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Pareto Optimal Operation of Distributed Battery Energy Storage Systems for Energy Arbitrage under Dynamic Pricing

机译:动态定价下用于套利的分布式电池储能系统的帕累托最优运行

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摘要

The optimal operation of a distributed battery energy storage system (BESS) for energy arbitrage under dynamic pricing is studied in this paper, and the Pareto optimal arbitrage policy that balances the economic value and lifetime tradeoff of the BESSis obtained. Specifically, the lifetime performance of the BESS is represented by its average lifetime, i.e., the average operational duration within which its capacity stays above a certain threshold, and the value performance of the BESS is defined as the total average arbitrage value within its entire lifetime. We propose a constrained stochastic shortest path (CSSP) model to characterize the optimal value-lifetime performance pair. By exploiting the hidden structure of this CSSP problem, an efficient parallel algorithm is proposed to compute the optimal policy. We further prove the condition under which the optimal policy is Pareto optimal. This implies that the achievable optimal value-lifetime performance pair is globally optimal as long as the system-wide utility is monotonically increasing in both the value performance and the lifetime performance. We validate our proposed model and algorithm via real battery specifications and electricity market data, and the results show promising insights for both infrastructure planning and operational management of BESSs in practice.
机译:研究了动态定价下用于能源套利的分布式电池储能系统(BESS)的最优运行,并获得了平衡BESS的经济价值和寿命折衷的帕累托最优套利策略。具体而言,BESS的生命周期性能由其平均生命周期表示,即其容量保持在一定阈值以上的平均操作持续时间,并且BESS的价值绩效定义为其整个生命周期内的总平均套利值。我们提出了一种约束随机最短路径(CSSP)模型来表征最佳价值-寿命绩效对。通过利用此CSSP问题的隐藏结构,提出了一种有效的并行算法来计算最优策略。我们进一步证明了最优策略是帕累托最优的条件。这意味着,只要系统范围的效用在价值绩效和生命周期性能上单调增加,则可实现的最佳价值-生命周期绩效对是全局最优的。我们通过实际的电池规格和电力市场数据验证了我们提出的模型和算法,结果表明在实践中对于基础设施规划和BESS的运营管理都具有广阔的前景。

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