The massive electric power blackout in the northeastern United States and Canada on August 14-15, 2003 resulted in the U.S. electricity system being called "antiquated" and catalyzed discussions about modernizing the grid. Industry sources suggested that investments of $50 to $100 billion would be needed. This report seeks to quantify an important piece of information that has been missing from these discussions: how much do power interruptions and fluctuations in power quality (power-quality events) cost U.S. electricity consumers? Accurately estimating this cost will help assess the potential benefits of investments in improving the reliability of the grid.We develop a comprehensive end-use framework for assessing the cost to U.S. electricity consumers of power interruptions and power-quality events (referred to collectively as "reliability events").The framework expresses these costs as a function of:• Number of customers by type in a region;• Frequency and type of reliability events experienced annually (including both power interruptions and power-quality events) by these customers; • Cost of reliability events; and• Vulnerability of customers to these events.The framework is designed so that its cost estimate can be improved as additional data become available.Using our framework, we estimate that the national cost of power interruptions is about $80 billion annually, based on the best information available in the public domain. However, there are large gaps in and significant uncertainties about the information currently available. Notably, we were not able to develop an estimate of power-quality events. Sensitivity analysis of some of these uncertainties suggests that the total annual cost could range from less than $30 billion to more than $130 billion. Because of this large range and the enormous cost of the decisions that may be based on this estimate, we encourage policy makers, regulators, and industry to jointly undertake the comparatively modest-cost improvements needed in the information used to estimate the cost of reliability events. Specific areas for improvement include: coordinated, nationwide collection of updated information on the cost of reliability events; consistent definition and recording of the duration and frequency of reliability events, including powerquality events; and improved information on the costs of and efforts by consumers to reduce their vulnerability to reliability events.

The massive electric power blackout in the northeastern U.S. and Canada on August [14][15] 2003 catalyzed discussions about modernizing the U.S. electricity grid. Industry sources suggested that investments of $50 to $100 billion would be needed. This work seeks to better understand an important piece of information that has been missing from these discussions: what do power interruptions and fluctuations in power quality (power-quality events) cost electricity consumers?We developed a bottom-up approach for assessing the cost to U.S. electricity consumers of power interruptions and power-quality events (referred to collectively as "reliability events").The approach can be used to help assess the potential benefits of investments in improving the reliability of the grid. We developed a new estimate based on publicly available information, and assessed how uncertainties in these data affect this estimate using sensitivity analysis.

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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.Assessing Changes in the Reliability of the U.S. Electric Power System │ii AcknowledgmentsThe work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, National Electricity Delivery Division of the U.S. Department of Energy (DOE) under Contract No. DE-AC02-05CH11231. The authors are grateful to David Meyer for his support of this research.We gratefully acknowledge a number of individuals who provided technical assistance, constructive advice, and/or encouragement at various points during this project: Amber Armentrout (Ventyx), William Morrow, Peter Cappers, Annika Todd, Liesel Hans, and Anna Spurlock (Lawrence Berkeley National Laboratory), Alex Hofmann, Mike Hyland (APPA), Marek Samotyj (EPRI), Bernard Neenan (Neenan Associates), Caitlin Callaghan, Rakesh Batra, and David Ortiz (DOE), Seth Blumsack (Pennsylvania State University), James Bouford (Quanta-Technology), Brett Efaw (Idaho Power), Larry Conrad (Conrad Technical Services), and John Weyant (Stanford University). We thank Dana Robson and Danielle Callaghan for their assistance with formatting the final version of the report and disseminating the results to interested stakeholders.Peter would like to thank the LBNL Tuition Assistance Program for indirectly supporting this research project. Finally, we are indebted to staff at the electric utilities and public utility commissions who shared reliability performance metrics and other insightful information with us in the early ...

This study examines the 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 weather and utility characteristics. We find statistically significant correlations between the average number of power interruptions experienced annually and above average wind speeds, precipitation, lightning strikes, and a measure of population density: customers per line mile. We also find significant relationships between the average number of minutes of power interruptions experienced and above average wind speeds, precipitation, cooling degree-days, and one strategy used to mitigate the impacts of severe weather: the amount of underground transmission and distribution line miles. Perhaps most importantly, we find a significant time trend of increasing annual average number of minutes of power interruptions over time-especially when interruptions associated with extreme weather are included. The research method described in this analysis can provide a basis for future efforts to project long-term trends in reliability and the associated benefits of strategies to improve grid resiliency to severe weather-both in the U.S. and abroad.

Lawrence Berkeley National Laboratory (LBNL)'s annual Tracking the Sun report summarizes installed prices and other trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. 1 The present report focuses on systems installed through year-end 2017, with preliminary trends for the first half of 2018. As in years past, the primary emphasis is on describing changes in installed prices over time and variation in pricing across projects. New to this year, however, is an expanded discussion of other project characteristics in the large underlying data sample. Future editions will include more of such material, beyond the report's traditional focus on installed pricing. Installed pricing trends presented within this report derive primarily from project-level data reported to state agencies and utilities that administer PV incentive programs, solar renewable energy credit (SREC) registration systems, or interconnection processes. Refer to the text box to the right for several key notes about the data. In total, data were collected and cleaned for more than 1.3 million individual PV systems, representing 81% of U.S. residential and non-residential PV systems installed through 2017. A public version of this dataset is available at trackingthesun.lbl.gov. The analysis of installed pricing trends in this report is based on a subset of roughly 770,000 systems with available installed price data.

