A graph theory-based optimal planning method for energy supply networks in an integrated energy system

The integrated energy system (IES) is a multi-energy internet carrier with high efficiency, and environmentally friendly that has recently been the focus of much attention. Furthermore, graph theory has a superior solving ability to optimize quickly and effectively a topology programming problem for complex networks. The widely focused concern of graph theory is more proactive consideration of the potential complex topology of network optimization of energy supply network (ESN) at the planning stage of IES. To this end, this paper proposed a novel graph theory-based optimizing approach for solving the ESN configuration, which is called the layering and pruning method (L & PM) in this paper. First, a shortcoming of the minimum spanning tree (MST) to solve the planning problem of ESN is given in detail with an elaborate analysis. After that, the L & PM are designed with topological and economic analyses of local topologies, power flows, material consumption, etc., of pipelines of ESN, which can optimize the overall topology and pipeline capacities of ESN simultaneously, and avoid the problem that only optimizes the total length of ESN by MST. In addition, a two-stage planning model of IES considering ESN is formulated. Finally, via a real-world IES in South China, compared to the Prim algorithm (MST), the results of the case studies showed the developed L & PM's advantages significantly in improving the overall planning scale and economy of IES and satisfy and reliability of the system, which verifies prominently the superiority, effectiveness, and feasibility of the proposed L & PM.