**A Comparison of Electricity Generation Reference Costs for Different Technologies of Renewable Energy Sources**

Alenka Kavkler1, Sebastijan Repina2 and Mejra Festić<sup>3</sup> *1Faculty of Business and Economics, University of Maribor and EIPF Economic Institute Ljubljana 2EIPF Economic Institute, Ljubljana 3Faculty of Business and Economics, University of Maribor and EIPF Economic Institute Ljubljana Slovenia* 

#### **1. Introduction**

308 Energy Efficiency – A Bridge to Low Carbon Economy

Said,S., ElAmin,I. and AlShehri,A. (2205). *Renewable energy potentials in Saudi Arabia*. Report.

Saudi Arabia Standards Organization. (2005). *Energy Labelling and Minimum Energy Performance Requirements for Air-Conditioners*, Standard No. 3459, Saudi Arabia. Saudi Arabia Standards Organization. (2006). *Energy Labelling Requirements of Household Electrical Clothes Washing Machines.* Standard No. 3569, Saudi Arabia. Saudi Arabia Standards Organization.(2007). *Energy Performance Capacity and Labelling of* 

Saudi Arabian Standards Organization. (2005). *Energy Labelling and Minimum Energy Performance Requirements for Air*‐*Conditioners.* Standard 3459, Saudi Arabia.

Saudi Electricity Company. (2009). Annual Report, Riyadh. Saudi Electricity Company.(2010). Annual Report, Riyadh.

World Bank. (2007). *World Development Indicators*, Report, Washington, D.C.

*Household Refrigerators, Refrigerator*-*Freezers, and Freezers*, Standard No. 3620, Saudi

Saudi Arabia.

Arabia.

The target value for electricity production from renewable resources in Slovenia till 2020 has amounted to additional 3.146 GWh. The highest share of this additional electricity will be obtained in majority from hydro power plants: additional 1.299 GWh will be obtained from big hydro power plants (that requires 618,3 mio € for investment); wind power plants with additional 567 GWh (that requires 345,6 mio € investment); photovoltaic with 469 GWh (which requires 1.641,5 mio € additional investment); biomass with additional 267 GWh (that requires 11,3 mio € of investment); small hydro power plants with additional 194 GWh and the needed investment amount of 148,8 mio €; natural gas with additional 191 GWh (that requires the investment amount of 95,5 mio €); and geothermal power plants with 150 GWh (that required investment amount of 93,8 mio € investicij). (Kavkler, Festić, Repina 2009).

Considering the economy and the contribution of particular technologies of renewable energy sources (RES) to the national economy macro indicators an adequate system for state incentives and abatements of RES investments in energy industry had to be made. The key eligibility condition for support of investments in renewable energy sources is the electricity cost price of particular RES technologies. Financial aid for electric power generated from renewable energy sources is defined in "The decree regulating subsidies for electricity generated from renewable energy sources", published in the Official Gazette of the Republic of Slovenia", nr. 37/09. Among other things the decree also defines (see art. 1):


A Comparison of Electricity Generation Reference Costs

Eur/MWhel by means of the following equation:

REVENUES = sale of heat (Eur) + other benefits (Eur) ELECTRICITY = annually generated electricity (MWh)

= installed power (MWel) \* annual operating hours (h)

means of sensitivity analysis.

**2.1 Reference costs of electricity** 

cost of fuel (Eur)

**1. electricity efficiency (EffEl),** 

**2. thermal efficiency (EffT),** 

and fuel input potential.

following equations (p. 10):

**2.2 Sensitivity analysis** 

capital respectively.

p. 10):

**2. A short description of the employed methodology** 

for Different Technologies of Renewable Energy Sources 311

Reference costs of electricity were calculated in accordance with the "Methodology for the reference costs calculation of RES generated electricity" instructions that had been prepared at the Institute Jozef Stefan Energy Efficiency Centre. Investment risk was accessed by

In the "Methodology for the reference costs calculation of RES generated electricity"

RCEP represent the total annual operation costs of a typical RES production facility reduced for all revenues and benefits of operations (sale of heat, etc.) and can be formulated in

