Two stage model of capacity planning and operation optimization for integrated energy system

Abstract

In this paper, the capacity planning and operation optimization model for integrated energy system is established. Taking the lowest economic cost of integrated energy system in the whole life cycle as the optimization goal and considering the constraints of material and energy balance, the optimal hourly scheduling optimization of equipment power in typical weeks is realized; Based on the operation scheduling, the classical particle swarm optimization algorithm is selected as the method to solve the double-layer model, the results are analyzed, and the expectation of the lowest economic cost is returned to the upper genetic algorithm to find the optimal capacity allocation, so as to realize the two-stage integrated stochastic optimization strategy.