Day-Head Scheduling Optimal Operation Strategy for Wind-Solar-Hydrogen-Heat Cogeneration Virtual Power Plants Considering Hydrogen Load Requirements

doi:10.3969/j.issn.1008-0198.2024.06.001

Abstract

Abstract: The cogeneration virtual power plant with hydrogen storage provides a new path for hydrogen storage to participate in grid scheduling and consume new energy by combining the cogeneration characteristics of the aggregated resources. First, the cogeneration characteristics of hydrogen storage energy are fully considered, and the day-ahead scheduling optimization model that minimizes the comprehensive operating cost of the virtual power plant is established to make decisions on the day-ahead output plan of the aggregated resources under the condition of meeting the heat and electricity load demand.Then,the day-ahead hydrogen demand forecast model is established by considering the load-side hydrogen demand, including the hydrogen fuel demand of hydrogen buses and hydrogen cars. Next, the hydrogen demand is embedded as a constraintinto the virtual power plant day-ahead scheduling optimization model to obtain the optimal operation strategy of the virtual power plant under the consideration of hydrogen load demand. Finally,a simulation analysis in a park is conducted, and the results show that the operating cost of the optimal scheduling strategy of the virtual power plant considering the revenue from hydrogen sales is reduced by 24.6% compared with the traditional virtual power plant scheduling strategy only considering the characteristics of hydrogen storage cogeneration.

Key words: virtual power plant, wind-solar-hydrogen-heat cogeneration, optimal operation, hydrogen energy storage, hydrogen load requirements

CLC Number:

TM732

CUI Xianyi, ZENG Weijie, CUI Zezheng, LIU Mouhai, SHEN Liman, MA Yeqin. Day-Head Scheduling Optimal Operation Strategy for Wind-Solar-Hydrogen-Heat Cogeneration Virtual Power Plants Considering Hydrogen Load Requirements[J]. Hunan Electric Power, 2024, 44(6): 1-9.

References

[1] WANG C L,WANG H,JI X,et al.Hybrid energy storage capacity configuration strategy for virtual power plants based on variable-ratio natural gas-hydrogen blending[J].International Journal of Hydrogen Energy,2024,58:433-445.
[2] 谭玲玲,孙鹏,郭沛璇,等. 含氢储能的微电网低碳-经济协同优化配置[J]. 发电技术,2024,45(5):983-984.
[3] 李咸善,胡长宇,张远航,等. 风电租赁储能参与电能-调频市场竞价策略[J]. 电网技术,48(5):1992-2002.
[4] 张昊天,韦钢,袁洪涛,等. 考虑氢-电混合储能的直流配电网优化调度[J]. 电力系统自动化,2021,45(14):72-81.
[5] 石梦舒,许小峰,张继广,等. 考虑电-氢市场的虚拟电厂两阶段优化政策研究[J]. 发电技术,2023,44(5):645-655.
[6] 王兆霖,张海波,陈会来.考虑氢燃料汽车与氢储能的虚拟电厂协调调度[J]. 华北电力大学学报(自然科学版),2024,51(4):69-76,86.
[7] 王秋杰,刘国安,谭洪,等.考虑电氢耦合的虚拟电厂鲁棒可行域模型与求解[J/OL]. 电网技术,1-15.(2024-06-18)[2024-10-12]. https://doi.org/10.13335/j.1000-3673.pst.2024.0510.
[8] 陈永权,方瑜. 多组合虚拟电厂中氢储能低碳经济配置与优化[J]. 电网与清洁能源,2024,40(3):107-118.
[9] ZHANG W Y,SHEN Y,WANG X Y,et al.Research on multi-market strategies for virtual power plants with hydrogen energy storage[J]. Frontiers in Energy Research,2023,11:1260251.
[10] 刘雨佳,樊艳芳,郝俊伟,等. 基于碱性电解槽宽功率适应模型的风光氢热虚拟电厂容量配置与调度优化[J]. 电力系统保护与控制,2022,50(10):48-60.
[11] 熊宇峰,司杨,郑天文,等. 基于主从博弈的工业园区综合能源系统氢储能优化配置[J]. 电工技术学报,2021,36(3):507-516.
[12] 万立新,陆立民,陆怀谷,等. 基于主从博弈的电氢综合能源系统优化运行方法[J]. 电器与能效管理技术,2021(7):14-22.
[13] 马永翔,马少洁,闫群民,等.虚拟电厂与电动汽车用户的主从博弈定价策略[J/OL].华北电力大学学报(自然科学版),1-10. (2023-08-23)[2024-10-12]. http://kns.cnki.net/kcms/detail/13.1212.tm.20230822.1034.006.html.
[14] 郑杰凯,何山,韩璐,等. 计及混合博弈配电网与氢能系统的多综合能源服务商优化调度[J/OL]. 电力自动化设备,1-18.(2024-09-03)[2024-10-12].https://doi.org/10.16081/j.epae.202409002.
[15] 陈锦鹏,胡志坚,陈颖光,等. 考虑阶梯式碳交易机制与电制氢的综合能源系统热电优化[J]. 电力自动化设备,2021,41(9):48-55.
[16] 李建林,孙浩元,梁忠豪,等.多能需求场景下的综合能源系统容量优化配置[J/OL]. 高电压技术,1-12.(2024-08-29)[2024-10-12].https://doi.org/10.13336/j.1003-6520.hve.20240688.
[17] 田雪沁,杨恒,袁铁江,等. 基于共享氢储能的电氢制充注一体站日前优化经济调度[J/OL]. 高电压技术,1-12.(2024-09-04)[2024-10-12].https://doi.org/10.13336/j.1003-6520.hve.20240271.
[18] 王秋杰,亓浩,谭洪,等.考虑碳市场风险的热电联产虚拟电厂低碳调度[J]. 电力自动化设备,2024,44(10):8-15.
[19] 王海洋,李珂,张承慧,等.基于主从博弈的社区综合能源系统分布式协同优化运行策略[J]. 中国电机工程学报,2020,40(17):5435-5445.
[20] 董军,方琳怡,姚文璐,等.基于主从博弈的综合能源系统多能定价及调度优化[J]. 浙江电力,2024,43(9):19-28.