Research On Environmental Economic Dispatch Of Multi-fuel Cogeneration Based On Improved Multi-objective Differential Evolution Algorith

The conventional thermal power units in the electricity production process lose a lot of heat,leading to a low energy conversion efficiency and releasing a lot of pollutant gases.In contrast,the combined heat and power(CHP)plant not only decreases environmental pollution while maintaining coal consumption,but also provides heat and electricity at the same time,with high energy conversion efficiency.With the advancement of the "carbon peaking and carbon neutrality goals.",it is of great theoretical importance to investigate the application of the combined heat and power(CHP)in power systems.In this paper,the core studies are as follows.(1)We propose an Oppositional Mutual Learning Strategy-based Improved Differential Evolutionary Algorithm(OMLIDE)for the traditional power system with complex economic load dispatch(ELD)problems.The population initialization conducted by using the oppositional mutual learning strategy to enlarge the search space and improve the probability of searching for the optimal solution;Two mutation schemes are developed and combined,which contribute to the convergence and diversity of the population to be balanced.In addition,an adaptive adjustment parameter strategy is designed to balance the exploration and exploitation performance and improve the robustness of the algorithm.And the superiority of the improved algorithm is verified by five economic dispatch cases considering valve point effects or multi-fuel options.(2)A multi-objective Jellyfish Search-based Hybrid Differential Evolution algorithm(MOJSHDE)is proposed and applied to the traditional environmental economic dispatch problem.The algorithm integrates the Jellyfish Search algorithm with powerful local exploitation performance and the Differential Evolution algorithm with stable global search performance,while introducing an improved parameter adjustment strategy.Finally,it is applied to four combined economic emission dispatch(CEED)cases,and the simulated results show that the algorithm has good comprehensive performance.(3)A multi-objective improved differential evolution algorithm(IMODE)for solving the combined heat and power(CHP)environment economic dispatch problem is proposed.The following improvements are proposed: A hybrid mutation strategy is designed in the mutation operation to satisfy the performance requirements of different stages;The senior stage of the GSK algorithm is integrated into the crossover operation to enhance the diversity of the population in the evolution process;The improved crowding distance is introduced in the selection operation in order to accurately describe the intensity among individuals in multi-objective optimization.Then,the IMODE algorithm is implemented for four different combined heat and power economic emission dispatch(CHPEED)cases,and the improved algorithm in this paper provides the dispatch solution with the optimal generation cost and the lowest pollution emission compared to other algorithms.