基于电解槽状态识别的风光制氢系统能量管理优化

年珩; 陈磊磊; 赵建勇; 马润生; 赵文强; 王克荣

年珩,陈磊磊,赵建勇,马润生,赵文强,王克荣.基于电解槽状态识别的风光制氢系统能量管理优化[J].电测与仪表,2023,60(10):10-16.
Nian Heng,Chen Leilei,Zhao Jianyong,Ma Runsheng,Zhao Wenqiang,Wang Kerong.Energy management optimization of photovoltaic hydrogen production system based on electrolytic cell state recognition[J].Electrical Measurement & Instrumentation,2023,60(10):10-16.

基于电解槽状态识别的风光制氢系统能量管理优化

Energy management optimization of photovoltaic hydrogen production system based on electrolytic cell state recognition

DOI：10.19753/j.issn1001-1390.2023.10.002

中文关键词: 碱性电解槽状态识别风光制氢系统能量管理 GA算法 SPEA2算法

英文关键词:alkaline water electrolysis, state recognition, wind-solar hydrogen production system, energy management, the GA algorithm, the SPEA2 algorithm.

基金项目:国网青海省电力公司科技项目资助(522807220002)、浙江省教育厅科研项目资助(Y202044527)、(Y202250621)

作者中文名	作者英文名	单位
年珩	Nian Heng	浙江大学电气工程学院
陈磊磊	Chen Leilei	浙江大学电气工程学院
赵建勇	Zhao Jianyong	浙江大学电气工程学院
马润生	Ma Runsheng	国网青海省电力公司电力科学研究院
赵文强	Zhao Wenqiang	国网青海省电力公司电力科学研究院
王克荣	Wang Kerong	国网青海省电力公司电力科学研究院

摘要点击次数: 1501

中文摘要:

风光制氢系统可以实现风光发电消纳、氢能绿色制取,具有很好的战略意义。针对碱性电解槽备用状态的选取问题,提出了一种基于碱性电解槽状态识别的风光制氢系统能量管理优化策略。首先确定制氢系统组成,建立系统模块模型；其次确定系统风光消纳率、售氢收益比为目标,确定系统运行约束条件,采用SPEA2+GA算法；之后结合天气预测数据、电网数据,以能量管理优化策略确定电解槽冷、热备用状态；最后利用算例论证。算例结果显示能量管理优化策略能准确识别碱性电解槽冷、热备用状态,能够利用冷备用状态节约系统电能,合理分配系统内功率,提高系统收益。

英文摘要:

The wind-solar hydrogen production system can realize the consumption of wind-solar power generation and the green production of hydrogen energy, which has a good strategic significance. Aiming at the problem of selecting the alkaline water electrolyzers standby state, an optimization strategy for energy management of wind-solar hydrogen generation system based on alkaline water electrolyzers state recognition is proposed. Firstly, the composition of hydrogen production system is determined and the system module model is established. Secondly, the absorption rate of wind-solar power generation and the profit ratio of hydrogen sales are determined as the objectives, and the constraints of system operation are determined. GA and SPEA2 algorithms were used at the same time. Then combined with the weather forecast data and power grid data, the cold or hot standby state of the electrolyzer was determined by the energy management optimization strategy. Finally, a numerical example is used to demonstrate. The results of the example show that the energy management optimization strategy can accurately identify the cold or hot standby state of alkaline water electrolyzers, and can use the cold standby state to save the system energy, reasonably distribute the power in the system, and improve the system revenue.#$NLKeywords: alkaline water electrolysis, state recognition, wind-solar hydrogen production system, energy management, the GA algorithm, the SPEA2 algorithm.

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