Distributed Control of Virtual Storage Plants for Grid Service Provision

This paper proposes a distributed Model Predictive Control (MPC) approach to coordinate flexible resources as a virtual storage plant (VSP) for delivering ancillary services to the power network with high renewable penetration. We consider VSPs comprising battery systems and Heating, Ventilation and Air Conditioning (HVAC) systems acting as storages. The proposed control framework is based on stochastic MPC and an alternating direction method of multipliers (ADMM)-based fully distributed algorithm. The main control objective is to timely track a time-varying automatic generation control signal from the area control center of the electric grid by optimally coordinating an arbitrary number of HVAC and battery units. The uncertainty is handled by randomized techniques, with a number of scenarios guaranteeing a robust constraint satisfaction of the stochastic convexified problem formulation. The effectiveness of the MPC scheme is tested through a numerical case study, where the proposed MPC framework can systematically deal with the system constraints and technical service requirements, and the procured nearly real-time unit dispatch can compensate for the impact of renewables on the network operation.