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作 者:孙惠娟 段伟男 陈俐 刘金祥 彭春华 SUN Huijuan;DUAN Weinan;CHEN Li;LIU Jinxiang;PENG Chunhua(School of Electrical and Automation Engineering,East China Jiaotong University,Nanchang 330013,Jiangxi Province,China)
机构地区:[1]华东交通大学电气与自动化工程学院,江西省南昌市330013
出 处:《电网技术》2024年第5期1873-1883,I0016,I0018-I0020,共15页Power System Technology
基 金:国家自然科学基金项目(52267007,52167009)。
摘 要:“双碳”背景下,以氢能为能源载体的含氢综合能源系统是中国能源行业低碳化转型的重要支撑。为保证含氢综合能源系统中的氢能供给并提高用氢效率,该文提出了一种电气混合制氢及氢能综合利用的综合能源系统运行模式;并基于碳捕集装置和综合需求响应建立了源荷互补降碳机制,以充分挖掘系统降碳潜能,进一步提升可再生能源消纳率及系统低碳化水平;此外,为了对含氢综合能源系统中的源荷随机波动实现快速响应,提出基于乐观行动-评判深度强化学习方法对系统优化调度模型进行离线训练和在线优化求解,可高效实现含氢综合能源系统的低碳经济在线优化调度。最后通过算例应用验证了所提方法的优越性。Under the background of"dual carbon",the hydrogen integrated energy system with the hydrogen energy as the energy carrier is an important support for the low-carbon transformation of China's energy industry.To ensure the supply and efficient utilization of the hydrogen energy in the hydrogen integrated energy system,this article proposes an operational mode of the integrated energy system which makes hydrogen energy from electricity and gas,which realizes the comprehensive utilization of the hydrogen energy.Based on the carbon capture devices and the integrated demand response,a carbon reduction mechanism with the complementarity between energy sources and loads is established to fully tap the potential of carbon reduction in the system,further improving the consumption rate of renewable energy and the low-carbon level of the system.In addition,in order to achieve a rapid response to the random fluctuations of the energy source and load in the integrated energy system containing hydrogen,an optimistic action-critic deep reinforcement learning method is proposed for the offline training and the online optimization of the scheduling model in the system,which efficiently achieves the low-carbon economic online optimization scheduling of the integrated energy system containing hydrogen energy.Finally,the superiority of the proposed method is verified through a responding case.
关 键 词:含氢综合能源系统 互补降碳 低碳经济调度 深度强化学习 氢能综合利用
分 类 号:TM721[电气工程—电力系统及自动化]
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