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Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

Estimates of the economic impact of widespread, long duration (WLD) power interruptions can be used to prioritize and justify significant investments in power system resilience. This report presents estimates of this type for WLDs originating within the Commonwealth Edison (ComEd) service territory. The intended audience for this research includes utility executives and technical staff, regulators, and government agencies.This project involved surveying ComEd customers to understand how they might respond when confronted with a WLD power interruption. The research team used the survey responses to calibrate a state-of-the-art regional economic model (“POET”) to estimate economic impacts to households and 38 industry sectors across 17 impacted micro-regions (individual counties or aggregations of counties) within ComEd’s service territory and beyond. We ran one-day, three-day, and 14-day interruption duration scenarios each with varying geographic extents as well as estimated the benefits of deploying additional backup generation across the service territory. The results were then compared to a “business as usual” scenario assuming that no interruption occurred. There are six key findings from this analysis:-There may be significant losses to gross output (business revenue), gross domestic product, and household consumption during WLD interruptions, especially multi-day interruptions that occur across all of ComEd, Cook county, or the suburbs of Chicago.-The wholesale trade and transportation sectors appear to be highly sensitive to power interruptions—losses to these sectors are large relative to the losses observed across the entire economy.-Several sector-region combinations—e.g., the transportation sector in Cook county—are very sensitive to interruptions.-High-income households experience proportionately larger losses to consumption during a one-day power interruption, but low-income households experience proportionately larger losses during the longest power interruptions.-Increasing the amount of backup generation deployed across ComEd’s service territory provides significant net benefits to system-wide gross domestic product, gross output, and household consumption relative to the existing amount of backup generation already being used.-Some micro-regions (e.g., Dekalb and Kendall counties), sectors (e.g., wholesale trade, transportation), and low-income households in Cook county may especially benefit from targeted resilience interventions.We recommend that decision-makers consider running cost-benefit analyses using each of the economic metrics presented in this report independent of one another to evaluate the robustness of the insights that each of these estimates may provide. In addition to this report, we developed a tool that will allow ComEd staff and other decision-makers to visualize the full suite of results using an easy-to-interpret, user interface. We hope that the findings from this research effort will provide valuable insights to ComEd, policymakers across Illinois, and other stakeholders who have an interest in the resilience of the power system.

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. In this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

This paper identifies and evaluates issues in traditional resource adequacy (RA) assessment practices, and how adjusting these practices may affect and depend on existing institutional arrangements for planning and procurement. The paper proposes a technical-institutional roadmap that would allow regulators in vertically-integrated jurisdictions and system planners and operators in restructured jurisdictions to revise RA practices across a range of components.First, we compile a critical review of current RA assessment practices based on (1) interviews with RA practitioners and (2) a review of recent technical literature. We find that (i) RA may need to expand beyond capacity adequacy to ensure energy adequacy – relevant for energy-limited resources such as storage – and potentially some form of ancillary service adequacy (e.g. enough ramping-up and ramping-down capability in the system); (ii) chronological hourly simulations for all hours in the year are the current best practice; (iii) metrics and models used do not reflect economic criteria in system operation and loss of load; and (iv) there is a need to improve representation of weather dependencies and weather data.Second, we review planning and RA reports for several private and public entities that plan generation and/or transmission infrastructure in the continental U.S. to look for existing practices involving resilience assessments. We find no systematic treatment of the costs of extreme weather and other hazards, the benefits of resilience, and resilience metrics in planning analyses and no systematic treatment of resilience metrics, methods, and outcomes for resource adequacy purposes.Third, we create a technical framework for probabilistic RA assessment and use it to study how key choices about how to model power system operations affect the values that are obtained for RA metrics. We find that (i) non-economic dispatch schemes that ignore economic objectives can lead to accurate RA assessments when coordinated with detailed operational strategies; (ii) multi-year data is critical to capture a wide variety of system conditions; (iii) not incorporating transmission limits into RA assessment could lead to substantial underestimation of traditional “expected value” RA metrics; and (iv) new RA metrics that capture event-specific shortfall characteristics should be used as supplements to traditional metrics.Finally, we examine RA assessments and use this information to propose a guide of evolving industry standards for resource adequacy assessments in resource planning and transmission planning. We report minimum, best, and frontier practices for temporal resolution of assessments, metrics and targets, weather data, load forecasting, characterization of variable renewable resources, characterization of transmission and market transactions, RA modeling and integration with planning processes, and capacity accreditation.

