**3. Proposed microgrid structure**

The main components of the renewable energy resource (RER) microgrid examined here are solar photovoltaics (PV), micro-wind turbines (MT), and a battery energy storage system (BESS). These are utilized for electricity generation and energy storage, and they supply energy to a load that is normally satisfied with grid power alone. The microgrid is studied for two types of operating conditions. First is an isolated RER which provides all of the load power. The second system is an RER with a diesel generator backup in which the generator is activated if the RER cannot supply the full load.

**3.3. RER and battery modeling**

**Figure 7.** RER and diesel generator model.

*Ps*

*3.3.2. Micro-wind turbine model*

constant air density of 1.225 kg

*3.3.3. Battery energy storage model*

level of the battery is *<sup>P</sup> <sup>B</sup>*

capacity, *<sup>B</sup> cap*(kWh).

where *ρ*: Air density (kg

speed (m/s), and *Pw*

*Pw*

/m<sup>3</sup> ), *Aw*

Columbus, Ohio [10]. The number of micro-turbines is *Nw*

duced by a PV panel, the following equation is used [8].

: Energy conversion efficiency (%), *As*

for Columbus, Ohio [10]. The number of solar PV panels is *Ns*

/m<sup>3</sup>

(*t*): Power generated by solar PV (W).

The power generated by a photovoltaic panel depends on two fundamental parameters: the solar irradiation and the ambient temperature. In order to simplify the model, the power pro-

The solar irradiation, sampled hourly, is found from typical meteorological year (TMY) data,

The electrical power generated by a micro-wind turbine depends on the wind speed, air density, area swept by the turbine blades, and an efficiency factor called the Betz coefficient [9]. A

(*t*) = 0.5*ρ Aw Cp Vw*

: Micro-turbine swept area (m<sup>2</sup>

The wind speed, sampled hourly, is found from typical meteorological year (TMY) data, for

Whenever the RER output exceeds the load demand, the extra power is stored in a battery. This power is then used whenever the RER is unable to supply the load demand. The charge

(t): Power generated by micro-turbine (W)

: PV panel area (m<sup>2</sup>

(*t*) = *η<sup>s</sup> As G*(*t*) (1)

Renewable Energy Microgrid Design for Shared Loads http://dx.doi.org/10.5772/intechopen.75980

.

is used, and the Betz coefficient is taken to be 59%.

.

(*t*), which is restricted to be in the range of 20–80% of the battery

), *Cp*

), *G*(*t*): Solar irradiation (*W/m*<sup>2</sup>

3(*t*) (2)

: Betz coefficient, *Vw*

),

7

(t): Wind

*3.3.1. Photovoltaic model*

where *η<sup>s</sup>*

and *Ps*

For each system, the hourly power flow to or from each element of the microgrid is simulated. The capacity of each RER component is chosen to minimize the overall cost.

#### **3.1. Isolated RER**

The first type of microgrid is the isolated RER, which is shown in **Figure 6**. The RER operates independently from the local utility grid to provide all of the electricity to residential and commercial building. This system requires large battery storage to use during low wind and solar output times. The RER for the isolated mode must be large enough to produce energy to cover 100% of the building's energy needs.

#### **3.2. RER and diesel generator**

**Figure 7** illustrates the second configuration and RER with a diesel generator backup. The diesel generator has the option of charging the battery, which is significantly different from the other scenarios.

**Figure 6.** Isolated grid model.

Renewable Energy Microgrid Design for Shared Loads http://dx.doi.org/10.5772/intechopen.75980 7

**Figure 7.** RER and diesel generator model.

#### **3.3. RER and battery modeling**

#### *3.3.1. Photovoltaic model*

shows the effect of combining the residential load with the commercial load, where the weatherdependent load is included with the commercial load. The load factor behavior varies more in this case. The LF for the combined load is still between the LF for the residential and commer-

The main components of the renewable energy resource (RER) microgrid examined here are solar photovoltaics (PV), micro-wind turbines (MT), and a battery energy storage system (BESS). These are utilized for electricity generation and energy storage, and they supply energy to a load that is normally satisfied with grid power alone. The microgrid is studied for two types of operating conditions. First is an isolated RER which provides all of the load power. The second system is an RER with a diesel generator backup in which the generator is

For each system, the hourly power flow to or from each element of the microgrid is simulated.

