全球能源互联网2025，Vol.8Issue(5)：552-564,13.DOI:10.19705/j.cnki.issn2096-5125.20240258
基于改进DDPG的含PCH综合能源系统低碳经济运行策略
Low-carbon Economic Operation Strategy of Integrated Energy System Containing PCH Based on Improved DDPG
摘要
Abstract
In order to make the integrated energy system better adapt to source-load uncertainty and improve its capability of low-carbon and economic operation,this paper proposes an integrated energy low-carbon economic operation strategy based on the improved deep reinforcement learning algorithm that considers the P2G(power-to-gas)-CCS(carbon capture and storage)-HFC(hydrogen fuel cell)(PCH)joint model and the improved carbon trading mechanism.Firstly,a PCH joint model with carbon sequestration capabilities was constructed,while a hydrogen energy allocation rate was introduced to achieve carbon reduction capabilities and efficient energy supply.Secondly,in order to promote the low-carbon nature of the integrated energy system dispatch strategy,an improved ladder carbon trading mechanism was proposed to replace the fixed value setting in the traditional ladder-type carbon trading mechanism.Furthermore,the mixed noise mechanism is used to improve the deep reinforcement learning algorithm which enables it to better adapt to uncertainties of source and load in low-carbon integrated energy systems.Finally,the calculation example results verify the effectiveness and adaptability of the strategy proposed in this article,as well as the positive effect of the PCH joint model and the improved carbon trading mechanism on the low-carbon of the integrated energy system.关键词
综合能源系统/低碳经济运行/改进深度强化学习/源荷不确定性/碳交易Key words
integrated energy system/low carbon economic operation/improve deep reinforcement learning/uncertainties of source and load/carbon trade分类
信息技术与安全科学引用本文复制引用
温裕鑫,范培潇,杨军,张幸,代贤忠,杨军伟..基于改进DDPG的含PCH综合能源系统低碳经济运行策略[J].全球能源互联网,2025,8(5):552-564,13.基金项目
国家自然科学基金项目(51977154) （51977154）
国家电网有限公司科技项目(5700-202257454A-2-0-ZN). National Natural Science Foundation Project of China(51977154) （5700-202257454A-2-0-ZN）
Science and Technology Foundation of SGCC(5700-202257454A-2-0-ZN). （5700-202257454A-2-0-ZN）
