Research on Two-stage Optimization Approach of Community Integrated Energy System Considering Load Supply Reliability

Abstract

The community integrated energy system (CIES) can significantly improve energy utilization and promote the consumption of renewable energy through multi-energy coupling complementary and collaborative optimization scheduling. It has become a new energy utilization realization approach for users to meet multi-energy supply and demand. Taking a community in Xiong’an New District, Hebei province as the research object, this paper designed a two-stage optimization approach for the CIES that takes into account the reliability of load supply. The first stage is based on the non-dominated sorting genetic algorithm II(NSGA-II) with elite preservation strategy to optimize the equipment type and capacity of the community energy station. It is a multi-objective planning optimization problem, and its purpose is to achieve the coordinated optimization of economic costs and environmental costs. The second stage is an operation optimization problem. As for the multiple Pareto frontier solutions obtained in the previous planning stage, the mixed integer linear programming (MILP) was used to separately optimize the operation cost and load supply reliability indicators of each planning scheme, and the result is used as an important reference for determining the best planning scheme. Case studies show that the designed planning approach can effectively reduce the system operating cost and guarantee the reliability of load supply, and it is more practical for instructing the CIES planning.

Keywords

• community integrated energy system
• planning optimization
• load supply reliability
• non-dominated sorting genetic algorithm ii (nsga-ii)
• mixed integer linear programming