Decision-making in multi-objective DG planning for distribution system via Shannon’s entropy

Abstract

In the current paradigm, integration of distributed generation (DG) has become essential for ensuring the quality, reliability, and security of distribution network operations. Existing literature typically formulates multi-objective problems to quantify the techno-economic assessment of DG placement in a distribution system. Nevertheless, there is a notable lack of a suitable method to assign weight impartially to each objective for optimal decision-making. This paper introduces a novel technique for strategically placing DG units in the distribution network, employing weights calculated based on the importance level of various techno-economic objectives using Shannon’s entropy. The proposed approach has been applied to a 38-node test system to illustrate its efficacy. The numerical findings from four distinct case studies reveal that changes in the physical attributes of the system correspondingly influence the significance of objectives in determining the optimal placement and size of DG. The results show significant reductions in active and reactive power losses and total annualized operational costs, with maximum reductions of 48.17%, 33.30%, and 42.96%, respectively. The minimum voltage magnitude improves from 0.9252 pu in the base case to 0.9384, 0.9695, 0.9369, and 0.9348 for Cases 1, 2, 3, and 4, respectively. Moreover, a comparative statistical analysis underscores the superiority of the proposed method over prevailing weight allocation strategies by achieving a 3.59% reduction in annual expenditure, while maintaining competitive network performance metrics in addressing the multi-objective DG placement problem.