The first type of microgrid is the isolated RER, which is shown in **Figure 6**. The RER operates independently from the local utility grid to provide all of the electricity to residential and commercial building. This system requires large battery storage to use during low wind and solar output times. The RER for the isolated mode must be large enough to produce energy to

**Figure 7** illustrates the second configuration and RER with a diesel generator backup. The diesel generator has the option of charging the battery, which is significantly different from

The capacity of each RER component is chosen to minimize the overall cost.

cial loads, except for January, March, and April.

activated if the RER cannot supply the full load.

cover 100% of the building's energy needs.

**3.2. RER and diesel generator**

the other scenarios.

**Figure 6.** Isolated grid model.

**3.1. Isolated RER**

6 Smart Microgrids

**3. Proposed microgrid structure**

The power generated by a photovoltaic panel depends on two fundamental parameters: the solar irradiation and the ambient temperature. In order to simplify the model, the power produced by a PV panel, the following equation is used [8].

$$P\_s(t) = \eta\_s A\_s \mathbf{G}(t) \tag{1}$$

where *η<sup>s</sup>* : Energy conversion efficiency (%), *As* : PV panel area (m<sup>2</sup> ), *G*(*t*): Solar irradiation (*W/m*<sup>2</sup> ), and *Ps* (*t*): Power generated by solar PV (W).

The solar irradiation, sampled hourly, is found from typical meteorological year (TMY) data, for Columbus, Ohio [10]. The number of solar PV panels is *Ns* .

#### *3.3.2. Micro-wind turbine model*

The electrical power generated by a micro-wind turbine depends on the wind speed, air density, area swept by the turbine blades, and an efficiency factor called the Betz coefficient [9]. A constant air density of 1.225 kg /m<sup>3</sup> is used, and the Betz coefficient is taken to be 59%.

$$P\_w(t) = 0.5\rho \, A\_w \, \mathbb{C}\_p V\_w^3(t) \tag{2}$$

where *ρ*: Air density (kg /m<sup>3</sup> ), *Aw* : Micro-turbine swept area (m<sup>2</sup> ), *Cp* : Betz coefficient, *Vw* (t): Wind speed (m/s), and *Pw* (t): Power generated by micro-turbine (W)

The wind speed, sampled hourly, is found from typical meteorological year (TMY) data, for Columbus, Ohio [10]. The number of micro-turbines is *Nw* .

#### *3.3.3. Battery energy storage model*

Whenever the RER output exceeds the load demand, the extra power is stored in a battery. This power is then used whenever the RER is unable to supply the load demand. The charge level of the battery is *<sup>P</sup> <sup>B</sup>* (*t*), which is restricted to be in the range of 20–80% of the battery capacity, *<sup>B</sup> cap*(kWh).

$$0.2\ B\_{\alpha p} \le P\_{\mathfrak{g}}(t) \le 0.8\ B\_{\alpha p} \tag{3}$$

• If the RER output is greater than the load, then the load is completely satisfied by the RER, and no battery power is used for the load. As much charging power as possible is transmitted to the battery, if its charge level is less than the upper threshold. Any remaining power

• There is a possibility of power outage if the combined RER and battery outputs cannot

At each hour of the simulation for the RER with distributed generation (DG) system illustrated in **Figure 7**, the RER power *P*(*t*) is determined using the TMY data. In addition, the

information, the graph in **Figure 9** is used to determine all other quantities and to determine when the DG is turned on/off. The graph illustrates the process of updating these quantities

(*t* − 1) are known. From this

Renewable Energy Microgrid Design for Shared Loads http://dx.doi.org/10.5772/intechopen.75980 9

meet the load. Increasing the size of the system reduces this possibility.

(*t*) and the charge level of the battery at the previous hour *PB*

each hour. The following characteristics are implemented in this graph.

from the RER is sent back to local grid.

