBO) problem. The present study suggests several measures to solve this problem, including: pilot and main two concentric combustion zones with separation, aerodynamic design to have main air slipping by pilot combustion zones, etc. For high fuel air ratio (FAR) combustor, the present authors propose using angled main fuel co-axial air plain jet injection. Make use of different penetration to meet the need for low power and high power conditions. For low emissions combustor, the present authors use small scale close contact fuel-air mixing with fuel staging to have low emissions at the same time to have good idle, good high altitude ignition, etc. Brand new cooling designs are proposed for outliner and inner liner. This chapter is mainly a survey of present author's own research. The results of this study will provide guideline for the development of next generation aero combustors.

**Keywords:** low emissions combustor, high FAR combustor, fuel air module design, liner cooling design, lean direct mixing combustion, idle LBO

## **1. Introduction**

What are new generation aero combustors?

Aero gas turbine engine combustors have been developed over 80 years. It does not matter if it is a civil engine combustor, or military engine combustor. They are all developed under one line, that is, towards higher performance, higher reliability, and lower fuel consumption.

On 1977, International Civil Aviation Organization (ICAO) published a document named "Control of Aircraft Engine Emissions". Since then aero combustors have entered a new era, it is that of low emissions combustors. The requirements for low emissions are different for civil aero combustor versus military aero combustor. For civil aero combustors, their emissions are regulated by ICAO Committee on Aviation Environmental Protection (CEAP) [1]. The standard has been developed from CEAP 1, CEAP 2, CEAP 4, CEAP 6, now it is CEAP 8. It is getting more and more restrictive. Now-a-days, any civil aero engine thrust higher than 26.7 KN must be in accordance with the CEAP 8 standard. Their emissions of nitrous oxide (NOx), carbon monoxide (CO), unburnt hydrocarbon (UHC), and smoke shall all be controlled. Actually, an aero engine company is required to report the percentage their engine combustor will produce of each type of emission lower than the corresponding CEAP specified.

Because of the requirement of continuous improvement for reduction of fuel consumption, civil aero engines have development in two aspects. An aero engine as a propulsion unit has propulsion efficiency. This is to increase bypass ratio. On the other aspect, an aero engine is also a thermal engine, it has thermal efficiency. The way to improve its thermal efficiency is to increase the pressure ratio of the engine (at the same time, increase turbine inlet temperature appropriately). Thus, for several decades engine pressure ratio has been going up all the time, from nearly 10, then 20, 30, 40, 50, and pressure ratio 60 aero engines has been certified, will be in service soon. New generation civil aero engines will achieve a high pressure ratio of 70.

### **Conclusion: a new generation civil aero combustor is a high pressure low emissions combustor.**

For a military aero engine, the most important development target is to have a higher thrust-to-weight ratio. In order to improve thrust-to-weight ratio, the engine shall have higher turbine inlet temperature (or higher combustor fuel air ratio, FAR) and increase the engine pressure ratio appropriately. Thus, the military aero combustor FAR has been increased from lower than 0.02 to 0.03, to 0.038, to 0.046. The new generation military aero combustor will have FAR, 0.051. Notice that a high FAR combustor is also called a high temperature rise combustor.

**Conclusion: new generation military aero combustor is high FAR combustor.**

## **2. Design of high FAR combustor**

For a military aero combustor, there is no 30% power condition, no 85% power condition, and no maximum cruise condition. There is a ground idle condition, maximum power condition (or 100% power condition) and cruise conditions at different altitudes and different Mach numbers. There is a high altitude idle condition. Particularly there is low altitude not-so-low Mach number penetration dash condition. In this condition, the combustor inlet pressure may be even higher than at the take-off condition. The inlet air temperature is very close to the take-off condition and FAR is only a little lower than take-off condition. At this condition, liner wall temperature higher than that at take-off condition is possible.

Don Bahr [2] reported that there are two major problems for high temperature rise combustor design; they are idle lean blow out (LBO) and liner cooling. According to present author's experience, it is true that these two issues are critical for high FAR combustor design and development. But there are other issues too. The design reported in this chapter is mainly from reference [3].

#### **2.1 Idle LBO**

For military aero combustor idle LBO issues, the present author proposed several design approaches. One approach is that, there is a concentric "twin" combustion zone concept. That is, the pilot fuel air combustion zone is at the center, main fuel air combustion zone is surrounding the pilot fuel air combustion zone, with some separation. Significantly, a reduction of the main air quenching effect on pilot fuel air combustion is performed. This is the way to improve idle LBO. The annular combustor has several fuel air modules, the fuel air module configuration is shown in **Figure 1**. This multiple swirler dome design is very different from reference [4]. The pilot fuel air module consists of a pressure swirl fuel nozzle and an axial air swirler. The main air module has a distance radially away from pilot module. This distance is from pilot module exit diameter to the inner diameter of main module annular exit. In this design it is 0.95 in.

**397**

**Figure 2.**

*Air flow pattern [3].*

**Figure 1.**

*Fuel-air module [3].*

*New Generation Aero Combustor*

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

The second design approach for solving idle LBO issue is the combustion zone aerodynamics. As shown in **Figure 1**, the main air module consists of two portions, one third is non-swirling air on inner side and two thirds is swirling air. The pilot module air is having weak swirling. Together with the separation distance, the combustion zone aerodynamics is shown in **Figure 2**. The combustion aerodynamics is low swirling. But in the present design, there is combination of swirling air and non-swirling air, which is rather different from reference [5]. The key feature is that the main air flow is just slipping and passing through pilot air recirculation without mixing with pilot air, that is the most important factor for reducing main

air quenching effect on idle condition pilot fuel air combustion.

### *New Generation Aero Combustor DOI: http://dx.doi.org/10.5772/intechopen.93916*

*Renewable Energy - Technologies and Applications*

ratio of 70.

**emissions combustor.**

**2. Design of high FAR combustor**

Because of the requirement of continuous improvement for reduction of fuel consumption, civil aero engines have development in two aspects. An aero engine as a propulsion unit has propulsion efficiency. This is to increase bypass ratio. On the other aspect, an aero engine is also a thermal engine, it has thermal efficiency. The way to improve its thermal efficiency is to increase the pressure ratio of the engine (at the same time, increase turbine inlet temperature appropriately). Thus, for several decades engine pressure ratio has been going up all the time, from nearly 10, then 20, 30, 40, 50, and pressure ratio 60 aero engines has been certified, will be in service soon. New generation civil aero engines will achieve a high pressure

**Conclusion: a new generation civil aero combustor is a high pressure low** 

For a military aero engine, the most important development target is to have a higher thrust-to-weight ratio. In order to improve thrust-to-weight ratio, the engine shall have higher turbine inlet temperature (or higher combustor fuel air ratio, FAR) and increase the engine pressure ratio appropriately. Thus, the military aero combustor FAR has been increased from lower than 0.02 to 0.03, to 0.038, to 0.046. The new generation military aero combustor will have FAR, 0.051. Notice that a

**Conclusion: new generation military aero combustor is high FAR combustor.**

For a military aero combustor, there is no 30% power condition, no 85% power condition, and no maximum cruise condition. There is a ground idle condition, maximum power condition (or 100% power condition) and cruise conditions at different altitudes and different Mach numbers. There is a high altitude idle condition. Particularly there is low altitude not-so-low Mach number penetration dash condition. In this condition, the combustor inlet pressure may be even higher than at the take-off condition. The inlet air temperature is very close to the take-off condition and FAR is only a little lower than take-off condition. At this condition,

Don Bahr [2] reported that there are two major problems for high temperature rise combustor design; they are idle lean blow out (LBO) and liner cooling. According to present author's experience, it is true that these two issues are critical for high FAR combustor design and development. But there are other issues too. The design

For military aero combustor idle LBO issues, the present author proposed several design approaches. One approach is that, there is a concentric "twin" combustion zone concept. That is, the pilot fuel air combustion zone is at the center, main fuel air combustion zone is surrounding the pilot fuel air combustion zone, with some separation. Significantly, a reduction of the main air quenching effect on pilot fuel air combustion is performed. This is the way to improve idle LBO. The annular combustor has several fuel air modules, the fuel air module configuration is shown in **Figure 1**. This multiple swirler dome design is very different from reference [4]. The pilot fuel air module consists of a pressure swirl fuel nozzle and an axial air swirler. The main air module has a distance radially away from pilot module. This distance is from pilot module exit diameter to the inner diameter of main module annular exit.

high FAR combustor is also called a high temperature rise combustor.

liner wall temperature higher than that at take-off condition is possible.

reported in this chapter is mainly from reference [3].

