Optimal Operation Method of Electric-Hydrogen Integrated Energy System Based on Master-Slave Game

doi:10.16628/j.cnki.2095-8188.2021.07.003

Abstract

Abstract:

In order to optimize the overall economic benefit and hydrogen distribution of the electric hydrogen integrated energy system,a master-slave game based optimal operation method and strategy solving algorithm for the electric hydrogen integrated energy system are proposed in this paper.Firstly,the basic architecture of the electric and hydrogen integrated energy system is designed,and the integrated structure of production and marketing is constructed.Secondly,based on the idea of master-slave game,the energy storage behavior and hydrogen sales behavior are regarded as two virtual players of the electric hydrogen integrated energy system operators.The operator was regarded as the leader,and the two virtual players were regarded as the followers.A master-slave game model of one master and two slaves was established.Thirdly,information entropy is introduced into the genetic algorithm to calculate the initial population and design the fitness function,and the model is solved.Finally,the results of an example show that the proposed model can effectively improve the overall economic benefit of the system,and the improved information entropy genetic algorithm has a strong ability of optimization,solution accuracy and stability.

Key words: master-slave game, electric hydrogen integrated energy system, hydrogen storage system, optimal operation

CLC Number:

TM73

WAN Lixin, LU Limin, LU Huaigu, HAN Yuqian, GE Le. Optimal Operation Method of Electric-Hydrogen Integrated Energy System Based on Master-Slave Game[J]. LOW VOLTAGE APPARATUS, 2021, 0(7): 14-22.

Figures/Tables 14

References 21

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参数	数值
制氢耗损系数	0.6
燃料电池耗损系数	0.6
氢气充放效率/%	98
燃料电池单位成本/(元·kW^-1)	4 500
电解槽单位成本/(元·kW^-1)	2 210

场景	EHIESO利润/元	ESB利润/元	HSB成本/元
场景1	452.28	301.65	3 510.22
场景2	509.52	98.95	1 390.02
场景3	672.65	85.51	898.90

算法	最好解	平均解	最优解标准差
传统遗传算法	2.912	6.658	3.453
改进遗传算法	2.491	3.721	1.945

算法	最好解	平均解	最优解标准差
传统遗传算法	7.077	12.721	17.062
改进遗传算法	2.619	7.346	2.921

算法	最好解	平均解	最优解标准差
传统遗传算法	0.247	60.584	181.152
改进遗传算法	0.142	24.268	36.002