**4.2. Diesel generator RER dispatch algorithm**

**Figure 8.** Isolated RER dispatch algorithm.

load *PL*

When charging or discharging the battery, the maximum amount of energy that can be removed during a 1-hour interval is *BHR*. This limit is expressed by the following inequality.

$$\left|P\_{\mathfrak{g}}(t) - P\_{\mathfrak{g}}(t-1)\right| \le B\_{\text{HR}}\tag{4}$$

Both the battery capacity and the hourly charge/discharge limit are parameters for the microgrid.

For every hour in the simulation of the microgrid, there is a decision made to charge or discharge the battery. This decision is determined in part by the charge level of the battery. If the current charge level is in the range of 20–80% of *BCAP*, then the battery can be charged or discharged. If the current charge level is less than 20% of *BCAP*, the battery can only be charged. If the current charge level is more than 80% of *BCAP*, the battery can only be discharged.

#### **3.4. Diesel generator model**

The diesel generator supports the microgrid by supplying power PDL(t) directly to the load and power PDB(t) to the battery. The sum of these two must be less than the maximum power output <sup>D</sup>max from the generator, such that.

$$0 \le P\_{\rm Dg}(t) + P\_{\rm Dt}(t) \le D\_{\rm max} \tag{5}$$

The conditions for activating the generator at each hour are determined by the current load and RER output, the state of the battery's charge, and whether or not the generator was running the previous hour. If the RER and battery cannot meet the load, the generator is activated. If the generator was running the previous hour and the battery can take more charge, then the generator is allowed to run during the current hour.

#### **4. Dynamic microgrid modeling**

#### **4.1. Isolated RER dispatch algorithm**

At each hour of the simulation for the grid-isolated system illustrated in **Figure 6**, the RER power *P*(*t*) is determined using the TMY data. In addition, the load *PL* (*t*) and the charge level of the battery at the previous hour *PB* (*t* − 1) are known. From this information, the graph in **Figure 8** is used to determine all other quantities. The graph illustrates the process of updating these quantities each hour. The following characteristics are implemented in this graph.

• If the RER output is less than the load at a given hour, then all of the available RER output is sent to the load (i.e., no battery charging at this hour), and the battery satisfies the remainder of the load.


#### **4.2. Diesel generator RER dispatch algorithm**

0.2 *Bcap* ≤ *PB*


**3.4. Diesel generator model**

<sup>D</sup>max from the generator, such that.

**4. Dynamic microgrid modeling**

**4.1. Isolated RER dispatch algorithm**

the battery at the previous hour *PB*

mainder of the load.

then the generator is allowed to run during the current hour.

power *P*(*t*) is determined using the TMY data. In addition, the load *PL*

microgrid.

8 Smart Microgrids

(*t*) ≤ 0.8 *Bcap* (3)


(*t*) and the charge level of

When charging or discharging the battery, the maximum amount of energy that can be removed during a 1-hour interval is *BHR*. This limit is expressed by the following inequality.

(*t* − 1)

Both the battery capacity and the hourly charge/discharge limit are parameters for the

For every hour in the simulation of the microgrid, there is a decision made to charge or discharge the battery. This decision is determined in part by the charge level of the battery. If the current charge level is in the range of 20–80% of *BCAP*, then the battery can be charged or discharged. If the current charge level is less than 20% of *BCAP*, the battery can only be charged.

The diesel generator supports the microgrid by supplying power PDL(t) directly to the load and power PDB(t) to the battery. The sum of these two must be less than the maximum power output

0 ≤ *PDB*(*t*) + *PDL*(*t*) ≤ *Dmax* (5)

The conditions for activating the generator at each hour are determined by the current load and RER output, the state of the battery's charge, and whether or not the generator was running the previous hour. If the RER and battery cannot meet the load, the generator is activated. If the generator was running the previous hour and the battery can take more charge,

At each hour of the simulation for the grid-isolated system illustrated in **Figure 6**, the RER

is used to determine all other quantities. The graph illustrates the process of updating these

• If the RER output is less than the load at a given hour, then all of the available RER output is sent to the load (i.e., no battery charging at this hour), and the battery satisfies the re-

quantities each hour. The following characteristics are implemented in this graph.