**396**

In this design it is 0.95 in.

**2.1 Idle LBO**

The second design approach for solving idle LBO issue is the combustion zone aerodynamics. As shown in **Figure 1**, the main air module consists of two portions, one third is non-swirling air on inner side and two thirds is swirling air. The pilot module air is having weak swirling. Together with the separation distance, the combustion zone aerodynamics is shown in **Figure 2**. The combustion aerodynamics is low swirling. But in the present design, there is combination of swirling air and non-swirling air, which is rather different from reference [5]. The key feature is that the main air flow is just slipping and passing through pilot air recirculation without mixing with pilot air, that is the most important factor for reducing main air quenching effect on idle condition pilot fuel air combustion.

**Figure 1.** *Fuel-air module [3].*

**Figure 2.** *Air flow pattern [3].*

The third design approach for solving idle LBO issue is design of pilot fuel air combustion. Pilot fuel air combustion, pilot air alone module and pilot fuel nozzle are designed at idle condition, not at maximum condition. For high FAR combustor, its idle condition FAR is higher than idle FAR for civil combustor. At the idle condition, if only the pilot fuel is working, when approaching flame out, the pilot fuel nozzle pressure drop will be very low, which is harmful for LBO (it is not practical that at idle condition pilot fuel nozzle pressure drop is extremely high, such as higher than 200 psig). Thus, it needs main fuel to be open to work together with pilot fuel combustion. At the idle condition, its fuel flow is split at 70% pilot fuel and 30% main fuel. 70% idle fuel flow together with pilot module air to form an idle pilot fuel combustion at equivalence ratio 1.2 and based on this design criteria to determine pilot air fraction within the combustion air. At idle condition, 30% main fuel with co-flowing air to provide idle main fuel combustion equivalence ratio 1.2 to determine co-flowing air amount. At idle condition, the main fuel injection pressure drop is very low, main fuel jet spray with co-flowing air is collapsed with pilot fuel combustion. Pilot fuel nozzle operation is designed at idle. At idle condition pilot fuel nozzle pressure drop is 120 psig. Based on this design approach to determine pilot fuel nozzle flow number (FN). There is a flow divider valve between the pilot fuel nozzle and the main fuel injector. The crack pressure for this flow divider valve is a critical design parameter. It needs to have an initial choice, then after both pilot fuel and main fuel design finished for the whole power condition range, it may be modified several times. Pilot fuel nozzle spray angle is 90 degree. The pilot air module inlet swirler is a thin curved blade low swirling axial swirler. The inlet effective flow area (ACd) is much higher than exit ACd to let the exit be the flow metering device.

High FAR combustor idle LBO design is related to many aspects. There are several design choices which must be balanced, making many times modification to have an all-round good solution. These design choices are:


The final design shall have good idle LBO, appropriate maximum condition pilot fuel and main fuel combustion equivalence ratio (none of them may exceed 1.2), and a maximum fuel nozzle pressure drop which is not higher than 800 psig.

**399**

because there is no dilution air.

**3.1 Combustion efficiency**

**3. Other issues**

*New Generation Aero Combustor*

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

Design of maximum condition is to reach both pilot fuel and main fuel combustion near stoichiometric combustion to determine the total combustion air fraction [3]. For example, if the combustor FAR is 0.051, combustion air is 75% to have combustion FAR 0.051/0.75 = 0.068, which is an equivalence ratio of one. Then the main fuel combustion air fraction is total combustion air minus the pilot combustion air fraction. Main fuel air combustion design is concentrated on main fuel injection. As shown in **Figure 1**, main fuel is co-axial air flowing plain jet fuel injection. There is an angle, between main injection center line and module center line, which is 15 degree in this design. This injection angle is a critical design choice. At the low power condition, main fuel injection pressure drop is very low, main fuel will not penetrate far away, thus main fuel will burn with pilot fuel combustion. At maximum power condition, main fuel injection pressure drop is very high, the spray will penetrate radially out to meet main air to form direct mixing combustion. Here the **design idea is to make use of the change of penetration to suit low power condition and high-power condition** [3]. That is the reason why the main fuel injection must be with an angle relative to module center line. Main fuel injection pressure drop at maximum condition is very high, hopefully higher than 600 psig. Somewhere between 40% to 60% power condition, there will be a situation the main fuel spray will detach from the pilot fuel combustion to form a separate main fuel air combustion zone. Main fuel penetration and mixing with main air is critical to form non-visible smoke, to have non-luminous flame, to have high efficiency at maximum power condition. Because of the need for high penetration, the main fuel injector is not a hole, but a **section of straight tubing of diameter 0.03 in**. Notice that the present author does not call main fuel injection as co-axial air blast atomization, but rather air co-flowing plain jet injection. In studies on such injection, it was found that under very low liquid injection pressure drop, it is air blast atomization, at medium injection pressure drop, it is air assist atomization, with very high liquid injection pressure drop, it is air retard atomization. Air retard atomization is a new term. It is a case where air does not help atomization of a finer drop size, but hurts atomization by becoming a coarser drop size. Actually, this is good. This is because with very fine droplets, the spray cannot penetrate far out, while for main fuel combustion, at high power condition, penetration is more important than drop size. But it is not the more penetration the better, for fuel injection the present author shall take atomization,

penetration, dispersion and fuel air mixing all four aspects into consideration. Notice that the circumferential distribution of main fuel injectors may be uniform or may be non-uniform. For example, main fuel injector positioning may start other than 12 o'clock position. The different main fuel injector circumferential arrangement is for minor adjustment of exit radial temperature and FAR profile

High FAR combustor has a combustion efficiency issue. Some designer mentioned that for high FAR combustor, at maximum power condition, its efficiency can only be 98%, it is because of chemical dissociation. The present author has studied chemical dissociation. It will have significant effect on efficiency at higher temperature. For aviation kerosene and air combustion, at stoichiometric fuel air ratio, the effect of chemical dissociation will not be so much. Thus, for well-organized high

FAR combustion, its combustion efficiency shall be higher than 98%.

**2.2 Design of maximum condition**

**Conclusion: with these design measures, a high FAR combustor idle LBO problem is solved** [3].

## **2.2 Design of maximum condition**

*Renewable Energy - Technologies and Applications*

have an all-round good solution. These design choices are:

• Idle condition, main fuel injection pressure drops

required maximum pump pressure capability)

• Idle condition, pilot fuel combustion equivalence ratio (determine pilot

• Idle condition main fuel and coaxial flowing air FAR ratio (determine

• Idle condition, pilot fuel nozzle pressure drops (determine pilot nozzle flow

• Flow divider valve crack pressure (affect at maximum condition, difference of injection pressure drop between pilot nozzle and main fuel injector, affect

• Maximum condition pilot fuel and main fuel division (determine maximum condition pilot fuel combustion and main fuel combustion equivalence ratio)

The final design shall have good idle LBO, appropriate maximum condition pilot fuel and main fuel combustion equivalence ratio (none of them may exceed 1.2), and a maximum fuel nozzle pressure drop which is not higher than 800 psig. **Conclusion: with these design measures, a high FAR combustor idle LBO** 

• Idle condition, main fuel-pilot fuel division

combustion air fraction).

co-flowing air amount)

number)

**problem is solved** [3].

The third design approach for solving idle LBO issue is design of pilot fuel air combustion. Pilot fuel air combustion, pilot air alone module and pilot fuel nozzle are designed at idle condition, not at maximum condition. For high FAR combustor, its idle condition FAR is higher than idle FAR for civil combustor. At the idle condition, if only the pilot fuel is working, when approaching flame out, the pilot fuel nozzle pressure drop will be very low, which is harmful for LBO (it is not practical that at idle condition pilot fuel nozzle pressure drop is extremely high, such as higher than 200 psig). Thus, it needs main fuel to be open to work together with pilot fuel combustion. At the idle condition, its fuel flow is split at 70% pilot fuel and 30% main fuel. 70% idle fuel flow together with pilot module air to form an idle pilot fuel combustion at equivalence ratio 1.2 and based on this design criteria to determine pilot air fraction within the combustion air. At idle condition, 30% main fuel with co-flowing air to provide idle main fuel combustion equivalence ratio 1.2 to determine co-flowing air amount. At idle condition, the main fuel injection pressure drop is very low, main fuel jet spray with co-flowing air is collapsed with pilot fuel combustion. Pilot fuel nozzle operation is designed at idle. At idle condition pilot fuel nozzle pressure drop is 120 psig. Based on this design approach to determine pilot fuel nozzle flow number (FN). There is a flow divider valve between the pilot fuel nozzle and the main fuel injector. The crack pressure for this flow divider valve is a critical design parameter. It needs to have an initial choice, then after both pilot fuel and main fuel design finished for the whole power condition range, it may be modified several times. Pilot fuel nozzle spray angle is 90 degree. The pilot air module inlet swirler is a thin curved blade low swirling axial swirler. The inlet effective flow area (ACd) is much higher than exit ACd to let the exit be the flow metering device. High FAR combustor idle LBO design is related to many aspects. There are several design choices which must be balanced, making many times modification to

