Electric Power Grid Disruptions : A Time Series Examination
Second , we hope to expand awareness of these data for various types of analyses and use by others concerned about electric power reliability . In particular , there is a need for multi-disciplinary study of the electric grid , including risk analyses , potential financing options for grid improvement , and the evaluation of alternative policy options . These data have limitations which are important to consider in time series analyses . We describe several of the limitations , expecting that others in the field can advocate for improved data quality and utility over time . The ability to conduct meaningful policy analysis in this arena requires reliable baseline data .
Background
Research to quantify and describe electric power system outages covers a wide range of issues and uses a variety of data sources and analytic methods . In a brief report , Wirks-Brock used the DOE dataset ( Form OE-417 ) and described compiling the information through yearly summaries of major power outage reports ( Wirfs-Brock 2014 ). Limited information was included such as outage causes , findings by day , time , and region for each reported case .
A data report by Mukherjee and colleagues described their use of publicly available data sources from several federal agencies such as the Department of Energy ( DOE ), National Oceanic and Atmospheric Administration ( NOAA ), and the National Climate Data Center ( NCDC ), among other sources ( Mukherjee , Nateghi , & Hastak 2018a ). In a recent study , Mukherjee et al . analyzed electrical outage failures for the period 2000 to 2016 and found that severe weather events accounted for 53 % of outages ( Mukherjee , Nateghi , & Hastak 2018b ). An earlier study proposed a model for risk-based decision-making to assess the impacts of weather induced power outages ( Mukeherjee 2017 ).
Another study examined major electrical distribution disturbances and unusual occurrences for the period 2002 through 2013 ( Nateghi , Guikema , Wu , & Bruss 2016 ). The authors concluded that extreme event repercussions are important , and that the risks associated with high impact low-frequency events may not be fully acknowledged and understood .
Adderly et al . ( 2019 ) used the DOE database to project the potential impacts of smart grid financing to reduce the economic impacts of U . S . large outage events . Applying residential and small , medium , and large business customer data as well as outage duration , a metric was developed to gauge the economic impact of outages on electricity customers . They found that the infusion of $ 4.5 billion by the Department of Energy in smart grid technologies in 2010 led to billions of dollars of financial benefits between 2011-2016 compared to 2003-2010 ( Adderly et al . 2019 ).
Three studies noted the importance and challenges of consequential low
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