1 research outputs found
Multi-objective Optimal Reactive Power Dispatch of Power Systems by Combining Classification Based Multi-objective Evolutionary Algorithm and Integrated Decision Making
For the purpose of addressing the multi-objective optimal reactive power
dispatch (MORPD) problem, a two-step approach is proposed in this paper. First
of all, to ensure the economy and security of the power system, the MORPD model
aiming to minimize active power loss and voltage deviation is formulated. And
then the two-step approach integrating decision-making into optimization is
proposed to solve the model. Specifically speaking, the first step aims to seek
the Pareto optimal solutions (POSs) with good distribution by using a
multi-objective optimization (MOO) algorithm named classification and Pareto
domination based multi-objective evolutionary algorithm (CPSMOEA). Furthermore,
the reference Pareto-optimal front is generated to validate the Pareto front
obtained using CPSMOEA; in the second step, integrated decision-making by
combining fuzzy c-means algorithm (FCM) with grey relation projection method
(GRP) aims to extract the best compromise solutions which reflect the
preferences of decision-makers from the POSs. Based on the test results on the
IEEE 30-bus and IEEE 118-bus test systems, it is demonstrated that the proposed
approach not only manages to address the MORPD issue but also outperforms other
commonly-used MOO algorithms including multi-objective particle swarm
optimization (MOPSO), preference-inspired coevolutionary algorithm (PICEAg) and
the third evolution step of generalized differential evolution (GDE3).Comment: Accepted by IEEE Acces