Optimization Operation of Multi-agent Mixed Game in Community Comprehensive Energy System Considering Source-load Uncertainty

WANG Chengjiang; XU Xiaorui; YUAN Xiaohong; WEI Shimeng

doi:10.19725/j.cnki.1007-2322.2023.0292

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Optimization Operation of Multi-agent Mixed Game in Community Comprehensive Energy System Considering Source-load Uncertainty

更新时间：2025-12-11

- Optimization Operation of Multi-agent Mixed Game in Community Comprehensive Energy System Considering Source-load Uncertainty
- Issue 6, Pages: 1318-1328(2025)
- 作者机构：
  
  三峡大学电气与新能源学院,湖北省,宜昌市,443002
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0292
  CLC：
- Published：2025
- 稿件说明：
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WANG Chengjiang, XU Xiaorui, YUAN Xiaohong, et al. Optimization Operation of Multi-agent Mixed Game in Community Comprehensive Energy System Considering Source-load Uncertainty[J]. 2025, (6): 1318-1328.
DOI：

WANG Chengjiang, XU Xiaorui, YUAN Xiaohong, et al. Optimization Operation of Multi-agent Mixed Game in Community Comprehensive Energy System Considering Source-load Uncertainty[J]. 2025, (6): 1318-1328. DOI： 10.19725/j.cnki.1007-2322.2023.0292.

摘要

为进一步探究源荷不确定下含产消者的社区综合能源系统多主体间的功率交互与利益分配，提出了计及源荷不确定性的社区综合能源系统多主体混合博弈优化运行模型。首先搭建能源服务商为上层领导者，用户联盟为下层跟随者的双层混合博弈框架。其次以成本最小化为目标构建上下层优化模型，其中上层服务商通过制定能源价格引导下层联盟合理用能，下层联盟通过合作博弈对上层服务商决策进行响应，且为保证联盟中各主体间效益的合理分配，基于纳什谈判理论将下层联盟优化模型分解为联盟成本最小化与联盟电能交易支付两个子问题。然后考虑上层源荷不确定性构建三阶段鲁棒优化模型，利用KKT条件将模型中双层博弈问题转化为单层线性化问题。最后使用列与约束生成算法结合交替方向乘子法对模型进行求解。算例结果证明所提构建模型能有效应对上层源荷不确定性风险，在协调各方运行优化的同时实现了联盟效益的合理分配与社区总成本的降低。

Abstract

To further investigate power interaction and benefit allocation among multiple agents in a community integrated energy system with producers and consumers under source-load uncertainty

in this paper we propose a two-layer mixed game optimization operation model for the community integrated energy system

with asource load uncertainty taken into account. The first step involves establishing a two-layer hybrid game framework

with energy service providers as upper level leaders and user alliances as lower level followers. Secondly

an upper and lower level optimization model is constructed with the goal of minimizing costs. The upper level service provider guides the lower level alliance to use energy reasonably by setting energy prices

while the lower level alliance responds to the decisions of the upper level service provider through cooperative games. To ensure the reasonable allocation of benefits among various entities in the alliance

based on Nash negotiation theory

the lower level alliance optimization model is decomposed into two sub problems: alliance cost minimization and alliance energy transaction payment. Subsequently

a three-stage robust optimization model is constructed considering the uncertainty of the upper source load

and the KKT condition is utilized to transform the two-layer game problem within the model into a single-layer linearization problem. Finally

the model is solved using the column and constraint generation algorithm combined with the alternating direction multiplier method. The calculation results demonstrate that the model constructed in this paper can effectively address the uncertainty risk of upper level source loads

while achieving a reasonable allocation of alliance benefits and reduction of total community costs

as well as coordinating and optimizing the operation of all parties involved.

关键词

Keywords

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