A multi-objective hybrid algorithm for feeder reconfiguration and planning of electrical distribution system - Kothuri Ramakrishna; Basavaraja Banakara (Engineering and Applied Science Research (EASR), 2019)
In this paper, a multi-objective Gravitational Search Algorithm (GSA) and Tabu search heuristic for feeder reconfiguration and planning of an electrical distribution system are proposed. In this strategy, the GSA has reduced the power losses and voltage deviations using relevant constraints. The optimal sizing of a distributed generator (DG) includes the best location with reduced electrical losses. The Gravitational Search Algorithm (GSA) hastens convergence with integration of a Tabu search heuristic. Then, the proposed multi-objective hybrid algorithm for planning an electrical distribution system is implemented on a MATLAB/Simulink platform. Its effectiveness is scrutinized by contrasting the results of the method under study with those of existing techniques such as ALO, LSA, CALMS and BBO-PSO. This comparison reveals the superiority of the proposed approach and affirms its potential to reduce power losses and voltage deviations.