Two-stage Economic Dispatch Optimization for Integrated Energy System Using Improved Brain Storm Optimization Algorithm

In this paper, a two-stage economic dispatch operation model of integrated energy system is constructed. Firstly, the day-ahead economic dispatching model is established, which comprehensively considers the operation and maintenance cost, electricity purchase cost, heat purchase cost, fuel cost and energy storage cost. Secondly, on the basis of day-ahead dispatching model, a real-time dispatching optimization model is built by modifying the running state of each micro-source unit. Furthermore, in order to solve the above optimization model, a brain storm optimization(BSO) algorithm based on chaotic crisscross mutation is proposed, that is, the Gaussian mutation in BSO is replaced by chaotic crisscross mutation to enhance the optimization performance and computational efficiency by maintaining the population diversity. Finally, the constructed dispatching model and the proposed CCSO-BSO are validated by a real-world case, and the relative results show that two-stage dispatching optimization model can effectively improve the renewable energy utilization and reduce the system operation cost, it may be a promising alternative for economic operation of integrated energy system.