Research on Multi-Objective Energy Management of Renewable Energy Power Plant with Electrolytic Hydrogen Production

被引:2
|
作者
Shi, Tao [1 ,2 ]
Gu, Libo [1 ]
Xu, Zeyan [1 ]
Sheng, Jialin [1 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210023, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Inst Adv Technol Carbon Neutral, Nanjing 210023, Peoples R China
基金
中国国家自然科学基金;
关键词
electrolytic hydrogen; power fluctuation smoothing; peak shaving auxiliary services; fuzzy chance constraints; improved particle swarm algorithm;
D O I
10.3390/pr12030541
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This study focuses on a renewable energy power plant equipped with electrolytic hydrogen production system, aiming to optimize energy management to smooth renewable energy generation fluctuations, participate in peak shaving auxiliary services, and increase the absorption space for renewable energy. A multi-objective energy management model and corresponding algorithms were developed, incorporating considerations of cost, pricing, and the operational constraints of a renewable energy generating unit and electrolytic hydrogen production system. By introducing uncertain programming, the uncertainty issues associated with renewable energy output were successfully addressed and an improved particle swarm optimization algorithm was employed for solving. A simulation system established on the Matlab platform verified the effectiveness of the model and algorithms, demonstrating that this approach can effectively meet the demands of the electricity market while enhancing the utilization rate of renewable energies.
引用
收藏
页数:21
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