中国电机工程学报2025，Vol.45Issue(8)：3031-3045,中插15,16.DOI:10.13334/j.0258-8013.pcsee.240538
基于顶点子图分解合并原理的综合能源站设备选型及容量优化配置
Comprehensive Energy Station Equipment Selection and Capacity Optimization Allocation Based on Vertex Graph Decomposition and Merging Principle
摘要
Abstract
This paper presents an integrated energy station equipment selection and capacity optimization method based on vertex subgraph decomposition and merging principles.Using an energy hub(EH)modeling approach grounded in graph theory,the method captures multi-energy flow coupling relationships and distribution characteristics within stations.The vertex subgraph decomposition and merging principle abstracts equipment options as vertex subgraphs,transforming equipment selection into a subgraph combination and merging problem.By analyzing the multi-energy flow balance network topology,we establish collection-distribution nodes and an energy flow correlation matrix for equipment options.These options are incorporated into the model's constraints through a combination of 0-1 and integer variables.Considering both economic and energy-saving indicators,we develop a mixed-integer linear programming model encompassing equipment selection,capacity configuration,and operational constraints.Case simulations verify the method's effectiveness in achieving coordinated equipment selection and capacity planning.The proposed approach demonstrates rational and effective solutions for comprehensive energy station design,addressing equipment selection,structural construction,and capacity configuration from initial planning stages.关键词
综合能源站/容量优化配置/多能流平衡网络/顶点子图Key words
integrated energy station/capacity optimization allocation/multi-energy flow balancing network/vertex subgraph分类
能源科技引用本文复制引用
黄大为,陈柄运,于娜,杨冬锋,孔令国..基于顶点子图分解合并原理的综合能源站设备选型及容量优化配置[J].中国电机工程学报,2025,45(8):3031-3045,中插15,16.基金项目
国家重点研发计划项目(2018YFB1503100) （2018YFB1503100）
国家自然科学基金项目(51977031).National Key R&D Program of China(2018YFB1503100) （51977031）
Project Supported by National Natural Science Foundation of China(51977031). （51977031）
