NewEnergyNews: TODAY’S STUDY: STATS ON THE HAVOC CLIMATE CHANGE IS BRINGING

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    Monday, September 21, 2015

    TODAY’S STUDY: STATS ON THE HAVOC CLIMATE CHANGE IS BRINGING

    Assessing Changes in the Reliability of the U.S. Electric Power System

    Larsen, et.al., August 2015 (Lawrence Berkeley National Laboratory)

    Abstract

    Recent catastrophic weather events, existing and prospective federal and state policies, and growing investments in smart grid technologies have drawn renewed attention to the reliability of the U.S. electric power system. Whether electricity reliability is getting better or worse as a result of these or other factors has become a material issue for public and private decisions affecting the U.S. electric power system.

    This study examines the statistical relationship between annual changes in electricity reliability reported by a large cross‐section of U.S. electricity distribution utilities over a period of 13 years, and a broad set of potential explanatory variables including various measures of weather and utility characteristics.

    We find statistically significant correlations between the average number of power interruptions experienced annually by a customer and a number of explanatory variables including wind speed, precipitation, lightning strikes, and the number of customers per line mile. We also find statistically significant correlations between the average total duration of power interruptions experienced annually by a customer and wind speed, precipitation, cooling degree‐days, the percentage share of underground transmission and distribution lines. In addition, we find a statistically significant trend in the duration of power interruptions over time—especially when major events are included. This finding suggests that increased severity of major events over time has been the principal contributor to the observed trend.

    Executive Summary

    Recent catastrophic weather events, existing and prospective federal and state energy and environmental policies, and growing investments in smart grid technologies have drawn renewed attention to the reliability of the U.S. electric power system. Whether electricity reliability is getting better or worse as a result of these or other factors has become a material issue for public and private decisions affecting the U.S. electric power system.

    Over the past 15 years, the most well‐publicized efforts to assess trends in U.S. electric power system reliability have focused only on a subset of all power interruption events (see, for example, Amin 2008 and Campbell 2012)—namely, only the very largest events, which trigger immediate emergency reporting to federal agencies and industry regulators. Anecdotally, these events are thought by many to represent no more than 10% of the power interruptions experienced annually by electricity consumers. Moreover, a review of these emergency reports has identified shortcomings in relying on these data as reliable sources for assessing trends, even with the reliability events they report (Fisher et al. 2012).

    Recent work has begun to address these limitations by examining trends in reliability data collected annually by electricity distribution companies (Eto et al. 2012). In principle, all power interruptions experienced by electricity customers, regardless of size, are recorded by the distribution utility. Moreover, distribution utilities have a long history of recording this information, often in response to mandates from state public utility commissions (Eto et al. 2006). Thus, studies that rely on reliability data collected by distribution utilities can, in principle, provide a more complete basis upon which to assess trends or changes in reliability over time.

    Accordingly, we assembled up to 13 years of information on the annual duration and frequency of power interruptions for a large cross‐section of U.S. electricity distribution utilities. These utilities, taken together, represent 70% of both U.S. electricity sales and total U.S. electricity customers. We then performed an econometric analysis to correlate annual changes in reliability reported by these utilities with a broad set of explanatory variables, including annual information on lightning strikes, average wind speeds, temperatures, numbers of customers per line mile of distribution, percentage of the distribution system underground, installation or upgrade of an automated outage management system, and transmission and distribution (T&D) spending.

    The measures of electricity reliability used in this study are the System Average Interruption Duration Index (SAIDI) and the System Average Interruption Frequency Index (SAIFI). SAIDI can be thought of as the total amount of time that a utility’s customers, on average, are without power over the course of a year. SAIFI can be thought of as the total number of times that a utility’s customers, on average, have experienced power interruptions over the course of a year.

    We conducted separate analyses of SAIDI and SAIFI both without and with inclusion of what utilities term “major events.” In order to facilitate year‐on‐year comparisons of utility reliability performance, utilities report SAIDI and SAIFI both without and with inclusion of major events. Major events refer to times during the year when the utility is subjected to significant, yet generally infrequent stresses, often due to severe weather. The number of major events experienced by a utility in any given year can vary considerably, yet because they are large including them has a disproportionate effect on year‐to‐year trends in reported reliability.

