Page 98 - 《中国电力》2026年第3期
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第 59 卷 第 3 期                                                                          Vol. 59, No. 3
               2026 年 3 月                            ELECTRIC POWER                                   Mar. 2026

              引用格式:郑峰, 孙电, 黄丽丽, 等. 基于混合博弈强化学习的虚拟电厂市场交易策略[J]. 中国电力, 2026, 59(3): 94−102.
              Citation: ZHENG Feng, SUN Dian, HUANG Lili, et al. Virtual power plant market trading strategy based on hybrid game reinforcement learning[J].
              Electric Power, 2026, 59(3): 94−102.



                   基于混合博弈强化学习的虚拟电厂市场交易策略



                                      郑峰 ,孙电 ,黄丽丽 ,杨峰 ,倪芸                             2
                                                      2
                                            1
                                                                            2
                                                                  2
                                    (1. 国家能源集团长源电力股份有限公司,湖北 武汉 430000;
                                         2. 国能长源能源销售有限公司,湖北 武汉 430000)
                      Virtual power plant market trading strategy based on hybrid game
                                                reinforcement learning

                                                                                   2
                                                                      2
                                                        2
                                             1
                                 ZHENG Feng , SUN Dian , HUANG Lili , YANG Feng , NI Yun   2
                                    (1. Chn Energy Changyuan Electric Power Co., Ltd., Wuhan 430000, China;
                                      2. Guoneng Changyuan Energy Sales Co., Ltd., Wuhan 430000, China)

              Abstract:  With  the  rapid  development  of  regional  distributed  higher returns.
              energy, the issues of small installed capacity and strong output  This work is supported by Science and Technology Project of
              variability  have  become  increasingly  prominent,  resulting  in  Chn Energy Changyuan Electric Power Co., Ltd. (No.CYDL-
              insufficient   competitiveness   when   distributed   energy  2024-14).
              participates  in  market  transactions  independently.  To  enhance  Keywords:  virtual  power  plant  operators;  market  trading;
              its  market  participation  capabilities,  integrating  distributed  hybrid game
              energy  resources  into  virtual  power  plant  has  emerged  as  an
                                                                摘 要:随着地区分布式能源快速发展,其单机装机容
              effective  approach.  Therefore,  this  study  investigates  market
                                                                量小和出力随机性强的问题愈发凸显,导致分布式能源
              trading  strategies  for  virtual  power  plant  incorporating
                                                                在单独参与市场交易时竞争力不足。为提升其市场参与
              distributed  energy  resources  and  proposes  a  trading  strategy
                                                                能力,整合分布式能源形成虚拟电厂(virtual power plant,
              based  on  hybrid  game-based  reinforcement  learning.  First,
                                                                VPP)已成为一种有效途径。因此,针对含分布式能源的
              establish  revenue  models  for  energy  suppliers  and  load
                                                                VPP  市场交易策略进行研究,提出一种基于混合博弈强
              aggregators based on the operational characteristics of internal
                                                                化学习的交易策略。首先,根据虚拟电厂内部单元的运
              units within the virtual power plant. Then, to ensure the overall
                                                                行 特 性 构 建 能 源 供 应 商 和 负 荷 聚 合 商 的 收 益 模 型 ; 然
              profitability of operators within the virtual power plant, a social
                                                                后,为了保证虚拟电厂内部运营商的整体收益建立社会
              welfare  maximization  model  is  established.  Finally,  the
                                                                福利最大化模型;最后,基于            Stackelberg  博弈和演化博弈
              transaction  model  is  solved  using  a  hybrid  game-based  的混合博弈强化学习算法求解该交易模型。算例分析表
              reinforcement  learning  algorithm  combining  Stackelberg  and  明,基于混合博弈强化学习算法的双层模型求解效果优
              evolutionary  game  theory.  Case  studies  demonstrate  that  the  于其他传统智能算法,求解时间减小近  50%;此外,VPP
              two-layer model based on hybrid game-theoretic reinforcement  同 时 参 与 能 量 市 场 和 辅 助 服 务 市 场 时 , 可 获 得 更 高 的
              learning   algorithms   outperforms   traditional   intelligent  收益。
              algorithms,  reducing  computation  time  by  nearly  50%.  关键词:虚拟电厂运营商;市场交易;混合博弈
              Furthermore,  when  virtual  power  plants  participate  in  both  DOI:10.11930/j.issn.1004-9649.202506047

              energy markets and ancillary service markets, they can achieve
                                                                0    引言
              收稿日期:2025−06−17; 修回日期:2026−01−05。
              基金项目:国家能源集团长源电力股份有限公司科技项目                             “双碳”目标背景下,以风电和光伏为代表
              (CYDL-2024-14)。                                   的分布式能源快速发展            [1-5] 。然而,分布式能源的

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