Analysis shows improved voltage regulation and reduced power losses in radial distribution systems using algorithm techniques.
The strategic placement of capacitors in a distribution system is crucial for optimizing power quality,minimizing power losses, and ensuring voltage stability. Inadequate optimization of capacitorplacement can result in increased power losses, voltage fluctuations, and suboptimal systemperformance. This paper focuses on determining the optimal location and size of capacitors in radialdistribution systems to achieve minimal power loss and an improved voltage profile. Acomprehensive analysis of metaheuristic algorithm techniques, such as Genetic Algorithms (GA)and Particle Swarm Optimization, is conducted to address the capacitor placement problem, withthe goal of achieving the best solution. Detailed simulations using ETAP and MATLAB softwaredemonstrate that the proposed method significantly improves voltage regulation. Additionally, theeconomic benefits of capacitor placement, including reduced energy costs and enhanced systemreliability, are evaluated. Simulation studies on the outgoing feeders of the Nyellang substation(132/33/11 kV), particularly focusing on the Dewathang (33/11 kV) radial distribution network,show substantial reductions in power losses and notable improvements in voltage regulation. Forelectrical engineers, this research study provides a systematic and algorithm-driven methodology tomanage power losses through optimizing the capacitor placement in transmission lines, enablingbetter decision-making in distribution network planning. Utility providers can also make use ofthese findings to achieve systems performance efficiency, minimize repair and maintenance cost,and reduce energy losses that enhance system reliability. It also assesses infrastructure upgradationand new energy efficient technology integration. The proposed approach offers a cost-effective andpractical solution for optimizing the performance of distribution networks through optimal capacitorplacement.
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Zangpo et al. (2025) studied this question.
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