Affiliations: [a] Beijing Key Laboratory of Demand Side Multi-Energy Carriers Optimization and Interaction Technique (China Electric Power Research Institute), Beijing, China | [b] School of Information Engineering, Nanchang University, Nanchang, Jiangxi, China
Correspondence:
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Corresponding author: Xuan Wen, Beijing Key Laboratory of Demand Side Multi-Energy Carriers Optimization and Interaction Technique (China Electric Power Research Institute), Beijing 100192, China. E-mail: NCUwenx@163.com.
Abstract: In order to improve the economy of the multi energy system and the efficiency of energy utilization, the research adopts the non dominated sorting genetic algorithms II (NSGA-II) to expand the population space. The elite strategy is introduced to improve the intelligent algorithm, and then the diversity of the population is retained to improve the optimization accuracy of the algorithm. In addition, the adaptive operator is introduced to improve the NSGA-II algorithm to improve the global search efficiency. The performance test of fast non dominated sorting genetic algorithm shows that the improved algorithm using elite strategy has better performance in coverage index, diversity index and convergence index. For example, in terms of convergence index, the improved NSGA-II algorithm has improved 0.0159, 0.822, 0.0243 and 0.0171 in four ZDT test functions. On the energy optimization operation for the integration of wind and hydrogen, the improved NSGA-II algorithm has obtained lower cost, with a total configuration cost of 606 million yuan, while the total system configuration cost corresponding to the unimproved NSGA-II algorithm is 624 million yuan, so the total system cost after the algorithm improvement has decreased by 18 million yuan. Therefore, this method has a better economy and higher energy efficiency.
Keywords: Wind energy, hydrogen energy, NSGA-II, energy optimization, elite strategy, population diversity, energy utilization efficiency, configuration cost
