Unlock the aggregated flexibility of electricity-hydrogen integrated virtual power plant for peak-regulation.

This paper proposes an aggregated flexibility estimation method considering the distributed electricity-hydrogen (H 2) interactions for virtual power plants (VPPs) to enhance the economic benefits from the peak-regulation market (PRM) while facilitating the accommodation of renewable generation. Firstly, various distributed energy resources (DERs) such as electric vehicles (EVs), air conditioning systems (ACs), and electricity-H 2 coupled hydrogen refueling stations (HRSs) are modeled as virtual storage (VS) with characterized charging/discharging response parameters. Besides, the temporal coupling power profile of VS can be abstracted as a polytope from the geometric perspective, and the aggregated high-dimensional flexibility region of VPP is formulated by the Minkowski sum for these polytopes. Furthermore, a day-ahead peak-regulation optimal scheduling model considering the conditional value at risk (CVaR) is developed for the electricity-H 2 integrated VPP participating the PRM, and the dimensionality of the aggregated polytope is reduced by the inscribed hyperbox approximation to provide a compact and concise scheduling region. Comparative studies have validated the aggregated power range and net income can be improved by 13.05% and 15.11% with the mechanism of electricity and hydrogen integrations. • The aggregated flexibility of distributed electricity and H 2 resources is unlocked. • Different types of virtual storage models are designed for EVs, ACs, and HRSs. • An inscribed hyperbox based aggregated flexibility projection method is proposed. • A concise day-ahead peak-regulation optimal scheduling model is developed for VPPs. [ABSTRACT FROM AUTHOR]