Optimal siting of wind and solar power plants in an electric power system

This study developed a single‑criterion mathematical model for selecting optimal sites for wind and solar power plants within an electric power system, taking into account renewable generation variability and economic efficiency. The objective functions included maximizing total electricity output, minimizing the overall rate of power change, minimizing total power increments, and maximizing base power, subject to constraints on installed capacity and the number of units per site. A test system was designed with six potential sites for wind power plants and two sites for solar power plants, with a combined installed capacity of 600 MW. The study proposed an algorithm integrating daily power profile simulations for a single wind turbine and a photovoltaic module group across candidate sites with varying topography and daylight duration. Optimization of installed capacity distribution among sites was then performed. Application of the model to the test system showed that the type of objective function significantly affects the configuration of the optimal system and the allocation of capacity among sites. Transitioning from the criterion of maximum electricity output to criteria related to power dynamics reduces generation by 6–7%, while decreasing the total rate of power change and total power increments by 19–39% and increasing base power by up to 38%. The proposed optimization algorithm provides a systematic framework for decision-making in the design of renewable energy systems with minimal internal volatility of generation. The selection of the objective function depends on the flexibility characteristics of a given power system and can be applied at early stages of planning renewable energy facilities.

1. Solomon B.D., Pasqualetti M.J., Nelson E. Global disparities in renewable energy development: where they exist and why. Applied Geography. 2026;186:103825. https://doi.org/10.1016/j.apgeog.2025.103825.

2. Akusta E., Cergibozan R. The role of renewable energy sources on the path to sustainable development for OECD countries: Considering the three pillars of sustainability. Renewable Energy. 2026;256(D):124101. https://doi.org/10.1016/j.renene.2025.124101.

3. Abdelhady S. Performance and cost evaluation of solar dish power plant: sensitivity analysis of levelized cost of electricity (LCOE) and net present value (NPV). Renewable Energy. 2021;168:332-342. https://doi.org/10.1016/j.renene.2020.12.074. EDN: ABXYHP.

4. Durakovic A. DEC rolls out 13 MW offshore wind turbine. Offshorewind.biz. Available from: https://www.offshorewind.biz/2022/02/23/dec-rolls-out-13-mw-offshore-wind-turbine/ [Accessed 10th September 2025].

5. Moon Hee Seung, Baik Sunhee, Park Won Young. Assessing the levelized cost of energy in South Korea. Energy Strategy Reviews. 2025;62:101897. https://doi.org/10.1016/j.esr.2025.101897.

6. Kabeyi M.J.B., Olanrewaju O.A. The levelized cost of energy and modifications for use in electricity generation planning. Energy Reports. 2023;9(9):495-534. https://doi.org/10.1016/j.egyr.2023.06.036.

7. Zhang Yu, Zhang Yongkang, Wu Tiezhou. Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control. Global Energy Interconnection. 2024;7(1):71-81. https://doi.org/10.1016/j.gloei.2024.01.007. EDN: MZNSFG.

8. Assireu A.T., Fisch G., Carvalho V.S.O., Pimenta F.M., De Freitas R.M., Saavedra O.R., et al. Sea breeze-driven effects on wind down-ramps: Their implications for wind farms along the north-east coast of Brazil. Energy. 2024;294:130804. https://doi.org/10.1016/j.energy.2024.130804. EDN: OIKOBM.

9. Artemyev A.Yu., Shakirov V.A., Yakovkina T.N. Criteria-based choice of areas for siting the wind power plants. Systems. Methods. Technologies. 2016;3:116-122. (In Russ.). https://doi.org/10.18324/2077-5415-2016-3-116-122. EDN: XQSOBH.

10. Wang Han, Zhang Ning, Du Ershun, Yan Jie, Han Shuang, Liu Yongqian. A comprehensive review for wind, solar, and electrical load forecasting methods. Global Energy Interconnection. 2022;5(1):9-30. https://doi.org/10.1016/j.gloei.2022.04.002. EDN: VYPUDU.

11. Sigitov O.Yu. Comparative analysis of wind farms dynamic coefficient of unevenness in various energy systems. RUDN Journal of Engineering Research. Seriya: Inzhenernye issledovaniya. 2025;26(1):28-38. (In Russ.). http://doi.org/10.22363/2312-8143-2025-26-1-28-38. EDN: JWTYWJ.

12. Álvarez-García F.J., Fresno-Schmolk G., OrtizBevia M.J., Cabos W., RuizdeElvira A. Reduction of aggregate wind power variability using empirical orthogonal teleconnections: an application in the Iberian Peninsula. Renewable Energy. 2020;159:151-161. https://doi.org/10.1016/j.renene.2020.05.153.

13. Shahriari M., Blumsack S. Scaling of wind energy variability over space and time. Applied Energy. 2017;195:572-585. https://doi.org/10.1016/j.apenergy.2017.03.073.

14. Sigitov O.Yu. A single-criteria optimization of wind farms construction sites. Bulletin of the Russian Academy of Sciences. Energetics. 2025;3:92-112. (In Russ.). https://doi.org/10.31857/S0002331025030067. EDN: KPZLJP.

15. Suslov K.V. Development of power supply systems of Russian isolated territories using renewable energy sources. Proceedings of Irkutsk State Technical University. 2017;21(5):131-142. (In Russ.). https://doi.org/10.21285/1814-3520-2017-5-131-142. EDN: YPLMUH.

16. Voropai N.I., Podkovalnikov S.V., Trufanov V.V., Belyaev L.S., Galperova E.V., Domyshev A.V., et al. Substantiation of electric power system development. Methodology, models, methods, and their use: a monograph. Novosibirsk: Nauka; 2015, 448 p. (In Russ.). EDN: ULMZZB.

17. Pourasl H.H., Barenji R.V., Khojastehnezhad V.M. Solar energy status in the world: a comprehensive review. Energy Reports. 2023;10:3474-3493. https://doi.org/10.1016/j.egyr.2023.10.022. EDN: IDZWRD.

18. Olkhovsky G., Radin Yu., Makarow O., Osika A., Trushechkin V. Expansion of operational load range of the CCPP 450 Mw. Power Technology and Engineering. 2015;3:2-9. (In Russ.). EDN: TQCIMH.

19. Radin Yu.A., Lenev S.N. Some features of combined-cycle gas turbine unit operation. Problems and prospects. Gazoturbinnye tekhnologii. 2024;1:2-6. (In Russ.). EDN: DSQFAZ.

20. Kostyuk R.I., Piskovatskov I.N., Chugin A.V., Koshok N.N., Radin Yu.A., Berezinets P.A. Several features of the operating conditions of the pilot PGU-450T power-generating unit. Thermal Engineering. 2002;9:6-11. (In Russ.). EDN: XROORT.

21. Teplov B.D., Radin Yu.A., Filin A.A., Rudenko D.V. Thermal tests of the SGT5-4000F gas-turbine plant of the PGU- 420T power-generating unit at Combined Heat and Power Plant 16 of Mosenergo. Thermal Engineering. 2016;8:10-17. (In Russ.). https://doi.org/10.1134/S0040363616080117. EDN: WDOUHD.

22. Radin Yu.A., Sigitov O.Yu., Zorchenko N.V. Thermal power plant flexibility in energy systems with wind farms. Power Technology and Engineering. (In Russ.). EDN: LGYQHG.

23. Teplov B.D., Radin Yu.A. Improving flexibility and economic efficiency of CCGT units’ operation in the conditions of the wholesale electricity market. Thermal Engineering. 2019;5:39-47. (In Russ.). https://doi.org/10.1134/S0040363619050096. EDN: ZBGRFB.