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Cost Minimizing Online Algorithms for Energy Storage Management With Worst-Case Guarantee

机译：具有最坏情况保证的最小化在线能量存储管理算法

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摘要

The fluctuations of electricity prices in demand response schemes and intermittency of renewable energy supplies necessitate the adoption of energy storage in microgrids. However, it is challenging to design effective real-time energy storage management strategies that can deliver assured optimality, without being hampered by the uncertainty of volatile electricity prices and renewable energy supplies. This paper presents a simple effective online algorithm for the charging and discharging decisions of energy storage that minimizes the electricity cost in the presence of electricity price fluctuations and renewable energy supplies, without relying on the future information of prices, demands, or renewable energy supplies. The proposed algorithm is supported by a near-best worst-case guarantee (i.e., competitive ratio), as compared with the offline optimal decisions based on full future information. Furthermore, the algorithm can be adapted to take advantage of limited future information, if available. By simulations on real-world data, it is observed that the proposed algorithms can achieve satisfactory outcomes in practice.
机译：需求响应计划中的电价波动和可再生能源供应的间歇性，使得微电网必须采用储能技术。但是，设计有效的实时能量存储管理策略具有挑战性，这可以确保在不因电价波动和可再生能源供应的不确定性而受到阻碍的情况下实现最优性。本文提出了一种用于储能充电和放电决策的简单有效的在线算法，该算法在存在电价波动和可再生能源供应的情况下将电力成本降至最低，而无需依赖于未来的价格，需求或可再生能源供应信息。与基于全部未来信息的离线最优决策相比，所提出的算法具有近乎最佳的最坏情况保证（即竞争比率）。此外，该算法可以调整为利用有限的未来信息（如果可用）。通过对现实世界数据的仿真，可以发现所提出的算法在实践中可以取得令人满意的结果。

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