Multi-objective Optimal Planning of Distributed Generators Using Improved Grey Wolf Optimizer and Combined Power Loss sensitivity
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Over the past several years, there has been increased research and industry interest in finding ways to successfully integrate DG into distribution networks. The main reason for the recent surge in interest is the demonstrable benefits that DG bring to power systems, such as notable reductions in power loss and improved reliability. However, to take full advantage of these benefits, it is crucial to determine optimal allocation (i.e., size and location) of the DG in distribution networks. This thesis proposes and develops a hybrid approach to determining optimal sizing and location for Distributed Generator (DG) sources within a distribution system. The approach uses the CPLS factor along with the I-GWO algorithm. In the proposed method, CPLS is employed to find candidate locations for incorporating DG in a network, and the I-GWO algorithm is used to determine optimal sizes and locations for the DG from the CPLS-suggested candidate buses. The aim is to simultaneously minimize power loss, enhance voltage stability, and improve the voltage profile through the application of the novel multi-objective strategy. The algorithm proposed in this work is evaluated using IEEE-33 and IEEE-69 bus radial distribution networks, and three types of DG contributions are investigated in order to compare performance and efficiency metrics. The results indicate that the proposed hybrid method, when compared to other popular optimization techniques , effectively achieves optimal results with regard to its multi-objective functions.