A Data-Driven Dispatching Approach for Sustainable Exploitation of Demand Response Resources

B. Zeng, Xuan Wei, Jiahuan Feng
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引用次数: 1

Abstract

Under the smart-grid environment, demand response (DR) provides an equivalent reserve resource to mitigate operational uncertainties, in addition to the supply-side solutions. Thus, identifying the effect of DR to service reliability turns to be essential for strategic planning decisions. In this paper, a novel data-driven dispatching approach for sustainable exploitation of DR capabilities in future smart-grids is proposed. Differing to existing studies, the user willingness factor attended with DR is especially focused in this work. To achieve this, we develop a two-term DR model, wherein the compliance of customers is characterized as a dynamic self-optimizing process that specified by the regret measure regarding historical payoffs. On this basis, a data-driven-based DR scheduling model is formulated from the grid’s point of view. It could permit desired tradeoffs between the system reliability target and sustainability of DR provision. To verify the effectiveness of the proposed approach, a hybrid algorithm embedded with sequential Monte-Carlo simulations is developed. Numerical experiments are conducted to illustrate the performance of the proposed method based on a real-world distribution network.
需求响应资源可持续开发的数据驱动调度方法
在智能电网环境下,需求响应(DR)除了提供供应侧解决方案外,还提供了一个等效的储备资源,以减轻运行的不确定性。因此,识别DR对服务可靠性的影响对于战略规划决策至关重要。本文提出了一种新的数据驱动调度方法,以实现未来智能电网容灾能力的可持续开发。与现有研究不同,本研究特别关注与DR相关的用户意愿因素。为了实现这一点,我们开发了一个两期DR模型,其中客户的合规性被描述为一个动态的自优化过程,该过程由关于历史收益的后悔度量指定。在此基础上,从网格的角度提出了基于数据驱动的容灾调度模型。它可以允许在系统可靠性目标和DR供应的可持续性之间进行预期的权衡。为了验证该方法的有效性,开发了一种嵌入时序蒙特卡罗模拟的混合算法。在实际配电网中进行了数值实验,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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