The California Public Utilities Commission (CPUC) sought support for the development of database schema specifications for a bi-directional data portal that would foster cross-jurisdictional collaboration necessary to improve resilient energy infrastructure planning processes. This technical assistance activity involved Berkeley Lab researchers reviewing 34 local/tribal government hazard mitigation plans to assess (1) the natural hazards that communities are most concerned about; (2) the variety of–and terminology used to describe–critical community infrastructure; and (3) the availability of GIS information that could be incorporated into CPUC-mandated "Microgrid Planning Portals". In addition, we develop a common, but generic data taxonomy showing what fields to collect to encourage consolidating and sharing of this information in the future. Finally, we partnered with the Bishop Paiute tribal government to demonstrate the value of combining electricity infrastructure, natural hazard layers, and critical community infrastructure into a series of maps. The project demonstrated that a single system containing both electric utility and community infrastructure data—as well as information about natural hazards—will help the state of California, the IOUs, first responders, and long-term planners better prepare for—and thus lower their exposure to these ongoing and emerging hazards. The project also identified a number of challenges that will need to be overcome before it is possible to stand up a single system to display this information.

Large-scale disasters have exposed vulnerabilities in energy systems and interdependent infrastructure, underscoring the importance of proactively mitigating risks to critical infrastructure. This paper focuses on strengthening power system planning by incorporating the costs associated with prolonged and extensive power interruptions to bolster resilience. To achieve this, duration-dependent customer damage functions are developed, capturing the direct, indirect, and societal impacts of power interruptions, ranging from short, localized events to widespread and long-duration ones. The research methodology is applied to three islanded communities facing substantial resilience challenges with limited data availability. Three customer interruption cost surveys are conducted with local electricity customers, yielding valuable insights into duration-dependent customer damage functions for direct, indirect, and monetizable societal costs. Significantly, the power interruption cost estimates derived from these functions vary considerably from those in the contiguous U.S. and even between the different islanded communities, reflecting their distinct hazard profiles and geographical characteristics. In conclusion, this study demonstrates the potential of duration-dependent customer damage functions to enhance power system resilience. It also identifies several areas for further research, paving the way for a more robust and resilient power infrastructure.

The costs that power interruptions impose on customers and society have emerged as essential considerations for decision-making about power system reliability and resilience. While the direct costs of localized and relatively short-duration power interruptions are well-understood, little is known about the full impact of widespread and long-duration power interruptions, especially the indirect costs and related economy-wide impacts of these events. As a result, the costs of widespread and long-duration power interruptions are generally not or only incompletely considered in utility planning activities. This paper describes a new approach for estimating the economic costs of widespread and long-duration power interruptions. This method involves using survey responses from utility customers to calibrate a regional economic model that can estimate both the direct and indirect costs of these events. Including better estimates of these costs will enhance both the comprehensiveness and completeness of the considerations relied on to support utility planning decisions, especially on grid-hardening strategies and other capital-intensive investments in electricity sector resilience.

This study explores the joint impacts across the power system of distributed energy resources (DER) that could be deployed in utility distribution systems through an analysis of generation, transmission, and distribution expansion and costs driven by DER adoption. We identify six adoption scenarios that combine deployment levels of rooftop solar photovoltaic modules (PV), electric vehicle charging (EV), and battery storage in residential and commercial customers connected to representative feeders in Indiana by 2025 and 2040. Indiana is a good proxy for many U.S. states with low current DER adoption but potentially high future growth. The economic value of DER is assessed by developing capacity expansion and power flow analysis of the generation and distribution segments, respectively, under future hourly demand assumptions based on each adoption scenarios. Results for the distribution system power flow simulations show that voltage violations are relatively rare. Voltage violations can be mitigated at a very low cost using a combination of smart inverters in future rooftop PV systems and voltage adjustments in the feeder heads. Line loading issues are minimal, with only 0.2% of simulation hours showing loading levels above 100% of capacity. Generation capacity impacts are driven by unmanaged EV charging and could be mitigated with charging management. We estimate that the incremental rate impact from power system investment and operation of increased DER adoption in Indiana will be between −1.6% to + 2% in 2025 and + 0.2% to + 15% in 2040 relative to the base case.

