| 沈阳,穆桂英,胡强,党伟,杨旭,徐芹芹.考虑综合需求响应的电-气综合能源系统低碳经济运行研究[J].电力需求侧管理,2026,28(1):33-40 |
| 考虑综合需求响应的电-气综合能源系统低碳经济运行研究 |
| Low-carbon economic operation research of electricity-gas integrated energy system considering integrated demand response |
| 投稿时间：2025-11-08 修订日期：2025-12-26 |
| DOI：10.3969/j.issn.1009-1831.2026.01.005 |
| 中文关键词: 燃气轮机-碳捕集与存储-电转气 综合需求响应 马尔科夫博弈过程 多智能体柔性动作-评价 |
| 英文关键词: GT-CCS-P2G integrated demand response Markov game process CM-MASAC |
| 基金项目:新疆维吾尔自治区重大专项“数字电力系统关键技术研发”(2022A01007 |
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| 中文摘要: |
| 面向碳中和战略目标,多能耦合协同驱动下综合能源系统(integrated energy system,IES)的低碳运行优化成为能源转型的关键路径。针对多能耦合协同运行框架,提出了一种考虑负荷需求响应的多时间尺度多维优化调度策略。首先,构建了燃气轮机-碳捕集与存储-电转气(gas turbine-carbon capture and storage-power to gas,GT-CCS-P2G)多层次耦合架构,并基于此构建了考虑综合需求响应的电-气综合能源系统(integrated electricity-gas system,IEGS)。其次,将电网和气网分别构建为一个智能体,并将IEGS调度方案转化为一个马尔科夫博弈过程。最后,通过基于通信机制的多智能体柔性动作-评价(communication mechanism-enabled multi-agent soft actor-critic,CM-MASAC)方法获得了最终调度决策。通过多种算法对比分析,探讨所提算法的先进性及综合需求响应与GT-CCS-P2G相结合的有效性。实验结果表明,所提方法相较于对比方法,最大降低10.29%运行成本和16.07%碳排放量。 |
| 英文摘要: |
| To achieve the strategic goal of carbon neutrality, optimizing the low-carbon operation of integrated energy systems (IES) through multi-energy coupling and synergy has emerged as a critical pathway for energy transition. Within the framework of multi-energy coupling and cooperative operation, a muti-dimensional optimal scheduling strategy incorporating multi-timescale analysis and load demand response is proposed. First, a multi-level coupled architecture for gas turbine-carbon capturing and storage-power to gas (GT-CCS-P2G) is constructed, and an integrated electricity-gas system (IEGS) considering comprehensive demand response is structured based on this architecture. Followed by the construction of the power grid and gas network as separate agents, and the conversion of the IEGS scheduling scheme into a Markov game process. Finally, the optimal scheduling strategy is obtained by the communication mechanism-enabled multi-agent soft actor-critic (CM-MASAC) method. Comparative analysis with multiple algorithms demonstrates both the superiority of the proposed method and the synergistic effectiveness of combining load demand response with GT-CCS-P2G technology. Experimental results indicate that this approach achieves optimal performance, reducing 10.29% operating costs and 16.07% carbon emissions compared to benchmark methods. |
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