A Multi-objective Shuffled Bat algorithm for optimal placement and sizing of multi distributed generations with different load models

• DG are considered for power system modeling using Current injection based load flow.
• A new Multi objective Shuffled Bat algorithm (MOShBAT) is proposed for planning of DGs.
• The prosed techniques is compared with NSGA-II and Improved Harmony search algorithm.
• MOShBAT is applied for various load models and results are presented.

In this paper a new and efficient hybrid multi-objective optimization algorithm is proposed for optimal placement and sizing of the Distributed generations (DGs) in radial distribution systems. A Multi-objective Shuffled Bat algorithm is proposed to evaluate the impact of DG placement and sizing for an optimal improvement of the distribution system with different load models. In this study, the ideal sizes and locations of DG units are found by considering the power losses, cost and voltage deviation as objective functions to minimize. Furthermore, the study is verified with voltage dependent load models like industrial, residential, commercial and mixed load models. The feasibility of the proposed technique is verified with the 33 bus distribution network and also the qualitative comparisons against a well-known technique, known as Non-dominated Sorting Genetic Algorithm II (NSGA-II) is done and results are presented.