A Comparative Study on Different Optimization Algorithms for Solving Economic Dispatch Problem

Abstract

Economic dispatch is one of the mathematical optimization problems in power system operation and planning. It aims to find the most efficient output for generating units that meets the demand of the load at the lowest possible cost while satisfy all operational constraints. This paper examines numerous methods to address the economic dispatch problem, including deterministic approaches like the Lagrange multiplier method, metaheuristic optimization algorithms such as the Genetic Algorithm, the Firefly Algorithm, the Harris-Hawks optimization algorithm, and their hybridizations. The study also utilizes PowerWorld Simulator, a software package that solves economic dispatch problems using sequential linear programming. Two different case studies have been conducted on IEEE 5-bus and 30-bus test systems for demonstrating the effectiveness of the proposed algorithms. The results of various case studies showed that the deterministic methods are the most effective for solving the economic dispatch problem. It was also shown that the hybrid algorithms, which combine the strengths of different optimization techniques, can achieve a significant enhancement in total cost compared to the conventional metaheuristic methods.