Implementation of improved grasshopper optimization algorithm to solve economic load dispatch problems

Abstract

The costs of different fuels are increasing gradually, for operation of power production units. Thus new optimization techniques are needed to tackle the complex problems of Economic Load Dispatch (ELD). Metaheuristics are very helpful for policy and decision makers in achieving the best results by minimizing the cost function. In this paper, we have updated the Grasshopper Optimization Algorithm (GOA) with a better initialization strategy to balance the search capability of GOA. The new algorithm is named as Improved Grasshopper Algorithm (IGOA). GOA is inspired by the swarms of grasshopper and mimics their biological behavior. Furthermore, IGOA is used to solve the ELD problems by tacking four case studies from literature. The objective in these problems is to find best decision variables for dispatching the available power with lowest cost, better efficiency and more reliability. To validate the efficiency of our proposed algorithm, we have tested it by solving 4 case studies of ELD with 1263MW, 600MW, 800MW and 2500MW demands respectively. IGOA is better in terms of convergence rate and quality of solutions obtained for the problems considered in literature for other metaheuristics.

Keywords

• constrained optimization,metaheuristics,improved grasshopper optimization algorithm (IGOA),economic load dispatch

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