A Mutually Beneficial Operation Framework for Virtual Power Plants and Electric Vehicle Charging Stations
Han Wang, Youwei Jia, Mengge Shi, Chun Sing Lai, Kang Li
Abstract
Virtual power plants (VPPs) and electric vehicle (EV) charging stations (CSs) have been attracting much attention in recent years. However, existing research rarely concerns the cooperation between VPPs and CSs that are managed by different stakeholders. To facilitate the cooperation between VPPs and CSs, this work proposes a cooperative operation framework for a multi-stakeholder VPP-CSs system. In the proposed cooperative framework, day-ahead offering and real-time balancing models are developed to maximize the total benefit of the VPP-CSs system. To support a more flexible operation of the VPP-CSs system with EV energy flexibility, an EV user incentive program is proposed for acquiring EV battery access rights. The conflicting interests of different stakeholders are addressed by a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> -value cost allocation method. To alleviate the computational burden in calculating the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> -values, a maximum right cost estimation approach is proposed. Case studies confirm that the proposed methods can provide superior performance by increasing 4.6% of VPP profit, increasing 20.7% of CS profit, reducing 16.3% of EV user charging fees, and achieving 99.2% of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> -value estimation accuracy.