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Multi-objective optimization dispatch of power systems including geothermal power generation based on improved NSGA-II algorithm
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Xiangqi KONG1, Peng ZHANG2, Xun MENG1, Meng SHAO1, Tao TANG1, Xinru ZHANG1, Jinwei SUN1
Thermal Power Generation | 2025, 54(2) : 30 - 41
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Thermal Power Generation | 2025, 54(2): 30-41
• Integrated technology of source-grid-load-storage •
Multi-objective optimization dispatch of power systems including geothermal power generation based on improved NSGA-II algorithm
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Xiangqi KONG1, Peng ZHANG2, Xun MENG1, Meng SHAO1, Tao TANG1, Xinru ZHANG1, Jinwei SUN1
Affiliations
  • 1.College of Engineering, Ocean University of China, Qingdao 266100, China
  • 2.China Renewable Energy Engineering Institute, Beijing 100120, China
Published: 2025-02-25 doi: 10.19666/j.rlfd.202406132
Outline
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In response to the current problems of high volatility in wind and photovoltaic power generation and difficulties in consumption in typical areas, a new hybrid energy system optimization scheduling method for promoting wind and solar consumption through geothermal power generation is proposed by incorporating reliable and rapidly climbing geothermal power generation into the hybrid energy system. Taking into account both operational costs and risks, and constrained by physical characteristics of the power units, a multi-objective optimization dispatch model for the new hybrid energy system is established. A rolling repair strategy is introduced to correct the initial values of the population, and the model is solved based on the adaptive trade-off model and the non-dominated sorting genetic algorithm II. This algorithm is more suitable for solving high-dimensional, complex constraint problems compared with the conventional algorithms and offers a faster convergence rate. Through a comparative analysis of two scenarios during typical winter days in a specific region of Tibet, geothermal power is found to enhance the absorption rates of wind and solar energy by 8.0% and 7.9%, respectively. Simultaneously, the system’s operating costs decreases by 2.5%, and risk indices decreases by 7.1%. These findings underscore the role of geothermal power in promoting the integration of wind and solar energy and improving the overall reliability of the power system. The research provides valuable theoretical support for decision-making and scheduling in hybrid energy systems.

hybrid energy system  /  geothermal power generation  /  multi-objective optimization  /  adaptive trade-off model  /  non-dominated sorting genetic algorithm
Xiangqi KONG, Peng ZHANG, Xun MENG, Meng SHAO, Tao TANG, Xinru ZHANG, Jinwei SUN. Multi-objective optimization dispatch of power systems including geothermal power generation based on improved NSGA-II algorithm[J]. Thermal Power Generation, 2025 , 54 (2) : 30 -41 . DOI: 10.19666/j.rlfd.202406132
Funding
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  • Natural Science Foundation of Shandong Province(ZR2023ME028)
  • National Natural Science Foundation of China(51609224; 52071307)
  • China Renewable Energy Engineering Institute Research Project(ZY-KJXN-20230025)
  • National Key Research and Development Program of China(2022YFC3104201)
Appendix
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Year 2025 volume 54 Issue 2
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128
55
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Article Info
doi: 10.19666/j.rlfd.202406132
  • Receive Date：2024-06-12
  • Online Date：2026-03-06
  • Published：2025-02-25
Article Data
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History
  • Received：2024-06-12
Funding
Natural Science Foundation of Shandong Province(ZR2023ME028)
National Natural Science Foundation of China(51609224; 52071307)
China Renewable Energy Engineering Institute Research Project(ZY-KJXN-20230025)
National Key Research and Development Program of China(2022YFC3104201)
Affiliations
    1.College of Engineering, Ocean University of China, Qingdao 266100, China
    2.China Renewable Energy Engineering Institute, Beijing 100120, China
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202406132
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