A Compound Coordinated Optimal Operation Strategy of Day-Ahead-Rolling-Realtime in Integrated Energy System

Abstract

Aiming at the impact of the uncertainty of source load on the optimal scheduling in an integrated energy system (IES), in this paper, based on hybrid resolution modeling and hybrid instruction cycle scheduling technology, three time scales of day-ahead, intra-day rolling and real-time feedback optimization scheduling models are established, respectively, with the objectives of the economic optimal daily operation of the system, the minimum sum of the operation cost of energy purchase and wind curtailment penalty cost in the rolling control time domain, and the minimum adjustment amount of equipment output power. Then, the chaotic gravitational search algorithm (CGSA) is used to solve the problem, and the composite coordination optimization operation strategy of IES with mixed time scales based on CGSA is proposed. In the example, the comparison between the multi-timescale scheduling plan and the actual output, the comparison of the system scheduling results under different strategies and the comparison of different optimization algorithms show that the proposed optimization operation strategy is beneficial to optimize the energy flow distribution, reduce the system operation cost, improve the IES economy and optimization speed.