Hierarchical Data-Driven Optimization Scheme Compatible with the Conception of Solid-State Power Substation for Real-time VPP Management

This paper investigates a hierarchical stochastic optimization model (SO) for a virtual power plant (VPP) considering the availability of battery storage and plug-in electric vehicles (EV) in a VPP, the spot price and its prediction for maximizing revenue over the whole trading horizon. Unlike traditional routes, such a SO model is compatible with the conception of a solid-state power substation (SSPS) to extend instant optimal operation details to the downstream energy storage individuals and thus decrease the complex computational and communicational time cost into a reasonable time frame adapted to real-time decisions. Further, a discrete behaviour scheme is proposed to adapt the control of charging /discharging of the battery storages with the real-time spot price and its rolling prediction update, and an SSPS-based auction algorithm is proposed to coordinate the interplay between the VPP and the downstream battery population. The simulation results show the proposed method not only can manage the battery storage in a VPP to obtain the traditional revenue but also can be more effective and suitable to operate in real-time control.