A Hybrid Sine Cosine Algorithm with SQP for Solving Convex and Nonconvex Economic Dispatch Problem | [Mehran University Research Journal of Engineering and Technology • 2020]

Author(s):

1. MUHAMMAD IMRAN BABAR: Department of Electrical Engineering, University of Engineering and Technology,Taxila,Pakistan

2. AFTAB AHMAD: Department of Electrical Engineering, University of Engineering and Technology,Taxila,Pakistan

3. SAQIB FAYYAZ: Department of Electrical Engineering, University of Engineering and Technology,Taxila,Pakistan

Abstract:

ED (Economic Dispatch) is one of the major problems of power system operation. The aim of ED problem is the efficient utilization of resources to provide the demanded power while generating cost turns out to be minimum and no constraint is violated either equality or inequality. The ED optimization problem, is necessary because of limited resources, high fuel cost and ever growing demand of power. This paper presents solution to convex and nonconvex ED problems using a novel HSCA (Hybrid Sine Cosine Algorithm). The proposed HSCA technique enhances the exploration capabilities of SCA (Sine Cosine Algorithm) by equipping it with mutation and crossover operators from DE(Differential Evolution) algorithm. DE algorithm introduces diversity in the operation of SCA enabling it to avoid local minima and premature convergence. To ensure precise and accurate optimum tracking results are finally refined by SQP (Sequential Quadratic Programming) algorithm. The high feasibility and applicability of proposed technique has been tested and validated on 13, 15 and 40 IEEE Standard test systems considering transmission losses and prohibited operating zones in “MATLAB 2014a”. Comparisons of results obtained from HSCA indicate significant improvement in convergence time and fuel cost as compared to the techniques reported in the literature.

Page(s): 31-46

DOI: 10.22581/muet1982.2001.04

Published: Journal: Mehran University Research Journal of Engineering and Technology, Volume: 39, Issue: 1, Year: 2020

Keywords:

Population Based Algorithm , Sine Cosine Algorithm

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