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arXiv · 1706.00620

Real-time Shared Energy Storage Management for Renewable Energy Integration in Smart Grid

Katayoun Rahbar·Mohammad R. Vedady Moghadam·Sanjib Kumar Panda
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Abstract

Energy storage systems (ESSs) are essential components of the future smart grids with high penetration of renewable energy sources. However, deploying individual ESSs for all energy consumers, especially in large systems, may not be practically feasible mainly due to high upfront cost of purchasing many ESSs and space limitation. As a result, the concept of shared ESS enabling all users charge/discharge to/from a common ESS has become appealing. In this paper, we study the energy management problem of a group of users with renewable energy sources and controllable (i.e., demand responsive) loads that all share a common ESS so as to minimize their sum weighted energy cost. Specifically, we propose a distributed algorithm to solve the formulated problem, which iteratively derives the optimal values of charging/discharging to/from the shared ESS, while only limited information is exchanged between users and a central controller; hence, the privacy of users is preserved. With the optimal charging and discharging values obtained, each user needs to independently solve a simple linear programming (LP) problem to derive the optimal energy consumption of its controllable loads over time as well as that of purchased from the grid. Using simulations, we show that the shared ESS can achieve lower energy cost compared to the case of distributed ESSs, where each user owns its ESS and does not share it with others. Next, we propose online algorithms for the real-time energy management, under non-zero prediction errors of load and renewable energy. The proposed algorithms differ in complexity and the information required to be shared between the users and central controller, where their performance is also compared via simulations.

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Katayoun Rahbar, Mohammad R. Vedady Moghadam, Sanjib Kumar Panda. 2017-06-02. Real-time Shared Energy Storage Management for Renewable Energy Integration in Smart Grid. https://arxiv.org/abs/1706.00620

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