Multi factor optimization method for comprehensive energy system based on multi-dimensional mixed energy storage

In this paper, a multivariate hybrid energy storage system optimization method is proposed to solve the problems of high renewable energy abandonment rate and insufficient optimization of combined cooling, heating and power (CCHP) system in the integrated energy system of the park. A day-ahead and intraday dual time scale optimization model of the integrated energy system in the park is established. On the basis of the day-ahead model, multiple factors such as energy purchase cost, CCHP revenue and new energy revenue are considered, and the improved particle swarm algorithm is used to solve the optimization with multi-constraint objectives. And the intraday optimization model is corrected by taking the day-ahead operation scheme as a reference to the day-ahead optimization results. The final results show that the economic performance of multiple energy storage is better than that of single energy storage configuration scheme, and the improved algorithm effectively improves the system operation efficiency on the basis of economy and environmental protection, which provides a basis for the subsequent energy supply system planning.