Optimal Scheduling of Integrated Energy System Based on NSGA-II-MOABC

Abstract

In order to solve the multidimensional energy flow optimal scheduling problem in integrated energy system (IES), this paper proposes an IES optimal scheduling method based on NSGA-II-MOABC. Firstly, an IES topology framework including electric and heat subsystems is constructed. Secondly, for the different subsystems in the system, the dynamic electricity price control strategy and the hierarchical energy supply control strategy based on the energy market are formulated to achieve the collaborative control of the overall system. Then the non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective artificial bee colony algorithm (MOABC) are improved by sorting and classifying the population crowding. A new algorithm named NSGA-II-MOABC is proposed and applied to the model of IES. Finally, the convergence of the algorithm is verified by simulation of example, and the optimal results of the model are analyzed from the energy efficiency and economic revenue. The result shows that multi-strategy collaborative control used in this paper can improve system energy efficiency, and optimal scheduling method based on NSGA-II-MOABC can raise system economic benefits from multiple perspectives.