A Pareto Strategy based on Multi-Objective for Optimal Placement of Distributed Generation Considering Voltage Stability

This study focuses on developing a multi-objective framework to seek out the optimal Distributed Generations (DGs) placement and sizing in large scale distribution networks. Renewable energy resources like wind turbine (WT), photovoltaic (PV) are employed as resources of Distributed Generation (DG). The well known and Non-dominated Sorting Genetic (NSGA-III) Algorithm is implemented to handle various objective functions such as active power losses, voltage deviation and voltage stability index. The proposed method is tested on standard IEEE 118-bus radial distribution networks. The proposed algorithm is used a range of non-dominant Pareto-optimal solutions that are stored in the external archive and then the ‘best’ compromise solution is identified by fuzzy sets technique. The simulation results show that the proposed methodology ready to provide well distributed Pareto optimum solutions for the multi-objective optimal power flow problem. Furthermore, in order to validate the obtained results Multi-objective Dragonfly (MODA) algorithm is performed also and the simulation results of two algorithms are compared with each other