The utility-scale solar sector-defined here to include any ground-mounted photovoltaic ("PV"), concentrating photovoltaic ("CPV"), or concentrating solar power ("CSP") project that is larger than 5 MWAC in capacity-has led the overall U.S. solar market in terms of installed capacity since 2012. It is expected to maintain its market-leading position for at least another five years, driven in part by December 2015's three-year extension of the 30% federal investment tax credit ("ITC") through 2019 (coupled with a favorable switch to a "start construction" rather than a "placed in service" eligibility requirement, and a gradual phase down of the credit to 10% by 2022). In fact, in 2016 alone, the utility-scale sector is projected to install more than twice as much new capacity as it ever has previously in a single year. This unprecedented boom makes it difficult, yet more important than ever, to stay abreast of the latest utility-scale market developments and trends. This report-the fourth edition in an ongoing annual series-is intended to help meet this need, by providing in-depth, annually updated, data-driven analysis of the utility-scale solar project fleet in the United States. Drawing on empirical project-level data from a wide range of sources, this report analyzes not just installed project costs or prices-i.e., the traditional realm of most solar economic analyses-but also operating costs, capacity factors, and power purchase agreement ("PPA") prices from a large sample of utility-scale solar projects throughout the United States. Given its current dominance in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are also presented where appropriate. Some of the more-notable findings from this year's edition include the following: • Installation Trends: Among the total population of utility-scale PV projects from which data samples are drawn, several trends are worth noting due to their influence on (or perhaps reflection of) the cost, performance, and PPA price data analyzed later. For example, the use of solar tracking devices (overwhelmingly single-axis, east-west tracking-though a few dual-axis tracking projects have entered the population in recent years) continued to expand in 2015, particularly among thin-film (CdTe) projects, which had almost exclusively opted for fixed-tilt mounts prior to 2014. In a reflection of the ongoing geographic expansion of the market beyond the high-insolation Southwest, the average long-term insolation level across newly built project sites declined for the first time in 2015. Meanwhile, the average inverter loading ratio-i.e., the ratio of a project's DC module array nameplate rating to its AC inverter nameplate rating-has increased among more recent project vintages, as oversizing the array can boost generation (relative to the AC capacity), and hence revenue, particularly during the morning and evening shoulder periods. These trends should drive AC capacity factors higher among more recently built PV projects (confirme...

There has been a limited amount of peer-reviewed literature on long-term trends in electricity reliability including the underlying factors that impact reliability across the United States. In this analysis, we considered up to 16 years of data from 203 U.S. utilities-representing about 70% of electricity sales. Annual frequency of interruptions for an average customer-at the regional and U.S. national-level-has generally decreased over this timeframe. But we do not find that there is a statistically significant trend in the annual duration of interruptions for an average customer. We find that more explicit measures of severe weather are correlated with reliability. We are able to explain 7% and 16% of past variation in the reliability metrics system average interruption duration and frequency indices, respectively, is due to severe weather-a significant improvement over earlier studies. We find that current year spending by utilities is correlated with worse reliability and that cumulative spending over the preceding three years is correlated with better reliability. Finally, we demonstrate that using a statistical instrument to represent the annual frequency of interruptions for an average customer can greatly improve analysis of trends in the annual duration of interruptions for an average customer. 1. Introduction Power interruptions are caused by a number of different factors including weather-related impacts, electrical equipment faults or failure, and, indirectly, spending strategies on power system infrastructure, operations, and maintenance. The U.S. Department of Energy (DOE) reports that extreme weather is the most commonly-reported cause of power interruptions with the frequency of these extreme events increasing significantly over the last two decades [1]. Power interruptions significantly impact economic activity. A recent study estimates that sustained power interruptions cost an average of $44 billion annually in the U.S. alone [2]. The 2017 Atlantic hurricane season is just one example of recent extreme weather that has caused long duration, widespread power interruptions. During this season, six hurricanes were classified as "major" (i.e., Saffir-Simpson Category three storms or higher). For perspective, the long-term average number of major hurricanes since 1851 is six per decade [3]. In August 2017, Hurricane Harvey flooded many parts of Texas and Louisiana where some locations received as much as five feet of rain, resulting in power interruptions that impacted more than 330,000 customers [4]. During this storm, substations were flooded, utility poles were toppled, and there was extensive damage to other critical energy and electricity infrastructure [5, 6]. The following month, Hurricane Irma caused widespread damage to the Florida Keys and resulted in power interruptions for nearly two million customers [7]. Less than a week later, Hurricane Maria-the second category five storm of the season-caused widespread devastation across the U.S. territory of Puerto Rico. This storm destroyed the is...