**398**

Design of maximum condition is to reach both pilot fuel and main fuel combustion near stoichiometric combustion to determine the total combustion air fraction [3]. For example, if the combustor FAR is 0.051, combustion air is 75% to have combustion FAR 0.051/0.75 = 0.068, which is an equivalence ratio of one. Then the main fuel combustion air fraction is total combustion air minus the pilot combustion air fraction.

Main fuel air combustion design is concentrated on main fuel injection. As shown in **Figure 1**, main fuel is co-axial air flowing plain jet fuel injection. There is an angle, between main injection center line and module center line, which is 15 degree in this design. This injection angle is a critical design choice. At the low power condition, main fuel injection pressure drop is very low, main fuel will not penetrate far away, thus main fuel will burn with pilot fuel combustion. At maximum power condition, main fuel injection pressure drop is very high, the spray will penetrate radially out to meet main air to form direct mixing combustion. Here the **design idea is to make use of the change of penetration to suit low power condition and high-power condition** [3]. That is the reason why the main fuel injection must be with an angle relative to module center line. Main fuel injection pressure drop at maximum condition is very high, hopefully higher than 600 psig. Somewhere between 40% to 60% power condition, there will be a situation the main fuel spray will detach from the pilot fuel combustion to form a separate main fuel air combustion zone. Main fuel penetration and mixing with main air is critical to form non-visible smoke, to have non-luminous flame, to have high efficiency at maximum power condition. Because of the need for high penetration, the main fuel injector is not a hole, but a **section of straight tubing of diameter 0.03 in**. Notice that the present author does not call main fuel injection as co-axial air blast atomization, but rather air co-flowing plain jet injection. In studies on such injection, it was found that under very low liquid injection pressure drop, it is air blast atomization, at medium injection pressure drop, it is air assist atomization, with very high liquid injection pressure drop, it is air retard atomization. Air retard atomization is a new term. It is a case where air does not help atomization of a finer drop size, but hurts atomization by becoming a coarser drop size. Actually, this is good. This is because with very fine droplets, the spray cannot penetrate far out, while for main fuel combustion, at high power condition, penetration is more important than drop size. But it is not the more penetration the better, for fuel injection the present author shall take atomization, penetration, dispersion and fuel air mixing all four aspects into consideration.

Notice that the circumferential distribution of main fuel injectors may be uniform or may be non-uniform. For example, main fuel injector positioning may start other than 12 o'clock position. The different main fuel injector circumferential arrangement is for minor adjustment of exit radial temperature and FAR profile because there is no dilution air.

## **3. Other issues**

#### **3.1 Combustion efficiency**

High FAR combustor has a combustion efficiency issue. Some designer mentioned that for high FAR combustor, at maximum power condition, its efficiency can only be 98%, it is because of chemical dissociation. The present author has studied chemical dissociation. It will have significant effect on efficiency at higher temperature. For aviation kerosene and air combustion, at stoichiometric fuel air ratio, the effect of chemical dissociation will not be so much. Thus, for well-organized high FAR combustion, its combustion efficiency shall be higher than 98%.

## **3.2 Exit distribution**

Notice here the title is only exit distribution, not exit temperature distribution. In reference [6], it was reported that for high FAR combustor exit temperature radial profile is different from exit FAR radial profile, as shown in **Figure 3**.

If **Figure 3** is a true situation in the engine, that is very harmful. This is because the over rich combustion gas entering turbine, meeting with turbine cooling air, will result in additional burning which can totally destroy local turbine cooling. But this was some work done more than 20 years ago. At that time the combustion organization for high FAR combustor was poor. Combustion was rather non-uniform. From present design, the high FAR combustion is well organized, there will not be such severe difference. The temperature defined radial profile and FAR defined radial profile will be of same shape. But the point reported in reference [6] is very important. It shows that to delete some extremely rich pockets in the combustor exit is of very high importance. It also shows in addition to temperature defined exit radial profile, there shall be FAR defined exit radial profile**.**

## **3.3 Visible smoke**

High FAR combustor must avoid visible smoke. This requirement is not only for the maximum condition, it is for all operational conditions. For smoke reduction, fuel additives method cannot be used [7]. To avoid maximum condition visible smoke, design at maximum condition combustion fuel air ratio is stoichiometric, particularly pilot fuel combustion shall not be over rich, avoid any possible local over rich pocket, and the whole combustion FAR shall be uniform. In reference [2], Don Bahr reported the number one issue for high temperature rise combustors is the contradiction between high power condition visible smoke and idle LBO. As mentioned in this chapter, if the idle LBO problem is to be solved, then the design may significantly increase combustion air fraction, such as for combustor FAR 0.051, combustion air is 75%. Then **the combustor cannot have primary air** 

**401**

*New Generation Aero Combustor*

**3.4 High altitude ignition**

**3.5 NO2 issue**

visible exhaust.

three things:

cooling air

**3.6 Cooling**

• Try to reduce UHC

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

efficiency must be appropriately good for pull-up.

equal to 12 times combustion air ACd

Two major design measures for high altitude ignition are:

fuel nozzle injection pressure drop at least 120 psig

ratio, which is about 8%, NO2 is at 80 ppm level

**holes. Also, there is no dilution air holes**. That brings liner configuration greatly changed. Also needs to use other design measures to have exit distribution adjusted.

As combustion air fraction is significantly increased, there is a high altitude ignition issue. For a high FAR combustor, it is required to have 35000 ft reliable ignition. It is more severe than civil aero combustor requirement, which usually has a 30000 ft ignition. Also, it is not only required to have ignition, it must provide engine with quick pull-up. That is after high altitude ignition, the combustion

a. Enlarge the liner cross sectional area. Liner cross sectional area is, **at least**

A high FAR combustor has a special issue, that is exhaust nitrogen dioxide (NO2). This is an environmental issue, NO2 is toxic. When NO2 exhausted to atmosphere it will combine with water vapor to form nitrous acid (HNO2) and nitric acid (HNO3), they are volatile micro matter. But for military combustor, it is related to

NO2 is a brown color gas, at 50 ppm volume concentration, it is visible. It has been seen in previous aero engine operation with afterburner working. Thus, the design requirement is that combustor exhaust raw NO2 concentration lower than 50 ppm (not converted to 15% oxygen concentration). In combustor, chemical reaction mainly generates NO, but under some conditions NO will be converted to NO2. Chemical reaction NO plus HO2 will become NO2 plus OH. That will be the case when high temperature combustion gas meets cold air temperature 1100 degree F. Particularly if in combustor there is some UHC, UHC will accelerate the NO2 formation reaction. Notice that if soot particle combined with NO2 their visible concentration limit will be lower than when each of them counting separately. To control NO2 from a high FAR combustor, the combustor designer needs to do

• Manage to reduce the total NOx level [8]. This is very difficult. At stoichiometric combustion, NOx is at 1000 ppm level. Even with rather low NO2 over NOx

• Avoid direct contact between high temperature combustion gas with cold

Reference [9] is important for liner cooling. The author reported it is not right try to make use of air flow passing through liner wall material absorbing heat to

solve liner cooling issues, which was the way Lamilloy developer used.

b.Using small FN pilot fuel nozzle. That is the reason why at idle condition pilot

**Figure 3.** *Difference between temperature defined and FAR defined radial distribution parameter [6].*

**holes. Also, there is no dilution air holes**. That brings liner configuration greatly changed. Also needs to use other design measures to have exit distribution adjusted.