RSEG = (COSTS - REVENUES) / ELECTRICITY COSTS = annual investments (annual instalment) + operating expenses (Eur) +

The method of RCEG calculation is based on an annuity method of investment cost evaluation that also takes into account the cost of capital and the required return on invested

The calculation of RCEG for RES production facilities based on cogeneration of heat and electricity (CHE) and those that use different fuels is also affected by the following two parameters ("Methodology for the reference costs calculation of RES generated electricity",

i.e. the ratio between the output calorific power (useful heat) of the RES production facility

Fuel consumption and the generation of useful heat can be calculated by means of the

Useful heat (MWh) = Electricity potential (MWEl) \* EffT/ EffEl \* Operating hours (h)

We do not know the exact net cash flows of the investment since they are exposed to numerous risks and can only be estimated. By means of sensitivity analysis we get to know

i.e. the ratio between the CHE production facility potential and fuel input potential;

Fuel consumption (MWh) = Electricity potential (MWEl) \* Operating hours (h)

= Generated electricity (MWh) \* EffT/ EffEl

reference costs of electricity generation (RCEG) are defined on page 7 as follows:

Production facilities exploiting the following renewable energy sources meet the eligibility criteria for subsidies (art. 3):


Size classes of RES production facilities defined in "The decree regulating subsidies for electricity generated from renewable energy sources" are listed in Table 1.


Source: "Methodology of reference costs determination for electricity generated from renewable energy sources", IJS, p. 9, table 1.

Table 1. Size classes of RES production facilities.

Subsidies are defined as potentially eligible financial aid to the generation of electricity by particular RES technologies if their production costs of electricity top the market price. The fifth article of "The decree regulating subsidies for electricity generated from renewable energy sources" defines two types of subsidies for RES production facilities:


Since reference costs of electricity generation (RCEG) are the starting point for the calculation of subsidy amounts for RES production facilities in the continuation of the paper a short description of RCEG methodology and RCEG calculations for different RES technologies will be introduced. A sensitivity analysis taking into account the financial volume of the investment and the interest rate of the loan will also be displayed.

## **2. A short description of the employed methodology**

Reference costs of electricity were calculated in accordance with the "Methodology for the reference costs calculation of RES generated electricity" instructions that had been prepared at the Institute Jozef Stefan Energy Efficiency Centre. Investment risk was accessed by means of sensitivity analysis.

#### **2.1 Reference costs of electricity**

310 Energy Efficiency – A Bridge to Low Carbon Economy

Production facilities exploiting the following renewable energy sources meet the eligibility

vi. energy generated from biogas originating from the treatment of biomass and

viii. energy generated from biogas originating from sludges from the treatment of industrial

Size classes of RES production facilities defined in "The decree regulating subsidies for

criteria for subsidies (art. 3):

iv. geothermal energy;

waste water;

sources", IJS, p. 9, table 1.

decree.

i. energy potential of watercourses;

v. energy generated from biomass;

biologically degradable waste vii. energy generated from landfill gas

ii. wind energy exploited in land-based production facilities;

ix. energy generated from biologically degradable waste.

Size classes of RES production facilities Potential

Table 1. Size classes of RES production facilities.

1. compulsory purchase of electricity;

2. financial aid for current operations;

market price of electricity.

1. Micro less than 50 kW

2. Small less than 1.000 kW

3. Middle from 1 to 10 MW

4. Big over 10 to including 125 MW

energy sources" defines two types of subsidies for RES production facilities:

Source: "Methodology of reference costs determination for electricity generated from renewable energy

Subsidies are defined as potentially eligible financial aid to the generation of electricity by particular RES technologies if their production costs of electricity top the market price. The fifth article of "The decree regulating subsidies for electricity generated from renewable

The subsidiary centre purchases all net generated electricity at prices defined by this

These subsidies are granted to the net generated electricity if production costs top the

Since reference costs of electricity generation (RCEG) are the starting point for the calculation of subsidy amounts for RES production facilities in the continuation of the paper a short description of RCEG methodology and RCEG calculations for different RES technologies will be introduced. A sensitivity analysis taking into account the financial

volume of the investment and the interest rate of the loan will also be displayed.

iii. solar energy exploited in production facilities using photovoltaics;

electricity generated from renewable energy sources" are listed in Table 1.

