Non-interactive approach to solve multi-objective optimal power flow problem

Abstract

The purpose of this research work is to solve the multi-objective optimal power flow (MO-OPF) problem using non-interactive approach. In this approach, the decision maker (DM) is not involved; however, the prior preference information is available to the DM. A satisficing function is offered to take care of the conflict between non-commensurable objectives, and the multi-objective problem is reformulated as a scalar optimization problem. This approach reduces the computation work involved for generating the Pareto front and for selecting the best satisficing solution. To attain the satisficing solutions, a hybrid optimization technique is applied, which integrates invasive weed optimization (IWO) with Powell’s pattern search (PPS) method. The IWO algorithm, utilized as the stochastic search technique, takes inspiration from the ability of weeds to adopt the environmental changes. Being a conjugate-based local search technique, the PPS method exhibits admirable exploitation search capability that further improves the solution provided by the IWO technique. The effectiveness of the proposed solution approach is confirmed by applying it to the three standard test systems, and the comparison is carried out with the well-established algorithms. Further, t test confirms the robustness of the proposed solution approach.