Updated Value of Service Reliability Estimates for Electric Utility Customers in the United States
Updated Value of Service Reliability Estimates for Electric Utility Customers in the United States
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DOI：
10.2172/1172643
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Sullivan;Josh A. Schellenberg;M. Blundell
中科院分区：
文献类型：
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作者：
M. Sullivan;Josh A. Schellenberg;M. Blundell
本报告更新了2009年的荟萃分析，该分析提供了美国电力客户服务可靠性价值的估计。元数据集现在包括10个不同的公用事业公司在1989年至2012年期间进行的调查的34个不同的数据集。由于这些研究使用了几乎相同的中断成本估计或意愿支付/接受方法，因此可以将其结果整合到一个单一的元数据集中，描述在所有这些研究中观察到的电力服务可靠性的价值。一旦将来自各种研究的数据集组合在一起，就可以使用两部分回归模型来估计客户损失函数，该函数通常可用于计算美国工业，商业和住宅客户的每个事件的客户中断成本，包括季节，一天中的时间，一周中的一天和地理区域。本报告重点介绍用于为所有客户类别开发最终修订模型的向后逐步选择流程。在客户类别中，修订后的客户中断成本模型得到了显著改善，因为它包含了更多的数据，并且不包括2009年荟萃分析中原始规范中的许多无关变量。向后逐步选择过程导致了一个更简约的模型，只包括关键变量，同时仍然实现了可比的样本外预测性能。反过来，中断成本估算工具（如中断成本估算（ICE）计算器）的用户将有更少的客户特征信息提供，相关的输入页面将不那么麻烦。ICE计算器的新版本预计将于2015年发布。
This report updates the 2009 meta-analysis that provides estimates of the value of service reliability for electricity customers in the United States (U.S.). The meta-dataset now includes 34 different datasets from surveys fielded by 10 different utility companies between 1989 and 2012. Because these studies used nearly identical interruption cost estimation or willingness-topay/accept methods, it was possible to integrate their results into a single meta-dataset describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the U.S. for industrial, commercial, and residential customers. This report focuses on the backwards stepwise selection process that was used to develop the final revised model for all customer classes. Across customer classes, the revised customer interruption cost model has improved significantly because it incorporates more data and does not include the many extraneous variables that were in the original specification from the 2009 meta-analysis. The backwards stepwise selection process led to a more parsimonious model that only included key variables, while still achieving comparable out-of-sample predictive performance. In turn, users of interruption cost estimation tools such as the Interruption Cost Estimate (ICE) Calculator will have less customer characteristics information to provide and the associated inputs page will be far less cumbersome. The upcoming new version of the ICE Calculator is anticipated to be released in 2015.