基于主从博弈的含碳捕集与热电联产综合能源系统优化运行

李畸勇; 郑一飞; 刘斌; 周小松; 皮本全

李畸勇,郑一飞,刘斌,周小松,皮本全.基于主从博弈的含碳捕集与热电联产综合能源系统优化运行[J].电测与仪表,2024,61(6):10-19.
LI Jiyong,ZHENG YIfei,LIU Bin,ZHOU Xiaosong,PI Benquan.Optimal operation of an integrated energy system with carbon capture system and combined heating and power based on a master-slave game[J].Electrical Measurement & Instrumentation,2024,61(6):10-19.

基于主从博弈的含碳捕集与热电联产综合能源系统优化运行

Optimal operation of an integrated energy system with carbon capture system and combined heating and power based on a master-slave game

DOI：10.19753/j.issn1001-1390.2024.06.002

中文关键词: 区域综合能源系统 Stackelberg博弈碳捕集系统协调优化郊狼算法

英文关键词:regional integrated energy system, Stackelberg game, carbon capture system, coordination optimization, coyote optimization algorithm

基金项目:国家自然科学基金资助项目（ 61863003）

作者中文名	作者英文名	单位
李畸勇	LI Jiyong	广西大学电气工程学院
郑一飞	ZHENG YIfei	广西大学电气工程学院
刘斌	LIU Bin	广西大学电气工程学院
周小松	ZHOU Xiaosong	广西大学电气工程学院
皮本全	PI Benquan	广西大学电气工程学院

摘要点击次数: 554

中文摘要:

为了合理地分配综合能源系统中各主体之间的利益，促进能源低碳化，文中基于主从博弈框架建立了含碳捕集系统的综合能源系统优化调度模型，降低了热电联产机组的碳排放量和系统的运营成本。文章构建碳捕集、电转气和热电联产的联合运行模型，在考虑综合需求响应的基础上，建立综合能源系统各主体的收益模型；构建一主多从的Stackelberg博弈模型，由于构建的优化模型具有高维、非线性非凸的特点，数值方法难以求解，传统启发式算法容易陷入局部最优且收敛速度较慢，因此提出一种新型天牛郊狼算法结合二次规划的分布式算法。以北方某工业园区为算例进行验证，分析结果表明，文中提出的模型及求解算法与传统模型相比，有效地降低了综合能源系统的运行成本和碳排放量，提高了可再生能源的消纳能力。

英文摘要:

In order to reasonably allocate the benefits among the stakeholders in the integrated energy system and promote the decarbonization of energy, this paper develops an optimal scheduling model of integrated energy system with carbon capture systems based on master-slave game framework, which reduces carbon emissions from combined heating and power (CHP) units and system operating costs. A joint operation model of carbon capture system (CCS), power-to-gas (P2G) and CHP is built, and a revenue model for each subject of the integrated energy system on the basis of considering comprehensive demand response is established. The Stackelberg game model with one master and multiple slaves is built. Due to the characteristics of high-dimensional, nonlinear and non-convex optimization, the numerical method is difficult to solve and the traditional heuristic algorithm is easy to fall into the local optimum and the convergence speed is slow. Therefore, a novel distributed algorithm combined the improved coyote algorithm with quadratic programming is proposed. An industrial park in the northern China is taken as an example to verify, and the analysis results show that the model and the algorithm proposed in this paper effectively reduce the operating costs and carbon emissions of the integrated energy system and enhance the accommodation capacity of renewable energy compared to the traditional model.

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