Solution of economic dispatch problem for wind-thermal power systems by a modified hybrid optimization method

Abstract

Economic Dispatch Problem (EDP) is a complex, constrained and non-linear optimization problem. In the EDP, it is aimed to minimize the system fuel cost between minimum and maximum limits of the active power buses. In this study, a modified hybrid Gravitational Search- Teaching-Learning Based Optimization Algorithm (MHGT), a quick, efficient and reliable method is proposed by combining standard Gravitational Search Algorithm (GSA) and Teaching-Learning Based Optimization (TLBO). The proposed MHGT method was developed by modifying the global search superiority in GSA and powerful local search specialty in TLBO for the solution of constrained optimization problem. The MHGT was tested experimentally by well-known and mostly used ten benchmark function in the literature. The proposed method was first implemented on a 6 bus wind-thermal power system for 400, 450 and 500 MW powers. Then, it was implemented on Turkey 19 bus wind-thermal power system according to different ratios of the installed power as 25, 27.5 and 30 percent to solve the EDP problem. The obtained results were compared with the results of other studies. From the results, it is seen that the proposed MHGT method finds the solution in a short execution time and less fuel cost with more reliably and more efficiently in terms of both fuel cost and execution time.