In the "Methodology for the reference costs calculation of RES generated electricity" reference costs of electricity generation (RCEG) are defined on page 7 as follows:

RCEP represent the total annual operation costs of a typical RES production facility reduced for all revenues and benefits of operations (sale of heat, etc.) and can be formulated in Eur/MWhel by means of the following equation:

RSEG = (COSTS - REVENUES) / ELECTRICITY


The method of RCEG calculation is based on an annuity method of investment cost evaluation that also takes into account the cost of capital and the required return on invested capital respectively.

The calculation of RCEG for RES production facilities based on cogeneration of heat and electricity (CHE) and those that use different fuels is also affected by the following two parameters ("Methodology for the reference costs calculation of RES generated electricity", p. 10):

#### **1. electricity efficiency (EffEl),**

i.e. the ratio between the CHE production facility potential and fuel input potential;

#### **2. thermal efficiency (EffT),**

i.e. the ratio between the output calorific power (useful heat) of the RES production facility and fuel input potential.

Fuel consumption and the generation of useful heat can be calculated by means of the following equations (p. 10):

Fuel consumption (MWh) = Electricity potential (MWEl) \* Operating hours (h)

Useful heat (MWh) = Electricity potential (MWEl) \* EffT/ EffEl \* Operating hours (h)

= Generated electricity (MWh) \* EffT/ EffEl

#### **2.2 Sensitivity analysis**

We do not know the exact net cash flows of the investment since they are exposed to numerous risks and can only be estimated. By means of sensitivity analysis we get to know

A Comparison of Electricity Generation Reference Costs

hours

Table 2. Hydroelectric power plants - basic data.

hours

hours

Size class Size Operating

Size class Size Operating

Table 3. Wind farms - basic data.

Size class Size Operating

up to

up to

up to

up to

up to 50kW up to 1MW up to 10MW

up to

up to

up to

up to

up to

for Different Technologies of Renewable Energy Sources 313

MWe h/year Eur/kWel % inv. % inv. % inv. nr. of

50kW 0,05 4.000 2.300 0,9 % 0,6 % 1,5 % 0,03

1MW 1 3.500 1.700 1,5 % 0,6 % 1,7 % 0,4

10MW 5 3.500 1.500 1,5 % 0,6 % 1,8 % 1,8

125MW 30 3.500 1.400 1,5 % 0,6 % 1,8 % 9 Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 20, table 5

MWe h/year Eur/kWel % inv. % inv. % inv. nr. of

125MW 50 2.100 1.100 0,3 % 0,2 % 1,3 % 5 Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 21, table 6.

MWe h/annum Eur/kWel % inv. % inv. % inv. nr. of

50kW 0,05 1.050 3.620 0,1 % 0,05 % 0,4 % 0,015

1MW 0,5 1.050 3.330 0,1 % 0,05 % 0,4 % 0,15

10MW 2 1.050 2.685 0,1 % 0,04 % 0,4 % 0,5

125MW 10 1.050 2.455 0,1 % 0,04 % 0,4 % 4 Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 24, table 8.

5 2.100 1.200 0,3 % 0,2 % 1,3 % 0,5

investment Maintenance Operation Insurance Labour

investment Maintenance Operation Insurance Labour

investment Maintenance Operation Insurance Labour

persons

persons

persons

Spec.

Spec.

Spec.

Table 4. Solar power plants (as independent objects) - basic data.

how the changes of certain variables influence the volume of cash flows and consecutively the investment effectiveness indicators. Each time only one of the variables is varied assuming that the values of all other variables remain unchanged. It is of crucial importance that critical variables whose changes have a substantial influence on electricity reference costs are chosen (Brigham and Houston, 2001).

#### **3. Assumptions and data**

Assumptions are recapitulated from the "Methodology for the reference costs calculation of RES generated electricity":


Datum corresponds to an average depreciation period for RES production facilities with regard to the existing practice.


The required yield on own invested resources in Slovenia is relatively high because of the possible production transfer abroad.


