Multi-objective rearrangement of unbalanced distribution network by considering uncertainty of loads and distributed generation by NSGA-II algorithm

Abstract

One of the cases that is often ignored in most distribution system researches, including in the distribution network rearrangement problem, is the uncertainty in the amount of load consumed and the power output of distributed generation resources. Thus, the certain methods that are used do not provide a complete and comprehensive view of the real state of the network. Similarly, in most studies, the single-phase nature of loads in distribution networks and their unbalanced nature is neglected and the results will be erroneous by assuming that loads are balanced. In this paper, both network rearrangement strategies and determining the optimal location of distributed generation in an unbalanced distribution network with the aim of simultaneously minimizing losses and improving network voltage profiles are studied using the multi-objective genetic optimization method (NSGA-II). Also, in order to consider the uncertainty of network loads and the amount of output power of distributed generation sources, a method which the stability of the solutions will be added to the two previous objectives is used. Finally, the problem is solved by generating Pareto front for different load scenarios and distributed generation and selecting the most stable solution from the set of solutions available on the Pareto front.