This study is the latest in a series of LBNL research into U.S. ESCO industry characteristics and market trends. The research is based on interviews with ESCO industry executives conducted during the fall of 2019 and the first half of 2020. Nearly all companies that identified themselves as ESCOs were contacted as part of this project.We find that after a period of little growth (2011-2014), industry revenues reached an estimated $6 billion in 2018, or a 3.4% annual average growth rate from 2015-2018. ESCOs primarily serve the public an institutional sectors (e.g., federal, state, and local governments; university and colleges; and K-12 schools). In 2018, project investments by public and institutional organizations accounted for over 90% of industry revenue, which is consistent with previous industry studies. ESCO activity in the Middle Atlantic, East North Central, and Pacific regions in the U.S. delivered the highest share of revenue in 2018, which is also consistent with earlier research. ESCOs reported that a majority of their customers use energy savings performance contracts (ESPCs) primarily for facility capital improvement needs and resilience rather than utility savings. In addition, the importance of non-energy benefits (e.g., water savings, avoided operations and maintenance costs, and avoided capital costs) accounted for in the project savings guarantee reportedly increased in all markets during 2016-2018 compared to previous time periods.The study found that the ESCO industry faces several key challenges, including: (1) increasing project development times due to more complex projects and other factors; (2) difficulty finding qualified subcontractors in some regions, including minority- women- and disadvantaged population-owned small business enterprises; and (3) difficulty accessing project documents and quickly fulfilling customer requests to justify project payments several years into the performance period of a project.

Resource adequacy (RA) is the ability of an electricity system to reliably satisfy loads using its available resources. Assessing and maintaining RA is becoming more challenging due to increasing coal plant retirements, penetration of wind and solar resources, reliance on bilateral and market transactions, and emerging technologies. RA evaluation and planning have traditionally been conducted by utilities and overseen by their state regulators using integrated resource planning (IRP) processes. However, the Northwest Power Pool (NWPP) is developing a proposal for a regional RA program in the Western U.S. that would set and enforce capacity obligations for member utilities, and achieve RA more cost-effectively by pooling resources and load profiles from across the region. In this paper, we investigate the policy implications of a regional RA program for existing IRP regulations, with the proposed NWPP RA program as our main object of study. We compile the RA assessment practices of Western U.S. utilities, the proposed NWPP RA program design, and lessons from the historical experience of the Southwest Power Pool's RA program. Our analysis reveals that the IRP components which would be most heavily impacted by the regional program are RA targets, load forecasts, capacity accreditation factors, and transmission upgrades. We conclude by discussing the policy issues that RA program design and state IRP policy would have to address.

LBNL collaborated with the Western Interstate Energy Board and the University of Texas-Austin to investigate the implications of a regional resource adequacy (RA) program on utility integrated resource planning (IRP). This report is focused on an active policy discussion to develop a novel voluntary program to share capacity resources and improve RA in the Western Interconnection. This report identifies two RA components of IRP that will be highly impacted by a regional RA program: resource capacity accreditation and RA targets. There are at least four resources that will require specific attention for their capacity credit calculations: (1) variable renewable resources, (2) demand-side resources, (3) hydroelectric resources, and (4) power purchase agreements. It will also be necessary to decide on a RA target reliability metric (e.g., a planning reserve margin) that is at least the minimum requirement in IRPs to ensure consistency in RA requirement calculations. The report finds that load forecasting and transmission expansion analyses will be moderately impacted, but that most of IRP components will be not significantly impacted.The report includes a review of traditional resource adequacy practices in IRP; a case study of an existing regional RA program that interacts with IRP (Southwest Power Pool) and it presents the Northwest Power Pool (NWPP) regional resource adequacy proposal that is a focus of this research. This paper addresses three research questions:•How would typical IRP processes change if a utility joined a regional RA program?•Which RA elements would remain local (i.e. within IRP) and which would become regional (i.e. within the RA program)? •How much control would utilities and states retain over their utility resource mixes considering the influence of a regional RA program? This paper is primarily written for state policymakers, public utility commission staff, and resource planners from states in the NWPP footprint that are pondering how their IRP guidelines and regulations may need to adjust to operate jointly with a regional RA program. The content of this paper may also help the NWPP RA program developer as it interacts with potential member states and utilities to understand what aspects of energy policy may be influenced by the program.This work was funded by the Energy Resilience Division of the U.S. Department of Energy’s Office of Electricity under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.