Calculation of loan costs is made on the basis of EURIBOR for 2008 (4.7 %) with an extra payment of 1.8 %.


Discount rate is defined as a weighed average of capital costs (WACC). For solar power stations (in accordance with the guidelines from abroad) because of the most expensive technology a lower discount rate (8 %) was used.


Tables containing basic data for different types of power plants are taken from the "Methodology for the reference costs calculation of RES generated electricity". For waste incinerators unfortunately there are no available data. Data used include the potential of power plants (MW), number of annual operating hours, amount of investment (Eur/kW), costs of maintenance, operation and insurance (as a % of investment) and the cost of labour (number of persons employed) and are stated in Tables 2 to 7.

Electrical efficiency for a small production facility using biomass that exceeds the 90 % share of fuel energy is 12 % while for a middle sized it is 17 %; a minimum 70 % operating efficiency is required.

how the changes of certain variables influence the volume of cash flows and consecutively the investment effectiveness indicators. Each time only one of the variables is varied assuming that the values of all other variables remain unchanged. It is of crucial importance that critical variables whose changes have a substantial influence on electricity reference

Assumptions are recapitulated from the "Methodology for the reference costs calculation of

Datum corresponds to an average depreciation period for RES production facilities with

The required yield on own invested resources in Slovenia is relatively high because of the

Calculation of loan costs is made on the basis of EURIBOR for 2008 (4.7 %) with an extra

Discount rate is defined as a weighed average of capital costs (WACC). For solar power stations (in accordance with the guidelines from abroad) because of the most expensive


Tables containing basic data for different types of power plants are taken from the "Methodology for the reference costs calculation of RES generated electricity". For waste incinerators unfortunately there are no available data. Data used include the potential of power plants (MW), number of annual operating hours, amount of investment (Eur/kW), costs of maintenance, operation and insurance (as a % of investment) and the cost of labour

Electrical efficiency for a small production facility using biomass that exceeds the 90 % share of fuel energy is 12 % while for a middle sized it is 17 %; a minimum 70 % operating


costs are chosen (Brigham and Houston, 2001).


technology a lower discount rate (8 %) was used. - Annual cost of labour: 25.000 Eur/person.


(number of persons employed) and are stated in Tables 2 to 7.

**3. Assumptions and data** 


regard to the existing practice.


possible production transfer abroad.



Eur/MWh

efficiency is required.

payment of 1.8 %.

RES generated electricity":


Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 20, table 5 Table 2. Hydroelectric power plants - basic data.


Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 21, table 6. Table 3. Wind farms - basic data.


Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 24, table 8. Table 4. Solar power plants (as independent objects) - basic data.

A Comparison of Electricity Generation Reference Costs

**Type of power plant Power (MW) Investment Spec.** 

(small) <sup>1</sup> 1.700 92,16

(big) <sup>30</sup> 1.400 76,57 Wind 50 1.100 86,74 Solar 10 2.455 269,22 Geothermal 5 4.600 152,47 Biomass 2 3.200 167,43 Biogas 2 3.300 140,77

As already mentioned solar power stations have the highest while hydroelectric power plants and wind farms have the lowest reference costs. Results are displayed graphically in

> **Reference costs of electricity RSEG (Eur/MWh)**

**Hydro (small) Hydro (big) Wind Solar Geothermal Biomass**

**4.1 Reference costs of electricity** 

**4. Results** 

generated electricity".

Hydro power plant

Hydro power plant

Table 8.

Picture 1.

**Biogas**

Fig. 1. Graphical display of electricity reference costs.

for Different Technologies of Renewable Energy Sources 315

Reference costs of electricity generation (RCEG) for 5 types of power plants were calculated on the basis of methodology developed at the Institute Jozef Stefan Energy Efficiency Centre. Calculations for small and middle sized hydro power plants were done separately while for other types of RES production facilities the greatest power for which relevant data existed was used. For waste incinerators unfortunately there were no data available. Results stated in Table 8 are in accordance with the RCEG from "The decree regulating subsidies for electricity generated from renewable energy sources", Official Gazette of the Republic of Slovenia", nr. 37/09 and from the "Methodology for the reference costs calculation of RES

**(Eur/kW) RCEG (Eur/MWh)** 


(1) Individual treatment of production facilities.

Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 25, table 10. Table 5. Geothermal power plants - basic data.


Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 28, table 11. Table 6. Production facilities using biomass that exceeds the 90 % share of fuel energy.


(1) RCEG are not defined.

Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 31, table 13. For biogas plants electrical efficiency of 34 % was used.

Table 7. Biogas plants operating on biogas produced from biomass - basic data.

## **4. Results**

314 Energy Efficiency – A Bridge to Low Carbon Economy

MWe h/annum Eur/kWel % inv. % inv. % inv. nr. of

125MW (1) (1) (1) (1) (1) (1) (1)

Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 25, table 10.

MWe h/annum Eur/kWel % inv. % inv. % inv. nr. of

1MW 0,5 5.500 4.500 2,0 % 0,8 % 1,2% 1

10MW 2 5.500 3.200 2,0 % 0,8 % 1,2 % 3

Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 28, table 11.

MWe h/annum Eur/kWel % inv. % inv. % inv. nr. of

50kW 0,05 6.800 4.000 2,0 % 0,8 % 1,2 % 0,12

1MW 0,5 6.800 3.800 2,0 % 0,8 % 1,2% 1

10MW 2 6.800 3.300 2,0 % 0,8 % 1,2 % 3

125MW (1) (1) (1) (1) (1) (1) (1)

Source: "Methodology for the reference costs calculation of RES generated electricity", IJS, p. 31, table 13.

Table 7. Biogas plants operating on biogas produced from biomass - basic data.

Table 6. Production facilities using biomass that exceeds the 90 % share of fuel energy.

Spec.

5 6.000 4.600 2,0 % 0,7 % 1,2% 12

investment Maintenance Operation Insurance Labour

investment Maintenance Operation Insurance Labour

investment Maintenance Operation Insurance Labour

persons

persons

persons

Spec.

Spec.

Size class Size Operating

up to 50kW up to 1MW up to 10MW

up to

up to 50kW up to

up to

up to 125MW

up to

up to

up to

up to

(1) RCEG are not defined.

hours

(1) Individual treatment of production facilities.

Size class Size Operating

Size class Size Operating

Table 5. Geothermal power plants - basic data.

hours

hours

For biogas plants electrical efficiency of 34 % was used.

#### **4.1 Reference costs of electricity**

Reference costs of electricity generation (RCEG) for 5 types of power plants were calculated on the basis of methodology developed at the Institute Jozef Stefan Energy Efficiency Centre. Calculations for small and middle sized hydro power plants were done separately while for other types of RES production facilities the greatest power for which relevant data existed was used. For waste incinerators unfortunately there were no data available. Results stated in Table 8 are in accordance with the RCEG from "The decree regulating subsidies for electricity generated from renewable energy sources", Official Gazette of the Republic of Slovenia", nr. 37/09 and from the "Methodology for the reference costs calculation of RES generated electricity".


Table 8.

As already mentioned solar power stations have the highest while hydroelectric power plants and wind farms have the lowest reference costs. Results are displayed graphically in Picture 1.

Fig. 1. Graphical display of electricity reference costs.

A Comparison of Electricity Generation Reference Costs

that exceeds the 90 % share of fuel energy.

technologies leads to similar conclusions.

produced from biomass.

for Different Technologies of Renewable Energy Sources 317

RATE OF INVESTMENT

RCEG(Eur/MWh) 130,41 141,44 152,47 163,49 174,52 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 146,38 149,37 152,47 155,66 158,94

RATE OF INVESTMENT

RCEG(Eur/MWh) 150,69 159,06 167,43 175,79 184,16 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 162,81 165,08 167,43 169,85 172,34 Table 14. Results of the RCEG sensitivity analysis for production facilities using biomass

RATE OF INVESTMENT

RCEG(Eur/MWh) 126,81 133,79 140,77 147,75 154,72 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 136,91 138,81 140,77 142,79 144,86

The results of the sensitivity analysis of electricity reference costs for small sized hydro power plants are displayed graphically in Picture 2. A comparison of sensitivity analysis based on the modifications of observed input parameters for the remaining types of RES

Table 15. Results of the RCEG sensitivity analysis for biogas plants operating on biogas

Fig. 2. Graphical display of sensitivity analysis for small sized hydro power plants.