    Findings related to the annual average duration of power interruptions (SAIDI)

    If major events are not included (see Figure ES ‐ 1), we find the following statistically significant relationships:

    • A 5% increase in annual average wind speed—above the long‐term (generally, 13‐year) average— is correlated with a 5% increase in SAIDI; yet a 10% increase in annual average wind speed is correlated with a 2% decrease in SAIDI1

    • Independent of these factors, each successive year over the analysis period is correlated with a slightly larger than 1% increase in the SAIDI

    If major events are included (see Figure ES ‐ 2), we find the following statistically significant relationships:

    • A 10% increase in annual precipitation—above the long‐term (generally, 13‐year) average—is correlated with a 10% increase in SAIDI

    • A 10% increase in the number of cooling degree‐days (i.e., warmer weather)—above the long‐ term (generally,13‐year) average—is correlated with a 8% decrease in SAIDI

    • A 5% increase in annual average wind speed—above the long‐term (generally, 13‐year) average—is correlated with a 56% increase SAIDI; a 10% increase in annual average wind speed is correlated with a 75% increase in SAIDI

    • A 10% increase in the percentage share of underground line miles is correlated with a 14% decrease in SAIDI

    Independent of the above factors, each successive year over the analysis period is also correlated with a nearly 10% increase in SAIDI.

    Findings related to the annual average frequency of power interruptions (SAIFI)

    If major events are not included (see Figure ES ‐ 3), we find the following statistically significant relationships:

    • A 10% increase in the number of customers per line mile is correlated with a 4% decrease in SAIFI

    • A 5% increase in annual average wind speed —above the long‐term (generally, 13‐year) average— is correlated with a 6% increase in SAIFI; yet a 10% increase in annual average wind speed is correlated with only a 1% increase in SAIFI

    If major events are included (see Figure ES ‐ 4), we find the following statistically significant relationships:

    • A 10% increase in annual lightning strikes is correlated with a 2% increase in SAIFI

    • A 5% increase in annual average wind speed —above the long‐term (generally, 13‐year) average— is correlated with a 14% increase in SAIFI; 10% increase in annual average wind speed is correlated with a 15% increase in SAIFI

    • A 10% decrease in average total precipitation—below the long‐term (generally, 13‐year) average— is correlated with a 3% increase in SAIFI

    Discussion of Findings

    We find a statistically significant trend in increasing annual average duration of power interruptions over time. The trend is larger when major events are included, which suggests that increases in the severity of major events over time has been the principal contributor to the observed trend.

    We were also surprised to find that increased T&D spending in the previous year was not correlated in any statistically significant fashion with improvements in reliability in the following year. We suspect that reliability is affected differently depending on whether utilities spend relatively more on preventative maintenance when compared to reactive maintenance. The presence of “competing” effects within the utility spending data may be influencing the results and leading to the counter‐ intuitive findings. Unfortunately, we did not have access to more detailed information on the constituents of annual utility T&D spending in order to explore these possibilities.

    Strictly speaking, these findings apply only to the utilities whose data we included in our analysis. Specifically, the utilities included in this study represent a significant portion of total electricity sales from all regions of the country except the East South Central census region. More precisely, our findings cannot be assumed to apply to the 25%, 99%, and 97% of investor‐owned, municipally‐owned, and cooperative utilities, respectively, that were not included in our study.

    Hence, while we believe this analysis is the most comprehensive study of this topic that has been performed to date, there are a number of areas where we believe improvements should be considered in future analyses of U.S. electric power system.

    First, there may be more appropriate annual weather parameters available to better capture the factors underlying major events (e.g., number of days per year with peak wind speeds greater than 35 mph, significant drought years followed by abnormally wet years).

    Second, as noted, it is important to continue to explore the relationship between reactive and proactive T&D spending and reliability. Related to this, we also believe that the relationship between reliability and the long‐run deployment of other “smart” technologies should be explored further.

    We hope that our findings will help to inform future public and private decisions that will influence the future reliability of the U.S. electric power system.

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