A distributed real-time control algorithm for energy storage sharing

In this paper, energy storage sharing among a group of cooperative households with integrated renewable generations in a grid-connected microgrid in the presence of dynamic electricity pricing is studied. In such a microgrid, a group of households, who are willing to cooperatively operate a shared energy storage system (ESS) via a central coordinator, aims to minimize their long term time-averaged costs, by jointly taking into account the operational constraints of the shared energy storage, the stochastic solar energy generations and time-varying load requests from all households, as well as the fluctuating electricity prices. We formulate this energy management problem, which comprises storage management and load control, as a constrained stochastic programming problem. Based on the Lyapunov theory, a distributed real-time sharing control algorithm is proposed to provide a suboptimal solution for the constrained stochastic programming problem without requiring any system statistics. The proposed distributed real-time sharing control algorithm, in which each household independently solves a simple convex optimization problem in each time slot, can quickly adapt to the system dynamics. The performance of the proposed low-complexity sharing control algorithm is evaluated via both theoretical analysis and numerical simulations. By comparing with a greedy sharing algorithm and the distributed ESSs case, it is shown that the proposed distributed sharing control algorithm outperforms in terms of both cost saving and renewable energy generation utilization. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates energy storage sharing among cooperative households with integrated renewable generations in a grid-connected microgrid under dynamic electricity pricing. A distributed real-time sharing control algorithm is proposed to optimize energy management, where each household independently solves a simple convex optimization problem in each time slot, leading to improved cost savings and renewable energy utilization.