| 引用本文: | 蒋 炜,郭志民,庞宇航,等.基于数字孪生模型的主从博弈掺氢综合能源系统最优决策方法[J].电力系统保护与控制,2025,53(11):72-83.[点击复制] |
| JIANG Wei,GUO Zhimin,PANG Yuhang,et al.Optimal decision-making method for hydrogen-blended integrated energy system based on digital twin models and Stackelberg game theory[J].Power System Protection and Control,2025,53(11):72-83[点击复制] |
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| 摘要: |
| 建立了一个包含综合能源系统运营商(integrated energy system operator, IESO)、基于碳捕集系统(carbon capture system, CCS)的能源供应商(energy supplier, ES)以及考虑需求响应的负荷聚合商(load aggregator, LA)的综合能源系统(integrated energy system, IES)数字孪生模型系统。首先，构建了IES系统模型，针对不同系统类型制定相应的约束条件，同时引入弃风弃光惩罚方法。其次，采用一种基于主从博弈的IES分布式协同优化运行策略，并结合遗传算法和二次规划算法求解模型，得到IES最优调度方案。在该主从博弈的框架中，IESO作为主导者，与CCS的ES和考虑需求侧响应的LA作为跟随者协同优化，优化IESO的定价策略、ES的出力计划和用户需求。通过数字孪生系统获得实时的IES数据，对不同维度、不同格式的数据进行统一处理分析后，再利用所提方法进行优化，得到IES最优决策方案。最后，通过数字孪生模型获得IES基础运行数据并基于扩展的IEEE39节点系统和6节点供暖系统仿真实验得到了IESO最优价格策略、ES最佳出力计划及LA最佳用能计划，使得供能更加经济、用能更加合理。基于数字孪生模型的主从博弈的决策方法能够使电网摆脱对历史运行数据的强依赖，降低决策的外推误差，实现IES优化决策技术升级。 |
| 关键词: 综合能源系统 主从博弈 数字孪生 碳捕集系统 需求侧响应 |
| DOI：10.19783/j.cnki.pspc.240604 |
| 投稿时间：2024-05-15修订日期：2024-07-03 |
| 基金项目:国家电网有限公司科技项目资助(5700- 202224202A-1-1-ZN)“面向县域能源互联网高效协同的数字孪生化管理及互动技术研究” |
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| Optimal decision-making method for hydrogen-blended integrated energy system based on digital twin models and Stackelberg game theory |
| JIANG Wei1,GUO Zhimin2,PANG Yuhang3,ZHANG Tongtong3,WANG Yanan3,ZHAO Jian2,DING Huixia3,WANG Xinyan4 |
| (1. State Grid Corporation of China, Beijing 100032, China; 2. State Grid Henan Electric Power Research Institute,
Zhengzhou 450000, China; 3. China Electric Power Research Institute, Beijing 100192, China; 4. State Grid
Henan Information & Telecommunication Company (Data Center), Zhengzhou 450000, China) |
| Abstract: |
| A digital twin model of an integrated energy system (IES) is established, incorporating an integrated energy system operator (IESO), an energy supplier (ES) equipped with carbon capture system (CCS), and a load aggregator (LA) that considers demand response. First, the IES system model is constructed, with tailored constraints for different system components and the introduction of a penalty mechanism for wind and solar curtailment. Then, an IES distributed cooperative optimal operation strategy based on a leader-follower (Stackelberg) game is adopted, and the strategy is solved by combining genetic algorithm and quadratic programming algorithm to obtain the optimal IES scheduling scheme. In this game theory framework, IESO acts as the lead player, while the CCS-based ES and the demand response LA act as followers, jointly optimize the IESO’s pricing strategy, ES contribution plan, and user demand schedules. Real-time IES data is obtained by the digital twin system. After the data of different dimensions and formats are processed and analyzed in a unified manner, the proposed method is used to optimize the IES optimal decision scheme. Finally, by using the digital twin model to obtain the basic operation data, simulation experiments based on the extended IEEE 39-node system and 6-node heating system yield IESO optimal price strategy, ES optimal output plan, and LA optimal energy use plan, leading to more economical energy supply and more rational energy consumption. The leader-follower game-based decision-making method based on a digital twin model, allows the power grid to move beyond heavy reliance on historical data, reduces extrapolation errors in decision-making, and enables a technical upgrade in IES optimization strategies. |
| Key words: integrated energy system Stackelberg game digital twin carbon capture system demand response |
