Examining uncertainty in demand response baseline models and variability in automated responses to dynamic pricing
Examining uncertainty in demand response baseline models and variability in automated responses to dynamic pricing
复制标题
检查需求响应基线模型的不确定性和动态定价自动响应的可变性
DOI：
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发表时间：
2011
期刊：
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通讯作者：
S. Kiliccote
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作者：
J. Mathieu;Duncan S. Callaway;S. Kiliccote
控制电力负荷以提供电力系统服务提出了许多有趣的挑战。例如，商业和工业（C&I）设施的电力消耗变化通常使用反事实基线模型进行估计，模型的不确定性使得难以精确量化控制响应。此外，C&I设施在其响应中表现出可变性。本文旨在了解基线模型误差和需求方的可变性，在开环控制信号（即动态价格）的反应。使用基于回归的基线模型，我们定义了几个需求响应（DR）参数，其特征在于在DR天的用电量的变化，然后提出了一种方法用于计算与DR参数估计的误差。除了分析DR参数误差的幅度之外，我们还开发了一种度量来确定观察到的DR参数变异性有多少归因于真实的事件间变异性与简单的基线模型误差。使用的数据从38 C&I设施，参加了自动化的DR程序在加州，我们发现，DR参数误差很大。对于大多数设施，观察到的DR参数变异性可能由基线模型误差解释，而不是真实的DR参数变异性;然而，许多设施表现出真实的DR参数变异性。在某些情况下，C&I设施的总人口表现出真实的DR参数的变化性，导致系统运营商在资源规划和系统稳定性方面的影响。
Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.