Hierarchical Optimization Scheduling Method for Integrated Community Energy Systems

Abstract

With the widespread of combined heat and power plants (CHP) and micro turbines (MT) in the distribution network, electricity, heat and natural gas are coupled tightly in community areas. In order to determine the optimal day-ahead scheduling schemes of the integrated community energy system (ICES), a hierarchical optimization method is proposed, where the reconfigurable capability of an electric distribution network is considered. The proposed hierarchical framework designs a client---server structure to handle the opacity of information among energy service providers (ESP). The client level that includes heat, electricity and natural gas is modeled by energy center (EC). Taking into account the demand-side response (DR) of alternative energy, the connected power between clients, the natural gas and electric distribution network is determined with the objectives of lower energy consumption and higher energy efficiency. The natural gas and electric distribution network are regarded as two servers. In order to minimize the loss, the distribution system operator (DSO) utilizes remotely controlled switches (RCSs) to reconfigure hourly the electric distribution network. A hybrid optimization method is utilized to solve the model, on the basis of an improved particle swarm algorithm and a nonlinear interior point method (IPM). This paper demonstrates the regional integrated energy system is able to operate economically and efficiently .