1. Costing of energy generation of multi area interconnected systems with conventional as well as renewable sources Kaisar R. Khan McNeese State University Lake Charles, LA 70605

2. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

3. Two Area Interconnected System X and Y resembles the two geographically isolated utility systems but electrically interconnected by a tie line with capacity TC. Each system is having a projected hourly load pattern with generating unit (SOU/JOU) to meet its own demand first and then they can export some of the generated energy if they have excess and the other system has demand.

4. Renewable Energy Sources in the Interconnected System Renewable energy sources are driving a great deal of research effort in different dimension in power system. It is primarily due to the minimum cost of energy generation and environmental friendliness. Solar, wind, hydro, geothermal, wave are few example of energy sources that are feasible alternative to the conventional fossil fuel burning electric generating unit. Inclusion of renewable generating unit to harvest solar/wind energy requires special attention to evaluate expected energy generation (EEG) as its availability is random (depending on the wind/solar profile). Wind profile is affected by the seasonal, weather and hourly variation of wind. Similar characteristics has been observed for solar irradiance.

5. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

6. The evaluation Procedure of the expected energy generated by a unit 1.Evaluate the expected export. Modify the demands of the exporting and the importing systems as well as the tie line capacity 2.Evaluate the expected share transfer from a JOU to the system where the unit is not located. Accordingly modify only the tie line capacity. For conventional unit this step is not necessary. 3.For unit with renewable (wind/solar) energy source modify the capacity according to hourly generation data and follow the above two steps used for conventional units. For the sake of simplicity we consider our renewable generation unit is considered as separately owned. 4.Obtain the expected unserved energy. If the committed unit is a JOU the evaluation of unserved energies of both the systems is required because both of them generate energy. 5.Convolve the unit [4,5]. 6.Recalculate the unserved energy after the convolution of the unit. 7.Calculate the EEG of each unit which is the deference of two unserved energies evaluated before and after the convolution.

7. Export or Import 1) Export Using Tie Line: A system will export to the other interconnected system to meet their excess demand only when the exporting system has surplus capacity and residual tie line capacity permits the export. 2) Export Without Using Tie Line: Since the JOU is located in system Y the export from the share of system X to system Y does not require the tie line. The amount of export depends on the expected unserved demand of system Y and the portion of share, which has not been transferred to system X, and it may be evaluated as the method mentioned in the previously reported results* For unit with renewable energy source modify the capacity according to hourly generation data. Kaisar R Khan, Q. Ahsan and M. R Bhuiyan, “Expected Energy Production Cost of Two Area interconnected Systems with Jointly Owned Units” Electric Power System Research journal (Elseiver),vol. 69, pp. 115-122, April 2004

8. LOLP Evaluation Follow the step 1-5 mentioned before. Recalculate the unserved energy after the convolution of the unit. If the unserved energy is less than or equal to zero then that segment is already served and will not include in LOLP calculation. Sum of the zero-th moment of probability of all the segment where unserved energy after convolving the generator is greater than or equal to zero is our LOLP.

9. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

10. Wind Generation The energy output from a wind turbine depends on the wind profile. If the wind speed is too low or too high then the wind generators are out of service. For that reason the availability of the generator depends on the wind profiles that are useable for electrical generation. Also the output power varies linearly with the wind speed and the probability distribution function (PDF) of the wind generators availability. The PDF follows the Weibull distribution. We consider wind generators having multi states of output powers and probability of being available.

11. Wind Profile Measured at SUNY Canton Weather Station (a) Wind speed measured at two different heights (30 m solid line, 20 m dashed line) and (b) Annual Wind speed Distribution of 2008 Modelled using Weibull Distribution

12. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

13. Two Area Interconnected System Example: Hourly load demand for both systems and the global demand X TC Area Y

14. EEG for individual unit committed in loading order with a tie line capacity of 450 MW EEG for individual unit committed in loading order with a tie line capacity of 450 MW Loading order Type of unit Capacity (MW) FORLocationOwner- ship Expected energy generation (GWh) 1Wind 1Variable 175(max) VariableYSOU3.348 2Hydro1200.032XSOU2.7878 3Steam Turbine17200.069XSOU16.087 4Steam Turbine2806+400.097XJOU10.99 5Combined Cycle1400.15XSOU0.1473 6Gas Turbine1420.33XSOU0.20 7Diesel Engine90.1YSOU0.012 8Barge Mounted180.15YSOU0.016 9Gas Turbine1670.27YSOU0.072 Total2337------------- 33.667 (Global generation)

15. (a) (b) Expected Energy Generation (a)Global EEG and (b) Expected Global Export with tie line capacities of the two area interconnected system having wind generators Kaisar Khan, Ahmed Arkaoub, Mohammed Youssef and Mike J. Newtown, “Evaluation of Loss of Load Probability and Expected Energy Generation in Multi-Area Interconnected Systems with Wind Generating Units”, Journal of Energy and power Engineering 8(2014) 805-811.

16. LOLP of the interconnected system with wind generators

17. Effect of TC variation on LOLP (a) (b)

18. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

19. Hourly Load and Expected Generation of BPS

20. Expected Energy Generation I Kaisar R. Khan, Ahmed A. Arkoub and Quamrul Ahsan, “Evaluation of expected energy generation in multi-area interconnected systems with photo voltaic generating units”, International Journal of Environmental Studies, DOI:10.1080/00207233.2013.798499

21. Expected Energy Generation II (a)Global EEG (b & c) Expected Global Export with tie line capacities of the two area interconnected system having solar generators

22. Effect of TC variation on EEG

23. Outline Introduction Proposed Numerical Model Wind Profile and Modification of the model Evaluation of EEG for a Two Area Interconnected System with Wind Generating Units Results for the system with PV generation Conclusion

24. Conclusions A model has been developed to evaluate the reliability and expected energy generation of a two area interconnected system with wind generation. The model also can successfully include the stochastic behavior of wind/solar generating units. This will give designer or system planners better ideas of how to include renewable generators for reliable and economic expansion of interconnected networks. The results show that even though renewable generators are economic but that will add more uncertainty while meeting the demand. Proper scheduling of generation is required to maximize the use of the wind energy resource.