The risks of long-duration, widespread interruptions (LDWIs) in electrical power are a concern of U.S. regulators, the electric power industry, and stakeholders. Those responsible for making decisions about increasingly costly investments to prevent such interruptions and to facilitate rapid recovery when they do occur need relevant information on which to base those decisions. Although a number of studies have examined the physical and engineering impacts of extreme weather and other precipitating events on the bulk power system, decision makers evaluating investments in preventive strategies need information on the costs of past power interruptions and the benefits of preventing them in the future. This paper contributes to addressing this need by offering six case studies that detail the economics, at the level of the utility service territory, of power interruptions caused by extreme weather and lasting from a few days to several weeks. These intermediate-duration interruptions have been, and will continue to be, the most common type of major electric power disruption. They are longer than the short-term disruptions addressed in utility reliability planning, but not as long or widespread geographically as the national-scale interruptions with durations of many weeks, months, or longer that have been examined in some recent studies. Through case studies, we are able to address the following five questions that have important policy and long-term planning implications for reducing power system vulnerabilities:1. How do utilities assess the costs of system damage caused by extreme weather and the costs of recovering from this damage?2. How do utilities estimate customer costs of past power interruptions?3. How do utilities or others estimate the costs and benefits of investments to reduce power system vulnerabilities to future extreme weather events?4. How do utilities and regulators use the concept of resilience in economic assessments of extreme weather impacts and the value of preventive investments?5. How do regulatory processes influence utilities’ economic analysis related to power interruptions?Finally, the case studies reveal a number of areas in which further research could be beneficial to utilities and regulators dealing with risks associated with LDWIs.

The Indiana Utility Regulatory Commission (IURC) retained LBNL to study the techno-economic impact of distributed energy resource (DER) adoption in the Indiana power system. For this study, LBNL developed a framework that employs a variety of methods to assess three components: the physical impact on distribution, transmission, and generation capacity; the economic and rate impact on customers; and the reliability and resilience impacts on the distribution system.LBNL used utility data from ~2800 distribution system feeders to determine representative feeders that could be used for in-depth analysis. We ran over 3400 simulation-hours on these representative feeders using distribution system simulation software Cymdist, covering a diverse array of DER adoption and net demand scenarios, over the short and long term (2025 and 2040). Feeder-level net demand was scaled up to the state-level and input into a capacity expansion and production cost models to assess the transmission and generation impacts of DER adoption levels and calculate rate impacts. Finally, LBNL used half a million historical outages in Indiana to simulate the impact of DER storage on reliability and resilience.The report finds that voltage regulation, line loading, and energy losses impacts in distribution systems are seldom and largely occur in the most stringent stress-test scenario. Generation impacts account for roughly 80% of the cost impacts in most scenarios. Overall, rates are higher for all DER adoption scenarios compared to the base case given the need to cover utility fixed costs with lower sales, or the need to provide substantial peak capacity to support unmanaged EV charging.

Distributed energy resources have been almost exclusively deployed and operated under a decentralized decision-making process. In this paper, we assess the evolution of a power system with centrally planned utility-scale generation, transmission, distribution, and distributed resources. We adapt a capacity expansion model to represent both centralized and decentralized decision-making paradigms under various electricity rate structures. This paper shows that a centralized planning approach could save 7% to 37% of total system costs over a 15-year time horizon using a Western United States utility as a case study. We show that centralized decision-making deploys substantially more utility-scale solar and distributed storage compared to a decentralized decision-making paradigm. We demonstrate how a utility could largely overcome the complications of decentralized distributed resource decision-making by incentivizing regulators to develop electricity rates that more closely reflect time- and location-specific, long-run marginal costs. The results from this analysis yield insights that are useful for long-term utility planning and electric utility rate design.

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.

Energy savings performance contracting (ESPC) enables building owners to implement facility upgrades and reduce energy and water consumption (often with operations and maintenance expenses) using the resulting annual stream of cost savings to cover project installation and financing costs. The size of the international ESPC market is ~$30 billion per year and growing. However, ESPCs still face myriad barriers to achieving their market potential. Barriers include lack of data standardization and transparency, lost data, and inconsistent project performance monitoring. These barriers have limited stakeholders’ ability to understand how projects perform. The inability to document and quantify past projects’ success has led to skepticism, aversion, and unnecessarily high transaction costs. This work discusses a standardized approach to develop and document ESPCs through eProject Builder (ePB), which involves a simple Excel-based set of financial schedules combined with an on-line data archiving and tracking system. ePB enables standardized collection, calculation and reporting of project data in a way that promotes greater transparency of ESPCs to facility owners and other stakeholders. Specifically, the key benefits of ePB are that it (1) minimizes redundancies; (2) eliminates data inconsistencies resulting from multiple data repositories; (3) increases transparency by preserving and providing access to data in perpetuity; (4) enables development of “what if” scenarios; and (5) standardizes data to allow for comparative analysis of ESPC projects. Accordingly, ePB increases confidence in the ESPC vehicle among prospective customers. The paper demonstrates one key aspect of ePB’s value by using it to conduct sensitivity analyses of key factors in hypothetical ESPC projects.