(*t* − 1) are known. From this information, the graph in **Figure 8**

If the current charge level is more than 80% of *BCAP*, the battery can only be discharged.

(*t*) − *PB*

At each hour of the simulation for the RER with distributed generation (DG) system illustrated in **Figure 7**, the RER power *P*(*t*) is determined using the TMY data. In addition, the load *PL* (*t*) and the charge level of the battery at the previous hour *PB* (*t* − 1) are known. From this information, the graph in **Figure 9** is used to determine all other quantities and to determine when the DG is turned on/off. The graph illustrates the process of updating these quantities each hour. The following characteristics are implemented in this graph.

**Figure 8.** Isolated RER dispatch algorithm.

where *ACC* <sup>=</sup> capital cost, *ARC* <sup>=</sup> replacement costs, *AFC* <sup>=</sup> fuel cost, and *AOC* <sup>=</sup> operating costs.

The capital cost is found from the initial costs for the PV array, MT units, BESS, and DG. The PV capital cost is \$1.8 per peak watt of PV power. It is assumed that each solar panel in the array

cost, including installation, of \$22,000 (about \$2 per peak watt of wind power) [11, 12]. There are *NW* of these units installed. Each kWh of BESS capacity has a cost of \$300 [11, 12], and the DG cost is approximated by a linear function of the capacity *Dmax*, from \$7000 for a 5 kW capacity to \$14,000 for a 40 kW capacity, based on advertised prices [12]. The DG cost formula is therefore

*CCAP* = *\$*720 · *Ns* + *\$*22,000 · *NW* + *\$*300 · *BCap* + *CDG* (8)

Standard amortization is applied to this capital cost, using an interest rate of *i* = 6%and a proj-

*ACC* = *CRF* · *CCAP* (10)

The PV and MT components last the full lifetime of the system, but the BESS and DG have shorter lifetimes and therefore need periodic replacement. Replacement costs are found with a sinking fund factor, which computes the amount of money that needs to be annually set aside to pay for periodic replacement of the BESS and DG. The formula for the sinking fund factor is.

in the capital recovery factor. The BESS lifetime is 7 years, and the DG lifetime is 15 years. The

*ARC* = *\$*300 · *BCap* · *SFF*(7) + *CDG* · *SFF*(15) (12)

\_\_\_\_\_\_\_\_\_\_ *\$*7000

panels in the entire array. Each MT unit has an up-front

<sup>35</sup> kW) <sup>+</sup> *\$*<sup>7000</sup> (7)

Renewable Energy Microgrid Design for Shared Loads http://dx.doi.org/10.5772/intechopen.75980

(<sup>1</sup> <sup>+</sup> *<sup>i</sup>*)*<sup>N</sup>* <sup>−</sup> <sup>1</sup> (9)

(<sup>1</sup> <sup>+</sup> *<sup>i</sup>*)*NL* <sup>−</sup> <sup>1</sup> (11)

and the interest rate *i* is the same as that used

. This leads to a

11

with a 20% efficiency, and that the peak radiation intensity is 1000 W/m<sup>2</sup>

Each of these categories is described in the following subsections.

**5.1. Annual capital cost**

per-panel capital cost of \$720, with *Ns*

*CDG* = (*Dmax* − 5 kW)(

ect lifetime of *N* = 20 years. The amortization factor is.

*CRF* <sup>=</sup> *<sup>i</sup>* (<sup>1</sup> <sup>+</sup> *<sup>i</sup>*)*<sup>N</sup>* \_\_\_\_\_\_\_

*SFF*(*NL*) <sup>=</sup> \_\_\_\_\_\_\_ *<sup>i</sup>*

The lifetime of the component in question is *NL*

annual replacement cost is therefore given by.

**5.2. Annual replacement cost**

This factor is applied to the capital cost to find the annual capital cost as.

The total up-front capital cost is then the sum of all four terms.

is 2 m<sup>2</sup>

**Figure 9.** Diesel generator RER dispatch algorithm.

