A novel multi-objective framework for harmonic power market including plug-in electric vehicles as harmonic compensators using a new hybrid gray wolf-whale-differential evolution optimization

Abstract

Plug-in electric vehicles are capable of providing harmonic reference currents to the smart micro-grid in order to approximately neutralize the undesirable effects of the harmonic sources. This paper proposes a holistic multi-objective optimization framework for plug-in electric vehicles' involvement in accurately clearing the harmonic power market in a micro-grid. The proposed multi-objective framework is capable of concurrently optimizing contradict objectives, comprising total distortion payment function of the harmonic compensators, and mean of total harmonic distortion while satisfying the constraints associated with the network, vehicles, and market price. The payment function includes availability, loss, and loss of opportunity cost terms according to the harmonic capability curve of the plug-in electric vehicles and active power line conditioners. Moreover, this study proposes a novel hybrid algorithm consisting of the whale optimization, the gray wolf optimization, and the differential evolution algorithm for settling this new market framework. The best compromise solution is selected based on a particular preference among diverse Pareto optimal solutions on a fuzzy decision-making procedure basis. In order to illustrate the effectiveness of the proposed methodology and the outperformance of the plug-in electric vehicles compared with the active power line conditioners, the single-objective and the multi-objective harmonic power market under different circumstances are employed in this study.