现代电力2024，Vol.41Issue(5)：854-865,12.DOI:10.19725/j.cnki.1007-2322.2022.0387
计及碳捕集装置及碳排放潮流理论的电力系统低碳优化学习调度
Low Carbon Optimal Learning Scheduling for Power Systems With Carbon Catchment Devices and Carbon Flow Theory
李吉峰 1邹楠 1李卫东 2张明泽 2吴俊1
作者信息
- 1. 国网辽宁省电力有限公司大连供电公司,辽宁省大连市 116001
- 2. 大连理工大学电气工程学院,辽宁省大连市 116024
- 折叠
摘要
Abstract
In allusion to the problems that the current research on power scheduling does not integrate the carbon emission flow with the power flow as well as the intelligence of the solu-tion algorithm still needs to be explored,a low-carbon optimal learning and scheduling method of power systems that took in-to account the carbon capture device and the carbon emission flow theory was proposed.Firstly,the power system's carbon emission flow model was constructed at the equipment and the system level respectively.Secondly,a bi-level alternating op-timal scheduling model,which includes system day-ahead scheduling and load demand response adjustment,was estab-lished by considering each link of source-grid-load-storage of the power system,and a deep reinforcement learning algorithm was adopted to solve the model.Finally,the effectiveness and applicability of the proposed theoretical approach in reducing operating costs and carbon emissions were verified through ac-tual example simulations.关键词
碳捕集/碳排放潮流/运行调度/深度强化学习/需求响应Key words
carbon capture/carbon emission flow/opera-tional scheduling/deep reinforcement learning/demand re-sponse分类
信息技术与安全科学引用本文复制引用
李吉峰,邹楠,李卫东,张明泽,吴俊..计及碳捕集装置及碳排放潮流理论的电力系统低碳优化学习调度[J].现代电力,2024,41(5):854-865,12.
