Renewable Energy Following Strategy via Quantified Aggregated Heterogeneous Electric Vehicle Flexibility

The rapid expansion of renewable energy (RE) generation brings environmental and economic benefits. However, the mismatch of the RE generation pattern and load profile introduces the imbalance between energy supply and demand, posing challenges to modern smart grids. While RE generation is inherently less controllable, the emergence of controllable loads, particularly electric vehicles (EVs) with their flexible charging and discharging capabilities, offers a promising solution to dynamically adjust energy consumption to match RE availability. To this end, this paper proposes a RE following mechanism for EV aggregator (EVA), enabling coordinated charging and discharging of EVs. First, we mathematically quantify the aggregated flexibility of EVs using an affine transformation of convex polytopes. This approach improves computational efficiency and accuracy in aggregating individual heterogeneous EV flexibility with different parameters. Then, a RE following mechanism for the EVA is formulated, treating the quantified EV flexibility set as an operating envelope. Two RE following evaluation methods, namely, Euclidean norm and cosine similarity, are used to assess the RE following effectiveness. Finally, we propose a pricing strategy accommodating various charging and parking decisions of EVs based on a combined framework of time-of-use (TOU) pricing and intraday-block pricing (IBP), incentivizing EV participation in RE following. The numerical results show that the proposed RE following mechanism significantly improves RE utilization, leading to an average increase of 62.04% in the RE consumption ratio and a 13.35% boost in average profits compared to the other two cases without RE following strategies