Multi-objective Optimization of the Electricity Generation Mix in the Development of Advanced Natural Gas Fired Power Plants
DOI:
https://doi.org/10.24160/1993-6982-2026-1-52-60Keywords:
advanced power plants, sustainable energy systems, generation mix, multi-objective optimization, Pareto-optimizationAbstract
The article considers a methodology for multi-objective optimization of electricity generation mix under the conditions of increasingly growing requirements for energy efficiency and environmental safety of power systems. The main technological classes of advanced natural gas fired power plants are identified: high-efficiency, low-carbon, and zero-carbon ones. An algorithm for multi-objective optimization of the electricity generation mix has been developed. The algorithm is based on consistent application of mathematical tools, including the principal component Analysis, Pareto-optimization, entropy weighting method, and technique for order preference by similarity to ideal solution. It has been found that, given the constraints specified by the model, the share of high-efficiency power plants in Pareto-optimal generation mixes typically does not exceed 40%, while the share of low-carbon plants does not exceed 60%. With extending the energy planning horizon, the share of zero-carbon power plants in the most efficient generation mixes increases, reaching 51% with the commissioning of generating equipment in 2031 and 92% with a power system launch date in 2035. The proposed methodology makes it possible to analyze the change with time in the optimal generation mix with highlighting a priority development direction for the sustainable energy sector.
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Для цитирования: Рогалев А.Н., Лапин И.О., Максимов И.А., Злывко О.В., Маленков А.С. Многокритериальная оптимизация структуры производства электрической энергии в контексте развития перспективных энергетических комплексов, работающих на природном газе // Вестник МЭИ. 2026. № 1. С. 52—60. DOI: 10.24160/1993-6982-2026-1-52-60
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Работа выполнена при поддержке Российского научного фонда (грант № 25-79-30037), https://rscf.ru/project/25-79-30037/
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Конфликт интересов: авторы заявляют об отсутствии конфликта интересов
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17. Rebello C.M. e. a. From a Pareto Front to Pareto Regions: a Novel Standpoint for Multiobjective Optimization. Mathematics. 2021;9(24):3152.
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19. Ma W. e. a. Multi-objective Carbon Neutrality Optimization and G1-EW-TOPSIS Assessment for Renewable Energy Transition. J. Cleaner Production. 2023;415:137808.
20. Yazdani H., Baneshi M., Yaghoubi M. Techno-economic and Environmental Design of Hybrid Energy Systems Using Multi-objective Optimization and Multi-criteria Decision Making Methods. Energy Conversion and Management. 2023;282:116873
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For citation: Rogalev A.N., Lapin I.O., Maksimov I.A., Zlyvko O.V., Malenkov A.S. Multi-objective Optimization of the Electricity Generation Mix in the Development of Advanced Natural Gas Fired Power Plants. Bulletin of MPEI. 2026;1:52—60. (in Russian). DOI: 10.24160/1993-6982-2026-1-52-60
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The Work was Supported by the Russian Science Foundation (Grant No. 25-79-30037), https://rscf.ru/project/25-79-30037/
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Conflict of interests: the authors declare no conflict of interest
