A Multi-objective Shuffled Bat algorithm for optimal placement and sizing of DGs with load variations

A new hybrid Multi-objective Shuffled Bat optimization algorithm is proposed in this paper for Distributed generations (DGs) optimal placement and sizing. Multiple objectives like system power losses, cost of DG and system voltage profiles are considered to evaluate the impact of DG placement and sizing for an optimal development of the distribution system with load variations. Furthermore, the study is demonstrated with different % loading such as 80,100 and 120% of base load condition. The proposed technique is tested in 33 bus distribution network, and compared against Non-dominated Sorting Genetic Algorithm II (NSGA-II).

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