Multi-Objective Golden Flower Optimization Algorithm for Sustainable Reconfiguration of Power Distribution Network with Decentralized Generation

This paper provides a meta-heuristic hybridized version called multi-objective golden flower pollination algorithm (MOGFPA) as the best method for choosing optimal reconfiguration distribution networks (DNs) in order to reduce power losses (PLs). Aside from PLs, another parameter is considered: load balance index (LBI). The expression LBI stated using real and reactive indices. It makes distributed generation (DG) placement DN routing of (MO) problem have PLs main parameters that need be optimized. For purpose, MOGFPA proposed this paper. consists search (GS) tangent flight with Pareto only needs few tuning parameters. Therefore, it simple alter these reach values compared other existing methodologies. Its performance predicted different case studies on multiple test bus systems, namely IEEE systems such 33, 69, 119, Indian 52 bus. Through simulation outcomes, computes optimum DG units reconfigures DNs aim minimal LBI. Furthermore, state-of-the-art technology comparing convergence charts provide outputs less time, minimum iterations.