An efficient global technique for solving the network constrained static and dynamic economic dispatch problem

This paper presents a new approach for solving the economic load dispatch (ELD) problem with generator constraints and transmission losses. The constrained globalized Nelder-Mead algorithm is a newly proposed algorithm for solving economic dispatch problems with and without valve-point effects. Convex and nonconvex cost functions with equality and inequality constraints are difficult to optimize. To circumvent these problems, a robust global technique is desirable. In this paper, the constrained globalized Nelder--Mead algorithm is proposed to optimize the ELD problem globally using variance variable probability. To validate the proficiency of the proposed approach, statistical studies have been accomplished for different test systems of static economic dispatch including 3-unit convex and nonconvex systems without losses, a 6-unit convex system with losses, 13-unit nonconvex systems without losses, and a 20-unit nonconvex system without losses. The proposed model proficiency is verified by applying it to dynamic economic dispatch for test systems including a 3-unit convex system with no losses and a 5-unit nonconvex system with losses. Comparison of the proposed algorithm with other optimization algorithms reported in the literature shows that the proposed algorithm is quite robust. The proposed algorithm has improved results from 0.0001% to 4.44% in different case studies.