Swarm based mean-variance mapping optimization for convex and non-convex economic dispatch problems

In power system generation, the economic dispatch (ED) is used to allocate the real power output of thermal generating units to meet the required load demand so as the total cost of thermal generating units is minimized. This paper proposes a swarm based mean-variance mapping optimization \((\hbox {MVMO}^{S})\) for solving the ED problems with convex and nonconvex objective functions. The proposed method is the extension of the original single particle mean-variance mapping optimization by initializing a set of particles. The special feature of the proposed method is a mapping function applied for the mutation based on the mean and variance of n-best population. The proposed \(\hbox {MVMO}^{S}\) is tested on various systems and the obtained results are compared to those from many other optimization methods in the literature. Test results have shown that the proposed method can obtain better solution quality than the other methods. Therefore, the proposed \(\hbox {MVMO}^{S}\) is a potential method for efficiently solving the convex and nonconvex ED problems in power systems.