## **3.4 High altitude ignition**

*Renewable Energy - Technologies and Applications*

Notice here the title is only exit distribution, not exit temperature distribution. In reference [6], it was reported that for high FAR combustor exit temperature radial profile is different from exit FAR radial profile, as shown in **Figure 3**. If **Figure 3** is a true situation in the engine, that is very harmful. This is because the over rich combustion gas entering turbine, meeting with turbine cooling air, will result in additional burning which can totally destroy local turbine cooling. But this was some work done more than 20 years ago. At that time the combustion organization for high FAR combustor was poor. Combustion was rather non-uniform. From present design, the high FAR combustion is well organized, there will not be such severe difference. The temperature defined radial profile and FAR defined radial profile will be of same shape. But the point reported in reference [6] is very important. It shows that to delete some extremely rich pockets in the combustor exit is of very high importance. It also shows in addition to temperature defined exit radial profile, there shall be FAR defined exit

High FAR combustor must avoid visible smoke. This requirement is not only for the maximum condition, it is for all operational conditions. For smoke reduction, fuel additives method cannot be used [7]. To avoid maximum condition visible smoke, design at maximum condition combustion fuel air ratio is stoichiometric, particularly pilot fuel combustion shall not be over rich, avoid any possible local over rich pocket, and the whole combustion FAR shall be uniform. In reference [2], Don Bahr reported the number one issue for high temperature rise combustors is the contradiction between high power condition visible smoke and idle LBO. As mentioned in this chapter, if the idle LBO problem is to be solved, then the design may significantly increase combustion air fraction, such as for combustor FAR 0.051, combustion air is 75%. Then **the combustor cannot have primary air** 

*Difference between temperature defined and FAR defined radial distribution parameter [6].*

**3.2 Exit distribution**

radial profile**.**

**3.3 Visible smoke**

**400**

**Figure 3.**

As combustion air fraction is significantly increased, there is a high altitude ignition issue. For a high FAR combustor, it is required to have 35000 ft reliable ignition. It is more severe than civil aero combustor requirement, which usually has a 30000 ft ignition. Also, it is not only required to have ignition, it must provide engine with quick pull-up. That is after high altitude ignition, the combustion efficiency must be appropriately good for pull-up.

Two major design measures for high altitude ignition are:


## **3.5 NO2 issue**

A high FAR combustor has a special issue, that is exhaust nitrogen dioxide (NO2). This is an environmental issue, NO2 is toxic. When NO2 exhausted to atmosphere it will combine with water vapor to form nitrous acid (HNO2) and nitric acid (HNO3), they are volatile micro matter. But for military combustor, it is related to visible exhaust.

NO2 is a brown color gas, at 50 ppm volume concentration, it is visible. It has been seen in previous aero engine operation with afterburner working. Thus, the design requirement is that combustor exhaust raw NO2 concentration lower than 50 ppm (not converted to 15% oxygen concentration). In combustor, chemical reaction mainly generates NO, but under some conditions NO will be converted to NO2. Chemical reaction NO plus HO2 will become NO2 plus OH. That will be the case when high temperature combustion gas meets cold air temperature 1100 degree F. Particularly if in combustor there is some UHC, UHC will accelerate the NO2 formation reaction. Notice that if soot particle combined with NO2 their visible concentration limit will be lower than when each of them counting separately. To control NO2 from a high FAR combustor, the combustor designer needs to do three things:


## **3.6 Cooling**

Reference [9] is important for liner cooling. The author reported it is not right try to make use of air flow passing through liner wall material absorbing heat to solve liner cooling issues, which was the way Lamilloy developer used.

For high FAR combustor, liner cooling is another very big issue. The present author cooling design is effusion cooling with brand new cooling hole configuration. Experiments have proven they are much more effective than conventional cooling configuration.

#### *3.6.1 Outer liner cooling*

The outer liner cooling configuration is shown in **Figure 4** [3]. The same configuration may also be used for tubular combustor. It is a tangential hole, but **not totally tangential,** it is **a compound angle tangential hole**. As shown in **Figure 5**, the axial direction angle is to prevent the upstream air jets impinging the downstream cooling air jets. 15 degree angle is only an example. The designed axial direction angle shall be based on axial spacing and circumferential spacing. It is Arctan (H/3\*S), as shown in **Figure 5**. From cooling hole center line to the wall inner surface there is a short distance. The minimum distance is half hole diameter. Of course, if the hole is perfectly tangential to the inner wall that is the best. Because it will be the most compact air flow. Depending on liner wall manufacturing, this distance may be more than half hole diameter. For a machined tubular liner, it is half the hole diameter plus 0.005 in. For a large diameter liner formed by sheet metal rolled and welded, this distance may be half hole diameter plus 0.02 in, depending on the liner roundness to avoid laser drilling blind hole.

Such cooling configuration design is based on the present author's long-time cooling study. The most important concept for liner cooling is not how to have cooling air passing liner wall internal passage absorbing more heat, such as Lamilloy (or Transply). That is no good. It is **how to form a compact cooling air layer sticking on wall surface**. The present author's cooling design is based on such concept. The compound angle tangential cooling hole will form such a thin, compact air layer

**403**

**Figure 6.**

**Figure 5.**

*New Generation Aero Combustor*

thus cooling effectiveness is low.

to have smaller hole but more number of holes.

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

sticking on wall surface, to **force the convective heat transfer from hot wall to the** 

in **Figure 6**, by author's own calculation, if liner diameter 25 in, cooling hole diameter 0.02 in, hole center line to inner wall surface is 0.03 in, cooling hole length, as defined by the hole center line length, is 0.8 in. This is good for liner cooing. It shall be stressed that the major advantage of this cooling design is not the long hole length. Instead, it is the cooling effectiveness. For a properly designed and manufactured cooling hole arrangement, very often the cooling effectiveness is 100%. From video an **air layer is spirally flowing around the liner surface**. That is why the cooling effectiveness is very good. The major weakness of Lamilloy is not its air passage inside of liner material is too short, it is the hole exit flow vertical to the wall surface, there will be more mixing of cooling air with the combustion gas,

Of course, the longer cooling hole length is helpful for liner cooling. As shown

For outer liner or tubular liner compound angle tangential cooling hole the discharge coefficient can be 0.86. The discharge coefficient depends on laser drilling. If the laser drilled hole likes something "dog bite", then the discharge coefficient will be lower. If laser drilling technology is available for even smaller holes, it is desirable

*Design of the axial direction angle in compound angle tangential inlet cooling hole configuration [3].*

*Tangential compound angle cooling hole length changed with the distance from hole centerline to liner inner* 

*surface for tubular and outer annular liner, hole diameter 0.02".*

**lower temperature cooling air layer**, **instead of from gas to wall.**

**Figure 4.** *Cooling hole configuration for annular or tubular liner [3].*

### *New Generation Aero Combustor DOI: http://dx.doi.org/10.5772/intechopen.93916*

*Renewable Energy - Technologies and Applications*

configuration.

*3.6.1 Outer liner cooling*

drilling blind hole.

For high FAR combustor, liner cooling is another very big issue. The present author cooling design is effusion cooling with brand new cooling hole configuration. Experiments have proven they are much more effective than conventional cooling

The outer liner cooling configuration is shown in **Figure 4** [3]. The same configuration may also be used for tubular combustor. It is a tangential hole, but **not totally tangential,** it is **a compound angle tangential hole**. As shown in **Figure 5**, the axial direction angle is to prevent the upstream air jets impinging the downstream cooling air jets. 15 degree angle is only an example. The designed axial direction angle shall be based on axial spacing and circumferential spacing. It is Arctan (H/3\*S), as shown in **Figure 5**. From cooling hole center line to the wall inner surface there is a short distance. The minimum distance is half hole diameter. Of course, if the hole is perfectly tangential to the inner wall that is the best. Because it will be the most compact air flow. Depending on liner wall manufacturing, this distance may be more than half hole diameter. For a machined tubular liner, it is half the hole diameter plus 0.005 in. For a large diameter liner formed by sheet metal rolled and welded, this distance may be half hole diameter plus 0.02 in, depending on the liner roundness to avoid laser

Such cooling configuration design is based on the present author's long-time cooling study. The most important concept for liner cooling is not how to have cooling air passing liner wall internal passage absorbing more heat, such as Lamilloy (or Transply). That is no good. It is **how to form a compact cooling air layer sticking on wall surface**. The present author's cooling design is based on such concept. The compound angle tangential cooling hole will form such a thin, compact air layer

**402**

**Figure 4.**

*Cooling hole configuration for annular or tubular liner [3].*

## sticking on wall surface, to **force the convective heat transfer from hot wall to the lower temperature cooling air layer**, **instead of from gas to wall.**

Of course, the longer cooling hole length is helpful for liner cooling. As shown in **Figure 6**, by author's own calculation, if liner diameter 25 in, cooling hole diameter 0.02 in, hole center line to inner wall surface is 0.03 in, cooling hole length, as defined by the hole center line length, is 0.8 in. This is good for liner cooing. It shall be stressed that the major advantage of this cooling design is not the long hole length. Instead, it is the cooling effectiveness. For a properly designed and manufactured cooling hole arrangement, very often the cooling effectiveness is 100%. From video an **air layer is spirally flowing around the liner surface**. That is why the cooling effectiveness is very good. The major weakness of Lamilloy is not its air passage inside of liner material is too short, it is the hole exit flow vertical to the wall surface, there will be more mixing of cooling air with the combustion gas, thus cooling effectiveness is low.