Load Serving Entities (LSEs) can procure electricity from their owned generation or purchase it on bilateral or centrally organized markets. Electric utility procurement decisions have important implications for resource adequacy, which is gaining attention especially in the Western U.S. However, there is little or no research on trends of utility procurement practices, and the role that wholesale market transactions can have for resource adequacy and other applications. This paper leverages information from the U.S. Department of Energy’s Energy Information Administration, Berkeley Lab’s Resource Planning Portal, and structured interviews with regulatory and utility staff. We find that use of market transactions to meet electric energy needs has been increasing across U.S. LSEs. The reasons for this trend include a general stagnation in building owned resources, a preference towards contracting renewable energy resources to meet RPS targets, and the lower relative cost of wholesale market electricity. Among market transactions across different time scales, short-term transactions were prevalent in Western U.S. LSEs until the 2008 recession, and thereafter declined to about a quarter of total purchases. In contrast, long-term market transactions have become more prevalent and resource planning reports project the share of these transactions in the procurement mix may continue to increase. Results suggest resource adequacy obligations may drive preferences for asset ownership more than a profit incentive. We also recommend improving the planning to procurement connection by reflecting in planning assumptions the operational constraints of market transactions. These results provide insights on key issues in electric utility procurement that could improve overall market efficiency, respond to rapidly changing industry conditions, and identify practices that LSEs and regulators should consider incorporating into their long-term transmission and capacity planning processes.

BackgroundLichens, encompassing 20,000 known species, are symbioses between specialized fungi (mycobionts), mostly ascomycetes, and unicellular green algae or cyanobacteria (photobionts). Here we describe the first parallel genomic analysis of the mycobiont Cladonia grayi and of its green algal photobiont Asterochloris glomerata. We focus on genes/predicted proteins of potential symbiotic significance, sought by surveying proteins differentially activated during early stages of mycobiont and photobiont interaction in coculture, expanded or contracted protein families, and proteins with differential rates of evolution.ResultsA) In coculture, the fungus upregulated small secreted proteins, membrane transport proteins, signal transduction components, extracellular hydrolases and, notably, a ribitol transporter and an ammonium transporter, and the alga activated DNA metabolism, signal transduction, and expression of flagellar components. B) Expanded fungal protein families include heterokaryon incompatibility proteins, polyketide synthases, and a unique set of G-protein α subunit paralogs. Expanded algal protein families include carbohydrate active enzymes and a specific subclass of cytoplasmic carbonic anhydrases. The alga also appears to have acquired by horizontal gene transfer from prokaryotes novel archaeal ATPases and Desiccation-Related Proteins. Expanded in both symbionts are signal transduction components, ankyrin domain proteins and transcription factors involved in chromatin remodeling and stress responses. The fungal transportome is contracted, as are algal nitrate assimilation genes. C) In the mycobiont, slow-evolving proteins were enriched for components involved in protein translation, translocation and sorting.ConclusionsThe surveyed genes affect stress resistance, signaling, genome reprogramming, nutritional and structural interactions. The alga carries many genes likely transferred horizontally through viruses, yet we found no evidence of inter-symbiont gene transfer. The presence in the photobiont of meiosis-specific genes supports the notion that sexual reproduction occurs in Asterochloris while they are free-living, a phenomenon with implications for the adaptability of lichens and the persistent autonomy of the symbionts. The diversity of the genes affecting the symbiosis suggests that lichens evolved by accretion of many scattered regulatory and structural changes rather than through introduction of a few key innovations. This predicts that paths to lichenization were variable in different phyla, which is consistent with the emerging consensus that ascolichens could have had a few independent origins.

Integrated resource planning is an important regulatory process used in many U.S. states to formulate and evaluate least-cost and risk-assessed portfolios to meet future load requirements for electric utilities. In principle, effective implementation of integrated resource planning seeks to assure regulators and the public that utility investment decisions, given uncertainty, are as cost-effective as possible. However, there is no empirical assessment on the effectiveness of integrated resource planning and its implementation. This paper compares planning outcomes and actual decisions for twelve utilities across the Western U. S. from 2003 to 2014. The authors find that subsequent plans differ significantly due to changes in the planning environment, which limited amount of information produced during planning is ultimately used during the procurement process, and that the latter process relies extensively on the most recent information available for decision making. These findings suggest that states' integrated resource planning rules and regulations mandating long-term planning horizons with the same analytical complexity throughout the planning period may not create useful information for the procurement process. The social value of a long-term planning process that departs from procurement and the balance between transparency and complexity of the planning and procurement processes is an open question.

