Research on Distribution Network Planning Based on Adaptive Weight Factor based White Shark Optimization

The planning of power grid is significant for the development of the power system. A distribution network has progressed from the individual to the multi-source multidirectional network, enhancing the operational and planning complexity. However, due to the non-linear nature of most of the loads, there is significant demand for the reactive power in the distribution network. Hence, this research proposes the Adaptive Weight Factor based White Shark Optimization (AWF-WSO) approach for the optimal planning of the distributed networks. Through effectively adapting the weight factor, the WSO considers the cleansing high-quality solutions, leads to more accurate and reliable planning results. For load estimations, a Backward Forward Sweep (BFS) approach is performed as the experimental setup to perform network effectiveness, focussing a power controlling constraints. The experimental results shows that the proposed AWF-WSO approach attains the minimum Iterative algebra at convergence of 28, fitness value of 1.05 and Computational time of 118s respectively as compared to the existing method like WSO.