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Robust and Optimal Consumption Policies for Deadline-Constrained Deferrable Loads

机译:时限约束的可延缓负载的鲁棒和最优消耗策略

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The paper analyzes the optimal response of an individual smart load with deferrable demand for electricity, to exogenous and stochastic price processes. It is assumed that a smart load can delay a time-flexible energy demand up to a fixed deadline. Under mild assumptions on the regularity of the stochastic price process, it is shown that the optimal strategy is to consume only when the price is less than or equal to a certain threshold that depends only on the time left to the deadline and the price statistics. This analysis is performed under both perfect and partial information about the statistics of the price process. Robust policies with performance guarantees are derived for the partial information case. Such performance bounds are also used for deriving upper and lower bounds on the economic value of load-shifting. Numerical simulation results based on price data from wholesale electricity markets suggest that when information must be empirically extracted from data, the robust policies provide various theoretical and practical advantages over the full information policies.
机译:本文分析了具有递延电力需求的单个智能负载对外部和随机价格过程的最佳响应。假设智能负载可以将时间灵活的能源需求延迟到固定的期限。在对随机价格过程的规律性的温和假设下,表明最优策略是仅在价格小于或等于某个阈值(仅取决于截止日期和价格统计信息的时间)的情况下进行消费。该分析是在有关价格过程统计信息的完全和部分信息下进行的。对于部分信息案例,导出了具有性能保证的健壮策略。这种性能界限还用于推导负载转移的经济价值的上限和下限。基于来自批发电力市场的价格数据的数值模拟结果表明,当必须根据经验从数据中提取信息时,与完整的信息策略相比,健壮的策略具有各种理论和实践优势。

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