The inclination of the pink line indicates that reference costs are more sensitive to the modification of the investment rate than to the interest rate of the loan. The cross-section point of both lines represents the starting value of electricity reference costs for small-sized hydro power plants (92,16 Eur) reached in accordance with basic assumptions regarding the rate of investment and interest rate of the loan that are 1.700 Eur/kW (Table 8) and 6,5 %.

Table 13. Results of the RCEG sensitivity analysis for geothermal power plants.


4,5 % 5,5 % 7,5 % 8,5 %


4,5 % 5,5 % 7,5 % 8,5 %


4,5 % 5,5 % 7,5 % 8,5 %

**rate of investment**

**interest rate of the loan**

#### **4.2 Sensitivity analysis**

Taking into account the available data it was reasonable to perform a sensitivity analysis in view of the amount of investment and the interest rate of the loan. With investment costs a reduction of 10% and 20 % and an increase of 10% and 20 % was taken into account. Interest rate of the loan was varied as follows: 4,5 %, 5,5 %, 7,5 % and 9,5 %. The results are displayed in Tables 9 to 15. Investments are more sensitive to the investment input modification.


Table 9. Results of the RCEG sensitivity analysis for small hydroelectric power plants.


Table 10. Results of the RCEG sensitivity analysis for big hydroelectric power plants.


Table 11. Results of the RCEG sensitivity analysis for wind farms.


Table 12. Results of the RCEG sensitivity analysis for solar power plants.

Taking into account the available data it was reasonable to perform a sensitivity analysis in view of the amount of investment and the interest rate of the loan. With investment costs a reduction of 10% and 20 % and an increase of 10% and 20 % was taken into account. Interest rate of the loan was varied as follows: 4,5 %, 5,5 %, 7,5 % and 9,5 %. The results are displayed in Tables 9 to 15. Investments are more sensitive to the investment input

RATE OF INVESTMENT

RCEG(Eur/MWh) 78,19 85,17 92,16 99,14 106,13 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 88,30 90,20 92,16 94,18 96,26

RATE OF INVESTMENT

RCEG(Eur/MWh) 65,06 70,82 76,57 82,32 88,07 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 73,39 74,95 76,57 76,23 79,94

RATE OF INVESTMENT

RCEG(Eur/MWh) 71,67 79,21 86,74 94,27 101,8 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 82,58 84,62 86,74 88,92 91,16

RATE OF INVESTMENT

RCEG(Eur/MWh) 319,93 244,58 269,22 293,67 318,51 INTEREST RATE OF THE LOAN

RCEG(Eur/MWh 264,29 266,76 269,22 271,69 274,15

Table 11. Results of the RCEG sensitivity analysis for wind farms.

Table 12. Results of the RCEG sensitivity analysis for solar power plants.

Table 10. Results of the RCEG sensitivity analysis for big hydroelectric power plants.

Table 9. Results of the RCEG sensitivity analysis for small hydroelectric power plants.


4,5 % 5,5 % 7,5 % 8,5 %


4,5 % 5,5 % 7,5 % 8,5 %


4,5 % 5,5 % 7,5 % 8,5 %


4,5 % 5,5 % 7,5 % 8,5 %

**4.2 Sensitivity analysis** 

modification.


Table 13. Results of the RCEG sensitivity analysis for geothermal power plants.


Table 14. Results of the RCEG sensitivity analysis for production facilities using biomass that exceeds the 90 % share of fuel energy.


Table 15. Results of the RCEG sensitivity analysis for biogas plants operating on biogas produced from biomass.

The results of the sensitivity analysis of electricity reference costs for small sized hydro power plants are displayed graphically in Picture 2. A comparison of sensitivity analysis based on the modifications of observed input parameters for the remaining types of RES technologies leads to similar conclusions.

