Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 9, Issue 6, Pages 6590-6598Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2017.2716382
Keywords
Energy storage; frequency regulation; energy arbitrage; low-rank approximation
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We develop a near-optimal solution to the problem of co-optimizing frequency regulation and energy arbitrage with battery storage using backward approximate dynamic programming, which is shown to handle the different time scales of each revenue stream. Solution of the problem using classical backward exact dynamic programming is computationally intractable for this problem due to the large state space and long horizon. Instead, we use state sampling and low-rank approximations to estimate the entire value function, producing a high quality solution that can he computed in real time. The new algorithm is shown to reduce the computational time by one order of magnitude, and the storage requirements by two orders of magnitude, while producing near optimal policies that consistently outperform pure frequency regulation.
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