Using the NSGA-II Algorithm for Optimal Allocation of Shunt Capacitors in Radial Distribution Networks: A Case Study
Abstract
The optimal placement of capacitors in radial distribution networks plays a significant role in reducing losses and improving the voltage profile. A multi-objective optimization technique was used, specifically the Non-Dominated Sorting Genetic Algorithm (NSGA-II), to determine the optimal location and size (capacity) of fixed shunt capacitors in radial distribution networks with the aim of minimizing the total cost represented by losses and capacitor costs, while also improving the voltage profile simultaneously.
To verify the validity and effectiveness of the proposed algorithm, we developed a program in the MATLAB R2018a environment for the proposed NSGA-II algorithm, as well as a second program for load flow, and integrated both together. The proposed algorithm was tested on the standard IEEE-33 Bus radial distribution network, and the results demonstrated the effectiveness and efficiency of the algorithm in obtaining a diverse set of solutions for the posed problem, known as Pareto Front solutions, from which system designers can select the optimal solution that fits the characteristics of the studied electrical system.
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