Energy efficiency is widely recognized as a cost-effective strategy to meet energy demand. The U.S. energy service company (ESCO) industry generates significant energy savings and other benefits through installing and maintaining energy efficiency, renewable and other types of projects. In this study, we evaluate factors that may explain trends in the economic performance of U.S. ESCO projects by analyzing project level data for ∼7000 U.S. ESCO industry projects. We find that real project investment levels normalized for floor area have increased over time in ESCO projects across market segments. However, the dollar value of energy savings and other reported benefits have not kept pace with increases in real project investment levels over time. The latter have increased 100%–500% in various market segments from 1990 to 2017. We conduct an econometric analysis to decompose the drivers of these underlying trends. Number of measures and a changing mix of conservation measures are the primary factors that correlate with the long-term increase in project investment levels. However, our analysis is only able to account for less than 50% of the increase in real investment levels. We discuss additional factors, and conclude discussing policy implications and outlining long-term research needs.

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electric utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. We review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.

Host-associated microbial dynamics are influenced by dietary and immune factors, but how exogenous microbial exposure shapes host-microbe dynamics remains poorly characterized. To investigate this phenomenon, we characterized the skin, rectum, and respiratory tract-associated microbiota in four aquarium-housed dolphins daily over a period of 6 weeks, including administration of a probiotic during weeks 4 to 6. The environmental bacterial sources were also characterized, including the animals' human handlers, the aquarium air and water, and the dolphins' food supply. Continuous microbial exposure occurred between all sites, yet each environment maintained a characteristic microbiota, suggesting that the majority of exposure events do not result in colonization. Small changes in water physicochemistry had a significant but weak correlation with change in dolphin-associated bacterial richness but had no influence on phylogenetic diversity. Food and air microbiota were the richest and had the largest conditional influence on other microbiota in the absence of probiotics, but during probiotic administration, food alone had the largest influence on the stability of the dolphin microbiota. Our results suggest that respiratory tract and gastrointestinal epithelium interactions with air- and food-associated microbes had the biggest influence on host-microbiota dynamics, while other interactions, such as skin transmission, played only a minor role. Finally, direct oral stimulation with a foreign exogenous microbial source can have a profound effect on microbial stability. IMPORTANCE These results provide valuable insights into the ecological influence of exogenous microbial exposure, as well as laying the foundation for improving aquarium management practices. By comparing data for dolphins from aquaria that use natural versus artificial seawater, we demonstrate the potential influence of aquarium water disinfection procedures on dolphin microbial dynamics.

Utilities are constantly making improvements to their infrastructure and operating protocols to maintain or enhance the reliability and resilience of the electric grid. Customer interruption cost (CIC) estimates are useful in assessing and monetizing the economic benefits customers receive from these improvements. This Guidebook for electric utilities explains how to conduct customer interruption cost studies and describes commonly-used, value-based planning methods. The authors intend that this Guidebook will serve as a reference for utility personnel, policymakers and experts in survey design and administration who may be planning to implement CIC studies. It brings the utility industry up-to-date using modern survey technologies, practices, and data analytics to estimate CICs and, ultimately, use the estimates to address both traditional and emerging planning needs.

In March 2018, Lawrence Berkeley National Laboratory (LBNL) and Nexant released a significant upgrade of the Interruption Cost Estimate (ICE) Calculator. While most of the improvements involved a modernization of the user interface, there are two notable modifications to the underlying econometric models. LBNL and Nexant documented the original models and customer interruption cost meta-analysis in a 2009 report. They subsequently revised the meta-analysis and econometric models for the ICE Calculator in 2015, as documented in an updated report. The models for the current version of the ICE Calculator are based on two additional modifications summarized in this update.

This analysis integrates regional models of power system reliability, output from atmosphere-ocean general circulation models, and results from the Interruption Cost Estimate (ICE) Calculator to project long-run costs to electric utility customers from power interruptions under different future severe weather and electricity system scenarios. We discuss the challenges when attempting to model long-run costs to utility customers including the use of imperfect metrics to measure severe weather. Despite these challenges, initial findings show that discounted cumulative customer costs, through the middle of the century, could range from $1.5-$3.4 trillion ($2015) without aggressive undergrounding of the power system and increased utility operations and maintenance (O&M) spending and $1.5-$2.5 trillion with aggressive undergrounding and increased spending. By the end of the century, cumulative customer costs could range from $1.9-$5.6 trillion (without aggressive undergrounding and increased spending) and $2.0-$3.6 trillion (with aggressive undergrounding and increased spending). We find that, in some scenarios, aggressive undergrounding of distribution lines and increased O&M spending is not always cost-effective. We conclude by identifying important topics for follow-on research, which have the potential to improve the cost estimates of this model.

