Multiobjective optimization for frequency support using electric vehicles: An aggregator-based hierarchical control mechanism

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Abstract

In the last few years, there has been an exponential increase in the penetration of electric vehicles (EVs) due to their eco-friendly nature, and ability to support bidirectional energy exchanges with the smart grid. Besides serving transportation needs and reducing the carbon footprints in the environment, EVs are widely used for instantaneous grid frequency support. However, the existing research proposals have concentrated majorly on unidirectional vehicle-to-grid (V2G) support using fleet of EVs, which in turn leads to reduced frequency regulation and reserve capacity of participating EVs. Motivated from these facts, in this paper, an “aggregator-based hierarchical control mechanism” for secondary frequency regulation (SFR) using a fleet of EVs has been presented. In the proposed solution, EVs' scheduling problem has been formulated to provide optimal SFR, while satisfying EVs' energy demands under battery degradation constraints. This multiobjective primal problem (Mo-PP) under multiple constraints is solved using an approximation approach. This task is achieved by decomposing the complex Mo-PP into four different subproblems (SPs), corresponding to controllers deployed at different layers. The designed SPs are then iteratively solved using interior point method. In summary, the tradeoff between SFR and EV's bidirectional energy demands has been investigated in this paper. Moreover, battery degradation issues induced due to frequent charging and discharging cycles of EVs are also explored. Optimal dispatch of regulation signals among the aggregators and charging stations also takes into account the advantages of conventional droop mechanism. Lastly, widely accepted Pennsylvania-New Jersey-Maryland and ERCOT regulation data have been used to perform extensive simulations. The results obtained demonstrate that the proposed scheme achieves 22.6% and 6.8% better performance in comparison with the existing schemes based on colored petri net and proportional integral derivative controller, respectively.

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Kaur, K., Singh, M., & Kumar, N. (2019). Multiobjective optimization for frequency support using electric vehicles: An aggregator-based hierarchical control mechanism. IEEE Systems Journal, 13(1), 771–782. https://doi.org/10.1109/JSYST.2017.2771948

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