Fig. 2. Graphical display of sensitivity analysis for small sized hydro power plants.

The inclination of the pink line indicates that reference costs are more sensitive to the modification of the investment rate than to the interest rate of the loan. The cross-section point of both lines represents the starting value of electricity reference costs for small-sized hydro power plants (92,16 Eur) reached in accordance with basic assumptions regarding the rate of investment and interest rate of the loan that are 1.700 Eur/kW (Table 8) and 6,5 %.

**15** 

*Germany* 

**Recycling Hierarchical Control Strategy of Conventional Grids for Decentralized** 

Egon Ortjohann, Worpong Sinsukthavorn, Max Lingemann,

*University of Applied Sciences South Westphalia / Division Soest, Soest,* 

The objective is to develop an efficient control strategy, which is adaptable and flexible for power electronic inverter based Distributed Generation (DG) to interconnect to each other and to existing power systems. Since the proposed control strategy will be developed based on the hierarchical control structure of conventional power systems in [1, 2], it is able to handle not only modern DG sources, but also conventional sources. The general overview of the hierarchical control levels through inverter based DG are structured as shown in Fig. 1. These hierarchical control levels are the primary control at unit level, the secondary control at local level and the tertiary control at supervisory level. Moreover, as mentioned, the active controlled region of the grid is covered by higher voltage levels. With the proposed strategy, this controlled region can be expanded to medium voltage and low voltage distribution networks by active grid integration of Distributed Energy Resource (DER) based Energy Conversion Systems (ECSs) through inverters. The future inverters must be operating as intelligent and multi-functional interfaces between any ECS and grid in [3, 4].

**2. Control strategy of distributed generation based on conventional power** 

description and function of hierarchical control strategies are clarified.

Future power distribution requires extra expandability and flexibility in the integration of DG. The inverter which is used for interfacing DERs to the grids is an important part of a DG system. Therefore, the control strategy in the interconnected grids should be combined with the control methodology of inverters (grid forming, grid supporting and grid parallel modes). Load management, synchronization and load sharing with respect to generation rating, meteorological forecasting and user settings, is required in order to implement a control methodology of inverters into an interconnected system. Moreover, due to the flexibility and expandability of an inverters' control strategy, inverters in different feeding modes can be implemented into interconnected grids. In the following sections, the

**1. Introduction** 

**systems** 

Nedzad Hamsic, Marius Hoppe, Paramet Wirasanti, Andreas Schmelter, Samer Jaloudi and Danny Morton

**Power Supply Systems** 

*Department of Power Engineering,* 

Modification of the loan interest rate obviously does not represent a significant economic risk because an increase of the effective interest rate for 1 percentage point leads to an increase of electricity reference costs from approximately 1,5 Eur for big hydro power plants to approximately 3 Eur for geothermal hydro power plants. If the investment input is increased for 10 % electricity reference costs will increase from 5 to 9 %. A 5 % increase is noticed with biogas plants and production facilities operating on the basis of wooden biomass while a 9 % increase of RCEG is noticed with solar power plants. Results depend on the share of investment costs in total costs. When comparing changes of RCEG it is also necessary to take into account the cost of fuel for biogas plants and production facilities operating on the basis of wooden biomass while for the remaining five types of RES technology this is not the case.

#### **5. Conclusions**

In accordance with the proposal of the European Parliament directive Slovenia should by 2020 reach a 20 % share of RES energy in the total energy consumption. The results of our analysis display that reference costs for RES generated electricity are substantial and for most technologies even higher than the market price of electricity. In the years to come energy policy will play a crucial role as it will have to see to the decrease of capital costs and at the same time establish market conditions and incentive schemes which meet the technically conditioned effectiveness and the service life of RES production facilities.

At present in Slovenia a "Plan of action to reach target shares of RES generated electricity final consumption by 2020" is in the process of preparation. The latter will also form the basis for the adoption of the Slovenian national action plan. The target of the national action plan is to generate additional 3.000 GWh of RES generated electricity in 2020 in comparison with the currently generated volume. This plan of action makes several proposals for different possibilities and scenarios in order to reach this target.

#### **6. References**