For outer liner or tubular liner compound angle tangential cooling hole the discharge coefficient can be 0.86. The discharge coefficient depends on laser drilling. If the laser drilled hole likes something "dog bite", then the discharge coefficient will be lower. If laser drilling technology is available for even smaller holes, it is desirable to have smaller hole but more number of holes.

#### **Figure 5.**

*Design of the axial direction angle in compound angle tangential inlet cooling hole configuration [3].*

#### **Figure 6.**

*Tangential compound angle cooling hole length changed with the distance from hole centerline to liner inner surface for tubular and outer annular liner, hole diameter 0.02".*

**Figure 7.** *Cooling hole configuration for inner liner [3].*

**405**

**combustion**.

**4.1 LDM vs. LDI**

*New Generation Aero Combustor*

without a life limiting factor.

*3.6.2 Inner liner cooling*

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

combustion gas, which is very bad for cooling result.

to laser drilling. Particularly drilling very small holes.

**4. High pressure low emissions combustor design**

need to have axial direction angle greater than the necessary one.

Inner liner cooling is very different from outer liner cooling. Because if using the same configuration, the cooling air will flow away from the wall surface to mix with

Inner liner cooling configuration design is based on one concept that **two compound angle tangential flowing air jets impinged at wall surface to form a pure axial direction cooling air layer**. The design is shown in **Figure 7** [3]. The impinged two jets must have axial direction angle. As shown in **Figure 8** this axial direction angle must be larger than a certain value to avoid the impinged jets forming reversed flow. The minimum axial direction angle depends on liner diameter. Of course, no

In a conventional combustor there are machined cooling air rings, which has one advantage, which is that the cooling air is flowing in the axial direction. However, the machined ring has a lip, which is life limiting factor. Now the newly designed inner liner cooling configuration has truly axial direction flow cooling air, but

Such inner liner cooling configuration is very good. But it brings some challenges

Such cooling designs are suitable for high FAR combustor, suitable for low emissions combustor, actually suitable for all kind gas turbine combustors.

For a very high pressure civil aero combustor, it cannot use lean pre-vaporized-

More than 20 years ago, someone suggested using lean direct injection (LDI) combustion. The suggestion was very simple, only a sketch. Actually, direct fuel injection was not a new concept. All conventional aero combustors (except vaporizer combustor) have fuel direct injection. There was no explanation from LDI suggestion, how to design a combustor for low emissions. Later on, several fuel air module

premixed (LPP) combustion. Because for an engine of pressure ratio 70, its combustor inlet conditions (inlet temperature and inlet pressure) are so high that the autoignition delay time is extremely short, that will not provide any useful reduction of NOx, but suffer very high risk of auto-ignition. From reference [10], auto-ignition delay time for aviation fuel at high pressure and high inlet temperature were obtained (pressure at 40 atm, temperature at 900 K, not so high as up to pressure ratio 70). The present author derived a calculation model, the pre-ignition chemical reaction and heat release were correlated by fitting the prediction to the experimental data. Then using the model to predict auto-ignition delay time for pressure 70 engine combustor inlet condition. The delay time is 0.31 msec. With a safety factor of 2, the usable premixing time is 0.155 msec. That is really no meaning to design an LPP combustion. Thus, it can only be non-premixing combustion. But for low NOx, at high power condition, fuel and air shall still be well mixed. Then it must be **direct mixing combustion**. Actually, for a high FAR combustor, it is also direct mixing combustion. The difference between these two direct mixing combustions is that, for a low emissions combustor, it is **lean direct mixing (LDM) combustion**, for high FAR combustor, it is **stoichiometric direct mixing** 

## *3.6.2 Inner liner cooling*

*Renewable Energy - Technologies and Applications*

**404**

**Figure 8.**

**Figure 7.**

*Cooling hole configuration for inner liner [3].*

*For inner liner cooling hole, there must be axial direction angle [3].*

Inner liner cooling is very different from outer liner cooling. Because if using the same configuration, the cooling air will flow away from the wall surface to mix with combustion gas, which is very bad for cooling result.

Inner liner cooling configuration design is based on one concept that **two compound angle tangential flowing air jets impinged at wall surface to form a pure axial direction cooling air layer**. The design is shown in **Figure 7** [3]. The impinged two jets must have axial direction angle. As shown in **Figure 8** this axial direction angle must be larger than a certain value to avoid the impinged jets forming reversed flow. The minimum axial direction angle depends on liner diameter. Of course, no need to have axial direction angle greater than the necessary one.

In a conventional combustor there are machined cooling air rings, which has one advantage, which is that the cooling air is flowing in the axial direction. However, the machined ring has a lip, which is life limiting factor. Now the newly designed inner liner cooling configuration has truly axial direction flow cooling air, but without a life limiting factor.

Such inner liner cooling configuration is very good. But it brings some challenges to laser drilling. Particularly drilling very small holes.

Such cooling designs are suitable for high FAR combustor, suitable for low emissions combustor, actually suitable for all kind gas turbine combustors.

## **4. High pressure low emissions combustor design**

For a very high pressure civil aero combustor, it cannot use lean pre-vaporizedpremixed (LPP) combustion. Because for an engine of pressure ratio 70, its combustor inlet conditions (inlet temperature and inlet pressure) are so high that the autoignition delay time is extremely short, that will not provide any useful reduction of NOx, but suffer very high risk of auto-ignition. From reference [10], auto-ignition delay time for aviation fuel at high pressure and high inlet temperature were obtained (pressure at 40 atm, temperature at 900 K, not so high as up to pressure ratio 70). The present author derived a calculation model, the pre-ignition chemical reaction and heat release were correlated by fitting the prediction to the experimental data. Then using the model to predict auto-ignition delay time for pressure 70 engine combustor inlet condition. The delay time is 0.31 msec. With a safety factor of 2, the usable premixing time is 0.155 msec. That is really no meaning to design an LPP combustion. Thus, it can only be non-premixing combustion. But for low NOx, at high power condition, fuel and air shall still be well mixed. Then it must be **direct mixing combustion**. Actually, for a high FAR combustor, it is also direct mixing combustion. The difference between these two direct mixing combustions is that, for a low emissions combustor, it is **lean direct mixing (LDM) combustion**, for high FAR combustor, it is **stoichiometric direct mixing combustion**.

#### **4.1 LDM vs. LDI**

More than 20 years ago, someone suggested using lean direct injection (LDI) combustion. The suggestion was very simple, only a sketch. Actually, direct fuel injection was not a new concept. All conventional aero combustors (except vaporizer combustor) have fuel direct injection. There was no explanation from LDI suggestion, how to design a combustor for low emissions. Later on, several fuel air module

configurations were proposed and tested. Unfortunately, the emissions were no good. Even more trouble is the fact that these fuel air module configurations cannot be integrated on to engine combustor.

Present author proposed lean direct mixing concept. The concept has put stress on one thing that the major design approach shall be concentrated on how to improve high power condition fuel air direct mixing. And the fuel air module proposed by the present author, is based on basic mixing concept, with realistically mechanical design, it can truly be integrated on to engine combustor.

