Particle Swarm Optimization for Risk-Aware Distributed Generation Planning in Distribution Networks

ton trieu

doi:10.31258/ijeepse.9.2.94-107

ton trieu Thu Duc College of Technology, Ho Chi Minh, Vietnam

DOI: https://doi.org/10.31258/ijeepse.9.2.94-107

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Keywords: Distributed generation, Distribution networks, Multi-objective optimization, Reverse power flow, Voltage stability.

Abstract

High penetration of distributed generation (DG) improves distribution network performance but may increase voltage rise and reverse power flow, threatening secure operation. This paper proposes a Particle Swarm Optimization (PSO)-based DG planning framework that simultaneously minimizes active power loss, mitigates voltage risk, suppresses reverse power flow, and maximizes DG penetration. A normalized multi-objective function integrates these criteria into a unified optimization model, while penalty functions enforce network operating constraints. The proposed method is validated on the 33-bus and 69-bus radial distribution systems and compared with GSA, MVMO-SH, and conventional PSO. For the 33-bus system, the proposed approach reduces active power loss by 36.47%, increases the minimum bus voltage from 0.913 p.u. to 0.964 p.u., and limits reverse power flow to 13.2 kW. For the 69-bus system, it achieves a 61.92% reduction in power loss, improves the minimum voltage from 0.909 p.u. to 0.972 p.u., and decreases reverse power flow to 18.9 kW while providing the highest DG penetration among the compared methods. The results demonstrate that explicitly considering voltage risk and reverse power flow enables more effective and reliable DG planning for active distribution networks.

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