Distributed optimization model and algorithms for virtual energy storage systems using dynamic price

Abstract Virtual energy storage systems (VESS) are important new equipment for distribution networks, consisting of battery energy storage systems (BESS) or flexible loads (FL), that improve peak shaving, frequency regulation and energy management. This paper focuses on power management and real-time control for multiple virtual energy storage systems (MVESS). To enhance renewable energy penetration using competing objective functions in MVESS, a distributed multi-objective power management scheme is proposed, where a Nash Bargaining Solution (NBS) is used to find optimal, unique and fair solutions. A distributed integral optimization algorithm, with fast convergence, is designed to solve the NBS-based problem, containing equality and inequality constraints. Distributed real time control for MVESS is proposed to increase system efficiency and control State of Energy (SoE) and proportional power sharing between BESS and FL. The mathematical analysis guarantees optimality and convergence for the two proposed algorithms. To evaluate the performance of the strategy, three different case studies were executed on a real time digital simulator (OPAL-RT OP5600). Finally, the simulation results demonstrate that system power was shared optimally between VESS, with proportional power sharing among BESS and FL and SoE synchronization.