**Conclusion: for high pressure low emissions combustor, it is LDM, not LDI.**

### **4.2 Mixing concept**

For good fuel air mixing, fuel and air shall have close contact. There must be small scale mixing. Thus, the fuel air module shall be of small size. From many years combustion research, combustor design and development, combustor test, the present author has defined **one very good and simple small size fuel air module**. It is one **single axial flow air swirler, and in the center position**, there is a simple pressure swirl fuel **nozzle**. Such combination will offer good efficiency and flame stabilization at low conditions (such as idle condition) with near stoichiometric combustion, while at high power condition, it is very close to premixing situation, if it is lean burn, it offers low emission index (EI) of NOx. There is a fundamental reason. At a high power condition, fuel injection pressure is high, atomization spray drop size is fine, with high air temperature, fuel evaporation is rather quick. Then with appropriate air swirling, fuel air mixing is good**. The flame zone cannot distinguish if it as a pre-vaporized, premixed fuel air mixture in a premixed module, or if it is mixed out of module during the flowing process before reaching the flame zone**. For combustion these two cases do not have a significant difference. That is the reason why at a high power condition, with high pressure, such small size one single axial air swirler plus one simple pressure swirl fuel nozzle will provide very good NOx output. Because of its small size, that means the whole combustor must have large number of modules. In this case, fuel air modules arrangement on dome and their installation on combustor must have good design.

#### **4.3 Direct mixing fuel air module design**

The direct mixing fuel air module for high pressure low emissions combustor is shown in **Figure 9** [11]. The design is very simple. At the inlet there is an axial swirler of low swirling strength, geometrical swirling angle is 35 degree, with thin swirler curved blade of thickness 0.045 in. It is suggested using 0.88 for swirler discharge efficient. In the center there is a simple pressure swirl fuel nozzle. The module has a convergent section of half angle 45 degree at exit. The fuel nozzle exit surface is at the throat section (0.02 in) downstream side. There is a very short divergent section of half angle 75 degree. It is not for aerodynamics, such as a "swirlventuri". It is for a structural purpose, in the module floating design. The module exit has a cross sectional area ACd smaller than the inlet ACd. That makes the exit a metering device.

#### **4.4 Arrangement of fuel air modules on dome**

The arrangement of large number fuel air modules on dome is shown in **Figure 10**. All fuel nozzles are of same size, all air-alone modules are aerodynamically the same and all the same size. Air-alone modules are staying on dome, only

**407**

**Figure 9.**

**Figure 10.**

*Fuel-air module [11].*

*New Generation Aero Combustor*

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

fuel nozzles are installed from air casing. This design idea is from the GE LM 6000 industrial low emissions combustor [12]. In the LM 6000, there are large number of premixed fuel (natural gas) and air modules. As they are premixed modules, the size is big, thus the opening on air casing is rather large. For the present design, the module is not premixed, only fuel nozzle is passing through

In **Figure 10**, altogether there are 80 fuel air modules. Distributed in three rows. From outer liner towards inner liner, they are 32, 32, 16 modules. The whole combustor is having three stages, as shown in **Figure 10**, first stage is idle condition, 16 modules are working. Second stage is from 20% power condition to 50% power condition, 32 modules working. Third stage is from 50% power condition to 100%

air casing, the opening can be much smaller.

*On dome fuel-air module arrangement [11].*

power condition, all modules are working.

*New Generation Aero Combustor DOI: http://dx.doi.org/10.5772/intechopen.93916*

*Renewable Energy - Technologies and Applications*

be integrated on to engine combustor.

**4.2 Mixing concept**

configurations were proposed and tested. Unfortunately, the emissions were no good. Even more trouble is the fact that these fuel air module configurations cannot

Present author proposed lean direct mixing concept. The concept has put stress on one thing that the major design approach shall be concentrated on how to improve high power condition fuel air direct mixing. And the fuel air module proposed by the present author, is based on basic mixing concept, with realistically

**Conclusion: for high pressure low emissions combustor, it is LDM, not LDI.**

For good fuel air mixing, fuel and air shall have close contact. There must be small scale mixing. Thus, the fuel air module shall be of small size. From many years combustion research, combustor design and development, combustor test, the present author has defined **one very good and simple small size fuel air module**. It is one **single axial flow air swirler, and in the center position**, there is a simple pressure swirl fuel **nozzle**. Such combination will offer good efficiency and flame stabilization at low conditions (such as idle condition) with near stoichiometric combustion, while at high power condition, it is very close to premixing situation, if it is lean burn, it offers low emission index (EI) of NOx. There is a fundamental reason. At a high power condition, fuel injection pressure is high, atomization spray drop size is fine, with high air temperature, fuel evaporation is rather quick. Then with appropriate air swirling, fuel air mixing is good**. The flame zone cannot distinguish if it as a pre-vaporized, premixed fuel air mixture in a premixed module, or if it is mixed out of module during the flowing process before reaching the flame zone**. For combustion these two cases do not have a significant difference. That is the reason why at a high power condition, with high pressure, such small size one single axial air swirler plus one simple pressure swirl fuel nozzle will provide very good NOx output. Because of its small size, that means the whole combustor must have large number of modules. In this case, fuel air modules arrangement on

mechanical design, it can truly be integrated on to engine combustor.

dome and their installation on combustor must have good design.

The direct mixing fuel air module for high pressure low emissions combustor is shown in **Figure 9** [11]. The design is very simple. At the inlet there is an axial swirler of low swirling strength, geometrical swirling angle is 35 degree, with thin swirler curved blade of thickness 0.045 in. It is suggested using 0.88 for swirler discharge efficient. In the center there is a simple pressure swirl fuel nozzle. The module has a convergent section of half angle 45 degree at exit. The fuel nozzle exit surface is at the throat section (0.02 in) downstream side. There is a very short divergent section of half angle 75 degree. It is not for aerodynamics, such as a "swirlventuri". It is for a structural purpose, in the module floating design. The module exit has a cross sectional area ACd smaller than the inlet ACd. That makes the exit a

The arrangement of large number fuel air modules on dome is shown in **Figure 10**. All fuel nozzles are of same size, all air-alone modules are aerodynamically the same and all the same size. Air-alone modules are staying on dome, only

**4.3 Direct mixing fuel air module design**

**4.4 Arrangement of fuel air modules on dome**

**406**

metering device.

**Figure 10.** *On dome fuel-air module arrangement [11].*

fuel nozzles are installed from air casing. This design idea is from the GE LM 6000 industrial low emissions combustor [12]. In the LM 6000, there are large number of premixed fuel (natural gas) and air modules. As they are premixed modules, the size is big, thus the opening on air casing is rather large. For the present design, the module is not premixed, only fuel nozzle is passing through air casing, the opening can be much smaller.

In **Figure 10**, altogether there are 80 fuel air modules. Distributed in three rows. From outer liner towards inner liner, they are 32, 32, 16 modules. The whole combustor is having three stages, as shown in **Figure 10**, first stage is idle condition, 16 modules are working. Second stage is from 20% power condition to 50% power condition, 32 modules working. Third stage is from 50% power condition to 100% power condition, all modules are working.

## **4.5 Installation of fuel nozzles on dome**

Fuel nozzles are not installed individually. They are installed in cluster nozzles. There are two types of cluster nozzle. One is three fuel nozzles in one cluster, the other is two fuel nozzles in one cluster. Because the fuel nozzles in one cluster are all in the same stage, so inside the cluster stem there is only one fuel line. That will simplify the cluster nozzle. The cluster of three fuel nozzles is shown in **Figure 11**. From liner axial direction, the cluster is close to one fuel nozzle size. The opening on air casing is not big, as shown in **Figure 12**, it is only an ellipse of one inch times two inches, much smaller than the opening on LM 6000 air casing. It is because of two reasons: first, in this design only the fuel nozzle passes through the air casing. The air-alone module does not pass through the air casing. In the LM 6000, fuel injector and air module together pass through the air casing. Second, in this design in one cluster, nozzles are all in the same stage, that makes cluster simplified and reduces the size. During installation, in one three nozzle cluster, three nozzles shall be installed onto dome to match three air module center holes, that requires very accurate manufacturing and accurate assembly. The same situation for two nozzle cluster installation. This is the reason as shown in **Figure 9**, there is a floating design. It allows the air-alone module moving in either direction 0.03 in. In this design, only the middle row air-alone modules are welded with dome without floating design, other air modules are all with floating design to make the assembly easier.

