Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach

Distribution network operators and planners face a significant challenge in optimizing planning scheduling strategies to enhance distribution efficiency. Using improved particle swarm optimization (IPSO), this paper presents an effective method for improving system performance by concurrently deploying remote-controlled sectionalized switches, distributed generation (DG), optimal reconfiguration. The proposed problem’s main objectives are reduce switch costs, maximize reliability, power losses, voltage profiles. An analytical reliability evaluation is DG-enhanced reconfigurable systems, considering both switching-only repairs switching interruptions. problem formulated the form of mixed integer nonlinear programming problem, which known as NP-hard problem. To solve effectively while conventional (PSO) exploration exploitation capabilities, novel chaotic inertia weight crossover operation mechanism developed here. It demonstrated that IPSO can be applied single- multi-objective problems, where systems’ considered sequentially simultaneously. Furthermore, IPSO’s effectiveness validated evaluated against well-known state-of-the-art metaheuristic techniques IEEE 69-node systems.