@article{27870,
  author = {Joseph H Eto and Kristina Hamachi LaCommare and Michael D Sohn and Heidemarie C Caswell},
  title = {Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days  View Document},
  abstract = {<p>IEEE Standard 1366 offers a method for segmenting reliability performance data to isolate the effects of major events from the underlying year-to-year trends in reliability. Recent analysis by the IEEE Distribution Reliability Working Group (DRWG) has found that reliability performance of some utilities differs from the expectations that helped guide the development of the Standard 1366 method. This paper proposes quantitative metrics to evaluate the performance of the Standard 1366 method in identifying major events and in reducing year-to-year variability in utility reliability. The metrics are applied to a large sample of utility-reported reliability data to assess performance of the method with alternative specifications that have been considered by the DRWG. We find that none of the alternatives perform uniformly “better” than the current Standard 1366 method. That is, none of the modifications uniformly lowers the year-to-year variability in SAIDI without major events. Instead, for any given alternative, while it may lower the value of this metric for some utilities, it also increases it for other utilities (sometimes dramatically). Thus, we illustrate some of the trade-offs that must be considered in using the Standard 1366 method and highlight the usefulness of the metrics we have proposed in conducting these evaluations.</p>},
  year = {2016},
  journal = {IEEE Transactions on Power Systems },
  volume = {32},
  month = {07/2016},
  publisher = {IEEE},
  doi = {10.1109/TPWRS.2016.2585978},
}