A Hybrid Cross-Entropy Method and Local Neighborhood Search Method for Low-Carbon Economic Dispatch Problem of IES

In order to protect the environment and cope with climate change, in order to promote the coordinated development of economy and environment, carbon trading must be considered in the economic scheduling of the current energy system. In this paper, establish a carbon trading model considering the ladder of reward and punishment mechanism and an integrated energy system (IES) model considering the operating cost and carbon trading. Firstly, the IES is modeled. Since the objective function of economic scheduling considers the step carbon trading cost, it will lead to a series of characteristics of nonlinear, non-convex and non-smooth objective function. Secondly, in order to solve this problem, a hybrid method combining the cross entropy method (CEM) and the local neighborhood search method (LNSM) is proposed for optimization. Meanwhile, a series of random solution sequences that gradually converge in probability to nearoptimal solutions are built through the proposed CEM. This can enhance the exploration capability. Then, through the proposed LNSM is used for local search, it can quickly converge to the optimal solution. Finally, a set of simulations of CEM-LNSM are carried out to verify the effectiveness of the proposed strategy.