An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing - Norainon, Mohamed; Dahaman, Ishak (Springer Science and Business Media Deutschland GmbH, 2022)
In this paper, an improved Non-dominated Sorting Genetic Algorithm III (NSGA III) is proposed in determining the location and sizing of multi-DGs. NSGA III is the new variant of pareto-based evolutionary algorithm by using reference point approach. Grey Relational Analysis (GRA) is used to determine the best compromise among the non-dominated pareto solutions. Considering that minimization of power losses and improvement of voltage profile as the objectives, the proposed method is applied to IEEE 14 bus system. The obtained results are comprehensively compared with other published works. From this comparative analysis, it is proved that the proposed algorithm is very effective in reducing the line losses and improving the voltage profile.