A Coordinated Model for Multiple Electric Vehicle Aggregators to Grid Considering Imbalanced Liability Trading

In the interaction between electric vehicle (EV) and grid, research on the coordinated optimization of different EV aggregators to reduce the adverse effect of EVs uncertainty is of great significance. This paper commits to formulating an imbalanced liability trading cooperation platform among multiple EV aggregators in real-time (RT) market. First, we propose a joint bidding model of multiple EV aggregators in RT market from the individual perspective. Each aggregator optimizes its internal bidding strategy and external imbalanced liability trading simultaneously. Next, considering the self-interest of each EV aggregator, the cooperative model is built based on general Nash bargaining (GNB) theory. To promote EV aggregators to trade but avoid over-dependence, each EV aggregator’s bargaining power is formulated by both individual trading quantity and trading dependence. Then, we decompose the model into two subproblems and introduce the neurodynamic-based algorithm for distributed solving. Finally, numerical results show that the proposed coordinated model can reduce the adverse effect of EVs’ uncertainties on grid power balance to some extent, and realize cost saving or even profit earning for aggregators.