Dynamic Cluster Optimization For Heat-electricity Coupled Integrated Energy System

With the large-scale development of distributed energy resources and combined heat and power(CHP)units,an integrated energy system with heat-electricity coupled has been formed to realize the comprehensive utilization of solar energy,electrical energy,and thermal energy at the community/park/commercial district level.Driven by market factors,the business model of the integrated energy system is diversified.The participation of multiple entities and the access of a large number of nodes have made it difficult for traditional centralized regulation to meet demand.Distributed optimization with multiple agents has become an important solution for the optimization and regulation of integrated energy systems.According to the basic principles of local consumption of renewable energy and efficient use of thermal energy,by dividing the network into several sub-regions,each sub-region constitutes a cluster,which can give full play to the autonomous characteristics of the cluster and realize the collaborative optimization between clusters.To this end,this paper uses the idea of cluster partition to realize the distributed optimization of the integrated energy system,and conducts research from two aspects of the cluster partition index system and effective algorithms to propose a cluster partition method suitable for the integrated energy system with heat-electricity coupled.Firstly,a cluster partition index system comprehensively considering the structural and functional properties is proposed.The modular index that takes into account the characteristics of power grid and heat network is used on the structural property to describe the connection strength between different network nodes,so as to ensure that the clusters formed on the two levels of power grid and heat network have tight connection within the cluster and loose connection between the clusters.The functional property focuses on the source-load matching level,and the indexes of supply-demand matching degree and heat-electricity coupling degree are introduced to reflect the balance degree between the internal supply and actual demand as well as source-side coupling output and actual consumption in a single energy network cluster.By taking advantage of the self-adjustment capability within the cluster,it promotes the local consumption and utilization of distributed energy and reduces the cross-cluster flow of energy.Secondly,a cluster partition method based on Louvain algorithm is proposed.In order to form a reasonable cluster partition structure at different levels of the power grid and heat network,this paper considers the impact of the coupled output of CHP units on the cluster partition.Based on the cluster partition index system,the optimization objectives at the two levels of power grid and heat network are designed as the basis for cluster partitioning.Thus,an electricity-heat cluster centered on combined heat and power is formed by Louvain community detection algorithm.Finally,the effectiveness of the proposed method is verified through the case study.The results show that the proposed partition method can automatically obtain stable and reasonable cluster structure.In addition,the cluster has strong structural strength and sufficient internal adjustment capabilities,which can effectively avoid the additional costs caused by the power flow across clusters and realize the economic operation of the system.