The microorganisms that inhabit hospitals may influence patient recovery and outcome, although the complexity and diversity of these bacterial communities can confound our ability to focus on potential pathogens in isolation. To develop a community-level understanding of how microorganisms colonize and move through the hospital environment, we characterized the bacterial dynamics among hospital surfaces, patients, and staff over the course of 1 year as a new hospital became operational. The bacteria in patient rooms, particularly on bedrails, consistently resembled the skin microbiota of the patient occupying the room. Bacterial communities on patients and room surfaces became increasingly similar over the course of a patient's stay. Temporal correlations in community structure demonstrated that patients initially acquired room-associated taxa that predated their stay but that their own microbial signatures began to influence the room community structure over time. The α- and β-diversity of patient skin samples were only weakly or nonsignificantly associated with clinical factors such as chemotherapy, antibiotic usage, and surgical recovery, and no factor except for ambulatory status affected microbial similarity between the microbiotas of a patient and their room. Metagenomic analyses revealed that genes conferring antimicrobial resistance were consistently more abundant on room surfaces than on the skin of the patients inhabiting those rooms. In addition, persistent unique genotypes of Staphylococcus and Propionibacterium were identified. Dynamic Bayesian network analysis suggested that hospital staff were more likely to be a source of bacteria on the skin of patients than the reverse but that there were no universal patterns of transmission across patient rooms.

Oceanic microbial diversity covaries with physicochemical parameters. Temperature, for example, explains approximately half of global variation in surface taxonomic abundance. It is unknown, however, whether covariation patterns hold over narrower parameter gradients and spatial scales, and extending to mesopelagic depths. We collected and sequenced 45 epipelagic and mesopelagic microbial metagenomes on a meridional transect through the eastern Red Sea. We asked which environmental parameters explain the most variation in relative abundances of taxonomic groups, gene ortholog groups, and pathways-at a spatial scale of

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.

There has been a general shortfall of peer-reviewed literature identifying methods to estimate the costs and benefits of strategies employed by electric utilities to improve grid resilience. This paper introduces—for the first time—a comprehensive analysis framework to estimate the societal costs and benefits of implementing one strategy to improve power system reliability: undergrounding power transmission and distribution lines. It is shown that undergrounding transmission and distribution lines can be a cost-effective strategy to improve reliability, but only if certain criteria are met before the decision to underground is made.

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.

Key highlights from U.S. Energy Service Company (ESCO) Industry: Recent Market Trends•After more than two decades of year-over-year growth, ESCO industry revenues appeared to flatten between 2011 and 2014. ESCOs reported 2014 industry revenue of approximately $5.3 billion, the same as revenues reported in 2011. •Based on ESCOs’ 3-year growth projections, ESCOs expect total annual industry revenues to be approximately $7.6 billion for 2017, which equates to an average annual growth rate of ~13% for the three years 2015-2017.•Public and institutional market sectors accounted for 85% of industry revenue in 2014, which is consistent with previous study findings.•Performance contracting generated 75% ($3.7 billion) of industry revenue in 2014, which is somewhat higher than the 69% share for performance contracting reported in 2011 and 2008. Design-build projects contributed the next largest share of 2014 revenue (16% or ~$800 million), followed distantly by consulting services (5%), onsite generation power purchase agreements (3%) and other activities (2%).•The share of industry revenue contributed by large ESCOs (annual energy services revenue of $300M or greater) declined somewhat between 2011 and 2014. Accordingly, medium-sized ESCOs as a group (annual revenue between $100M and $299M) increased market share from 29% in 2011 to 33% in 2014. Small ESCOs (annual revenue

Implementation of carbon capture and sequestration (CCS) will increase water demand due to the cooling water requirements of CO2 capture equipment. If the captured CO2 is injected into saline aquifers for sequestration, brine may be extracted to manage the aquifer pressure, and can be desalinated to provide additional freshwater supply. We conduct a geospatial analysis to determine how CCS may affect local water supply and demand across the contiguous United States. We calculate baseline indices for each county in the year 2005, and project future water supply and demand with and without CCS through 2030. We conduct sensitivity analyses to identify the system parameters that most significantly affect water balance. Water supply changes due to inter-annual variability and projected climate change are overwhelmingly the most significant sources of variation. CCS can have strong local effects on water supply and demand, but overall it has a modest effect on water balances.

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km(2)) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value

The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over 6 weeks were assessed, including three families that moved their home. Microbial communities differed substantially among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens observed on a kitchen counter could be matched to the hands of occupants. After a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants' former house, suggesting rapid colonization by the family's microbiota.