#### **4.6 Air distribution and liner cross sectional area**

For a high pressure low emissions combustor, its air flow distribution is combustion air 75% and cooling air 25%. The liner layout has no primary air holes, no dilution air holes. Liner cross sectional area is designed by 12 times combustion air ACd, or it can also be designed as liner average Mach number 0.02. The Mach number is defined by that, air flow rate is combustion air, sonic velocity is defined by inlet air temperature, air density is defined by inlet air pressure, inlet air temperature.

Notice the design choices will always need several times modification, make good balance between the following items:


The key item is the total number of fuel air modules. That will affect the ACd for each air module and module size, also affect fuel nozzle flow number and whole fuel air module arrangement on dome.

#### **4.7 Fuel nozzle design**

Fuel nozzle is designed for the maximum condition. At the 100% condition, the nozzle injection pressure drop is between 400 psig and 800 psig. At the idle

**409**

**Figure 12.**

**Figure 11.**

*Cluster of 3 nozzles [11].*

*New Generation Aero Combustor*

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

pump with very high pressure capacity.

*Opening on air casing for cluster fuel nozzles [11].*

**4.8 90-degree sector combustor design**

The control of fuel staging is simple on-off valve.

shown in **Figure 14**, which was designed by the present author.

condition, fuel nozzle pressure drop is 120 psig. At all operational conditions, such as before one new stage is opened, nozzle pressure drop shall not be higher than 800 psig and just after a new stage is opened, nozzle pressure drop is not less than 100 psig. Since it is for a high pressure low emissions combustor, there needs to be a fuel

90 degree sector combustor design is shown in **Figure 13**, which is a rectangular shape, not a fan shape. Previously a 90 degree sector was usually cut from a full annular combustor, the cost was a whole full annular combustor. And the traversing gear to measure exit temperature distribution is complicated. From present author's experience, using a rectangular 90 degree sector will not affect the combustor development, its aerodynamics will not be affected. Two side walls are water cooled with no effect on air distribution. The combustion data will be taken from the middle 60 degree sector. The rectangular 90 degree sector design idea is taken from reference [13]. In reference [13], the recommended 90 degree rectangular sector is

*New Generation Aero Combustor DOI: http://dx.doi.org/10.5772/intechopen.93916*

**Figure 11.** *Cluster of 3 nozzles [11].*

*Renewable Energy - Technologies and Applications*

**4.5 Installation of fuel nozzles on dome**

**4.6 Air distribution and liner cross sectional area**

good balance between the following items:

• Liner annular height (affect module radial spacing)

the locations of modules with floating design)

spacing between modules)

fuel air module arrangement on dome.

diameter)

**4.7 Fuel nozzle design**

Fuel nozzles are not installed individually. They are installed in cluster nozzles. There are two types of cluster nozzle. One is three fuel nozzles in one cluster, the other is two fuel nozzles in one cluster. Because the fuel nozzles in one cluster are all in the same stage, so inside the cluster stem there is only one fuel line. That will simplify the cluster nozzle. The cluster of three fuel nozzles is shown in **Figure 11**. From liner axial direction, the cluster is close to one fuel nozzle size. The opening on air casing is not big, as shown in **Figure 12**, it is only an ellipse of one inch times two inches, much smaller than the opening on LM 6000 air casing. It is because of two reasons: first, in this design only the fuel nozzle passes through the air casing. The air-alone module does not pass through the air casing. In the LM 6000, fuel injector and air module together pass through the air casing. Second, in this design in one cluster, nozzles are all in the same stage, that makes cluster simplified and reduces the size. During installation, in one three nozzle cluster, three nozzles shall be installed onto dome to match three air module center holes, that requires very accurate manufacturing and accurate assembly. The same situation for two nozzle cluster installation. This is the reason as shown in **Figure 9**, there is a floating design. It allows the air-alone module moving in either direction 0.03 in. In this design, only the middle row air-alone modules are welded with dome without floating design, other air modules are all with floating design to make the assembly

For a high pressure low emissions combustor, its air flow distribution is combustion air 75% and cooling air 25%. The liner layout has no primary air holes, no dilution air holes. Liner cross sectional area is designed by 12 times combustion air ACd, or it can also be designed as liner average Mach number 0.02. The Mach number is defined by that, air flow rate is combustion air, sonic velocity is defined by inlet air temperature, air density is defined by inlet air pressure, inlet air temperature. Notice the design choices will always need several times modification, make

• Liner average diameter (affect total number of modules and the circumferential

• Module detailed design (affect module inlet diameter and module exit

• For module installation, the required minimum floating distance (may affect

The key item is the total number of fuel air modules. That will affect the ACd for each air module and module size, also affect fuel nozzle flow number and whole

Fuel nozzle is designed for the maximum condition. At the 100% condition, the nozzle injection pressure drop is between 400 psig and 800 psig. At the idle

**408**

easier.

#### **Figure 12.**

condition, fuel nozzle pressure drop is 120 psig. At all operational conditions, such as before one new stage is opened, nozzle pressure drop shall not be higher than 800 psig and just after a new stage is opened, nozzle pressure drop is not less than 100 psig.

Since it is for a high pressure low emissions combustor, there needs to be a fuel pump with very high pressure capacity.

The control of fuel staging is simple on-off valve.

#### **4.8 90-degree sector combustor design**

90 degree sector combustor design is shown in **Figure 13**, which is a rectangular shape, not a fan shape. Previously a 90 degree sector was usually cut from a full annular combustor, the cost was a whole full annular combustor. And the traversing gear to measure exit temperature distribution is complicated. From present author's experience, using a rectangular 90 degree sector will not affect the combustor development, its aerodynamics will not be affected. Two side walls are water cooled with no effect on air distribution. The combustion data will be taken from the middle 60 degree sector. The rectangular 90 degree sector design idea is taken from reference [13]. In reference [13], the recommended 90 degree rectangular sector is shown in **Figure 14**, which was designed by the present author.

**Figure 13.** *Sector combustor of 20 fuel-air modules.*

**Figure 14.** *Sector test combustor (shown with 3 fuel injectors) [13].*

## **5. Combustor performances**

This high pressure low emissions combustor design has good combustion performances. First, the high power condition EI NOx is good, which is very close to a well-developed LPP system. The high pressure EI NOx can be easily obtained by single module tubular combustor test.

High altitude ignition is good, because as shown in **Figure 10**, the fuel nozzle spray for ignition is rather close to ignitor and there is no other air in-between spray and ignitor.

Flame stabilization is good. Idle LBO is good for two reasons:


For the 30% power condition, as the designed working modules combustion equivalence ratio is close to one, which is good flame stabilization for the storm weather heavy rain test.

As it is non-premixed, lean direct mixing combustion with low swirling, there will not be severe combustion instability.

For exit temperature distribution, the pattern factor is low. Because there is small scale mixing, it is close to uniform heat release combustion.

For the exit radial profile, this design has its natural feature for good radial profile. If there needs some minor adjustment, the designer may easily move the two fuel nozzle cluster and related air modules radially just a little bit.

**411**

*New Generation Aero Combustor*

**6. Summary of this chapter**

development.

to metal parts

an equation of

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

One additional advantage for this combustor design is that, for high pressure low emissions combustor development, very often there is a lack of such a high pressure and high air flow rate test facility to run up to the 100% power condition. When there are such facilities, the running cost is very high. For this combustor design, only 1.25% of 100% power condition air flow is required for single module tubular combustor test. That is, the designer can run a large number of tests to verify the effect of pressure, air temperature, FAR on EI NOx to correlate

That gives the designer opportunity to study the combustion in depth.

• The new generation civil aero combustor is a high pressure (such as 70 atm) low emissions combustor. The new generation military aero combustor is a high FAR (such as 0.051) combustor. For combustion organization, they are both direct mixing combustion. For the civil combustor, it is a lean direct mixing combustion concept. For the military combustor, it is a stoichiometric direct mixing combustion concept. They both require a high combustion air fraction, such as 75%. The liner will have no primary holes, no dilution holes. Cooling air is reduced to 25%. There must be advanced cooling technology. The liner design for the new generation aero combustor has been reported in this chapter. New generation aero combustor also needs some more technology

• As 75% air coming into liner through dome, there needs to be a new inlet diffuser design. The new diffuser design for the new generation aero combustor will be

• The new generation aero combustor needs a new liner material, which is ceramic matrix composites (CMC). Such technology is available. For further development, two problems need to be solved. One is how to drill tiny small cooling holes on CMC. The other is how to connect CMC with metal parts. For the second problem, there needs a transition region, from metal gradually change to CMC, then CMC part can easily weld or connect

• The new generation aero combustor will require to be fabricated with additive manufacturing (or 3-D printing manufacturing). Such technology is available. It needs further development to be used for liner dome parts, in addition to

• New generation aero combustor shall have laser ignition technology. This technology is not available now. It will be particularly useful for high altitude

reported somewhere else by the present author

fuel nozzles, currently made by such technology

ignition. Such technology shall be developed in the future.

