A novel multi-objective salp swarm optimization algorithm is proposed in this paper, which is combined with equality constraint modification technology and feasible solution dominant constraint processing technology to solve the highly constrained environmental economic optimization dispatch problem of power system. A Gauss sampling strategy and a mutation operator are adopted to enhance the optimization performance of the suggested algorithm; a non-dominated sorting method based on improved dynamic crowding distance is adopted to obtain a uniformly distributed Pareto-optimal front; a fuzzy set theory is applied to provide the best compromise solution for decision makers. Simulations are carried out on the IEEE 30-bus 6-unit standard test system and compared with other optimization algorithms. The results show that the proposed algorithm has better optimization effect in solving environmental economic dispatch problem of power system.