The U.S. energy service company (ESCO) industry is an example of a private sector business model where energy savings are delivered to customers primarily through the use of performance-based contracts. This study was conceived as a snapshot of the ESCO industry prior to the economic slowdown and the introduction of federal stimulus funding mandated by enactment of the American Recovery and Reinvestment Act of 2009 (ARRA). This study utilizes two parallel analytic approaches to characterize ESCO industry and market trends in the U.S.: (1) a ?top-down? approach involving a survey of individual ESCOs to estimate aggregate industry activity and (2) a ?bottom-up? analysis of a database of ~;;3,250 projects (representing over $8B in project investment) that reports market trends including installed EE retrofit strategies, project installation costs and savings, project payback times, and benefit-cost ratios over time. Despite the onset of a severe economic recession, the U.S. ESCO industry managed to grow at about 7percent per year between 2006 and 2008. ESCO industry revenues were about $4.1 billion in 2008 and ESCOs anticipate accelerated growth through 2011 (25percent per year). We found that 2,484 ESCO projects in our database generated ~;;$4.0 billion ($2009) in net, direct economic benefits to their customers. We estimate that the ESCO project database includes about 20percent of all U.S. ESCO market activity from 1990-2008. Assuming the net benefits per project are comparable for ESCO projects that are not included in the LBNL database, this would suggest that the ESCO industry has generated ~;;$23 billion in net direct economic benefits for customers at projects installed between 1990 and 2008. There is empirical evidence confirming that the industry is evolving by installing more comprehensive and complex measures?including onsite generation and measures to address deferred maintenance?but this evolution has significant implications for customer project economics, especially at K-12 schools. We found that the median simple payback time has increased from 1.9 to 3.2 years in private sector projects since the early-to-mid 1990s and from 5.2 to 10.5 years in public sector projects for the same time period.

This paper evaluates the issue of non-energy benefits within the context of the U.S. energyservices company (ESCO) industry?a growing industry comprised of companies that provide energy savings and other benefits to customers through the use of performance-based contracting. Recent analysis has found that ESCO projects in the public/institutional sector, especially at K-12 schools, are using performance-based contracting, at the behest of the customers, to partially -- but not fully -- offset substantial accumulated deferred maintenance needs (e.g., asbestos removal, wiring) and measures that have very long paybacks (roof replacement). This trend is affecting the traditional economic measures policymakers use to evaluate success on a benefit to cost basis. Moreover, the value of non-energy benefits which can offset some or all of the cost of the non-energy measures -- including operations and maintenance (O&M) savings, avoided capital costs, and tradable pollution emissions allowances-- are not always incorporated into a formal cost-effectiveness analysis of ESCO projects. Nonenergybenefits are clearly important to customers, but state and federal laws that govern theacceptance of these types of benefits for ESCO projects vary widely (i.e., 0-100percent of allowable savings can come from one or more non-energy categories). Clear and consistent guidance on what types of savings are recognized in Energy Savings agreements under performance contracts is necessary, particularly where customers are searching for deep energy efficiency gains in the building sector.

This report outlines the results of a study of the impact of climate change on the energy infrastructure of California and the San Francisco Bay region, including impacts on power plant generation; transmission line and substation capacity during heat spells; wildfires near transmission lines; sea level encroachment upon power plants, substations, and natural gas facilities; and peak electrical demand. The following end-of-century impacts were projected: Expected warming will decrease gas-fired generator efficiency. The maximum statewidecoincident loss is projected at 10.3 gigawatts (with current power plant infrastructureand population), an increase of 6.2 percent over current temperature-induced losses. By the end of the century, electricity demand for almost all summer days is expected toexceed the current ninetieth percentile per-capita peak load. As much as 21 percent growth is expected in ninetieth percentile peak demand (percapita, exclusive of population growth). When generator losses are included in thedemand, the ninetieth percentile peaks may increase up to 25 percent. As the climate warms, California’s peak supply capacity will need to grow faster thanthe population. Substation capacity is projected to decrease an average of 2.7 percent. A 5º Celsius (9º Fahrenheit) air temperature increase (the average increase predicted forhot days in August) will diminish the capacity of a fully loaded transmission line by anaverage of 7.5 percent. The potential exposure of transmission lines to wildfire is expected to increase withtime. This study identified some lines whose probability of exposure to fire are expectedto increase by as much as 40 percent. Up to 25 coastal power plants and 86 substations are at risk of flooding (or partialflooding) due to sea level rise.