EI NOx f P, T, FAR) = ( (1)

*Renewable Energy - Technologies and Applications*

**5. Combustor performances**

*Sector combustor of 20 fuel-air modules.*

LBO a very good one.

will not be severe combustion instability.

weather heavy rain test.

and ignitor.

**Figure 13.**

**Figure 14.**

single module tubular combustor test.

*Sector test combustor (shown with 3 fuel injectors) [13].*

This high pressure low emissions combustor design has good combustion performances. First, the high power condition EI NOx is good, which is very close to a well-developed LPP system. The high pressure EI NOx can be easily obtained by

High altitude ignition is good, because as shown in **Figure 10**, the fuel nozzle spray for ignition is rather close to ignitor and there is no other air in-between spray

Flame stabilization is good. Idle LBO is good for two reasons:

• The combustion equivalence ratio for working fuel air module is 1.2

• As shown in **Figure 10**, at idle condition there are 8 modules working as a group in one combustion zone. There is not much non-working module air quenching effect. Particularly there are two working module flames which are protected by the surrounding flames. They support each other, make the idle

For the 30% power condition, as the designed working modules combustion equivalence ratio is close to one, which is good flame stabilization for the storm

As it is non-premixed, lean direct mixing combustion with low swirling, there

For exit temperature distribution, the pattern factor is low. Because there is

For the exit radial profile, this design has its natural feature for good radial profile. If there needs some minor adjustment, the designer may easily move the

small scale mixing, it is close to uniform heat release combustion.

two fuel nozzle cluster and related air modules radially just a little bit.

**410**

One additional advantage for this combustor design is that, for high pressure low emissions combustor development, very often there is a lack of such a high pressure and high air flow rate test facility to run up to the 100% power condition. When there are such facilities, the running cost is very high. For this combustor design, only 1.25% of 100% power condition air flow is required for single module tubular combustor test. That is, the designer can run a large number of tests to verify the effect of pressure, air temperature, FAR on EI NOx to correlate an equation of

$$\text{EI NOx = f (P, T, FAR)}\tag{1}$$

That gives the designer opportunity to study the combustion in depth.

## **6. Summary of this chapter**


*Renewable Energy - Technologies and Applications*

## **Author details**

Jushan Chin1 \* and Jin Dang2

1 Retired, AIAA Associate Fellow, California, USA

2 Fossil Energy Research Corp., California, USA

\*Address all correspondence to: jschin2016@gmail.com

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**413**

*New Generation Aero Combustor*

[1] Secretariat IC. Annex 16— Environmental Protection Volume II—Aircraft Engine Emissions. ISBN 978-92-9231-123-02008; 2008.

[3] Chin J. Suggestions on High

[4] KRESS E, Taylor J, Dodds W. Multiple Swirler Dome Combustor for High Temperature Rise Applications. In 26th Joint Propulsion Conference 1990

[5] Johnson MR, Littlejohn D, Nazeer WA, Smith KO, Cheng RK. A Comparison of the Flowfields and Emissions of High-swirl Injectors and Low-swirl Injectors for Lean Premixed Gas Turbines. Proceedings of the Combustion Institute. 2005 Jan

[6] Van Erp CA, Richman MH. Technical

Development of Advanced Combustion Systems. In RTO Meeting Proceedings

[7] Liscinsky D, Colket M, Hautman D, True B. Effect of Fuel Additives on Particle Formation in Gas Turbine Combustors. In 37th Joint Propulsion Conference and Exhibit 2001 (p. 3745).

[8] Sturgess, G, Zelina, J, Shouse, D, Roquemore, W. Emissions Reduction Technologies for Military Gas Turbine Engines. Journal of Propulsion and

[9] Andrews GE, Asere AA, Hussain CI, Mkpadi MC, Nazari A. Impingement/ Effusion cooling: Overall Wall Heat

Power 2005; 21(2):193-217.

Challenges Associated with the

**References**

Mar;3(2):179-86.

2019 (p. 4327).

(p. 2159).

1;30(2):2867-74.

1999.

*DOI: http://dx.doi.org/10.5772/intechopen.93916*

Transfer. In Turbo Expo: Power for Land, Sea, and Air 1988 Jun 6 (Vol. 79214, p. V004T09A036). American Society of Mechanical Engineers.

[10] Guin C. Characterization of

[12] Leonard, G, Stegmaier, J. Development of an Aeroderivative Gas Turbine Dry Low Emissions Combustion System. Journal of

1994; 116(3):542-546.

Proceedings 1999.

2018 (p. 4921).

Autoignition and Flashback in Premixed Injection Systems. In RTO Meeting

[11] Chin J. Design of Aero Engine Lean Direct Mixing Combustor. In AIAA Propulsion and Energy 2018 Forum

Engineering for Gas Turbines and Power

[13] NASA Glenn Research Center. Technology Readiness Levels. CAEP/6-IP/4 Appendix A.

[2] Bahr DW. Technology for the Design of High Temperature Rise Combustors. Journal of Propulsion and Power. 1987

Temperature Rise Combustor. In AIAA Propulsion and Energy 2019 Forum

## **References**

*Renewable Energy - Technologies and Applications*

**412**

**Author details**

\* and Jin Dang2

provided the original work is properly cited.

1 Retired, AIAA Associate Fellow, California, USA

2 Fossil Energy Research Corp., California, USA

\*Address all correspondence to: jschin2016@gmail.com

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Jushan Chin1

[1] Secretariat IC. Annex 16— Environmental Protection Volume II—Aircraft Engine Emissions. ISBN 978-92-9231-123-02008; 2008.

[2] Bahr DW. Technology for the Design of High Temperature Rise Combustors. Journal of Propulsion and Power. 1987 Mar;3(2):179-86.

[3] Chin J. Suggestions on High Temperature Rise Combustor. In AIAA Propulsion and Energy 2019 Forum 2019 (p. 4327).

[4] KRESS E, Taylor J, Dodds W. Multiple Swirler Dome Combustor for High Temperature Rise Applications. In 26th Joint Propulsion Conference 1990 (p. 2159).

[5] Johnson MR, Littlejohn D, Nazeer WA, Smith KO, Cheng RK. A Comparison of the Flowfields and Emissions of High-swirl Injectors and Low-swirl Injectors for Lean Premixed Gas Turbines. Proceedings of the Combustion Institute. 2005 Jan 1;30(2):2867-74.

[6] Van Erp CA, Richman MH. Technical Challenges Associated with the Development of Advanced Combustion Systems. In RTO Meeting Proceedings 1999.

[7] Liscinsky D, Colket M, Hautman D, True B. Effect of Fuel Additives on Particle Formation in Gas Turbine Combustors. In 37th Joint Propulsion Conference and Exhibit 2001 (p. 3745).

[8] Sturgess, G, Zelina, J, Shouse, D, Roquemore, W. Emissions Reduction Technologies for Military Gas Turbine Engines. Journal of Propulsion and Power 2005; 21(2):193-217.

[9] Andrews GE, Asere AA, Hussain CI, Mkpadi MC, Nazari A. Impingement/ Effusion cooling: Overall Wall Heat

Transfer. In Turbo Expo: Power for Land, Sea, and Air 1988 Jun 6 (Vol. 79214, p. V004T09A036). American Society of Mechanical Engineers.

[10] Guin C. Characterization of Autoignition and Flashback in Premixed Injection Systems. In RTO Meeting Proceedings 1999.

[11] Chin J. Design of Aero Engine Lean Direct Mixing Combustor. In AIAA Propulsion and Energy 2018 Forum 2018 (p. 4921).

[12] Leonard, G, Stegmaier, J. Development of an Aeroderivative Gas Turbine Dry Low Emissions Combustion System. Journal of Engineering for Gas Turbines and Power 1994; 116(3):542-546.

[13] NASA Glenn Research Center. Technology Readiness Levels. CAEP/6-IP/4 Appendix A.

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Renewable Energy - Technologies and Applications

Renewable Energy

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