ABSTRACT
A novel flower pollination algorithm differential evolution (FPA-DE – hybrid approach) is used to solve the multiobjective optimal power flow (MOOPF) problem. The objectives with innate differences such as total fuel cost, active power losses, and the emission are selected. Two different test systems IEEE 30 and 57 have been considered to evaluate the performance of the proposed algorithm for handling the optimal power flow (OPF) problems from various standpoints. The FPA-DE approach is very robust and powerful for answering the OPF problem in all case studies. As a case in point, it managed to reduce the total generation cost by 7.95%, emission by 47.12%, and loss by 61.02% and improve the stability index by 18.76%, which is quite a cogent achievement. Also, an exhaustive comparative study has been made to assess the best obtained results thus far in which the FPA-DE algorithm turned out to be the best approach.
