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At least 37 records · Page 2

The Future of U.S. Electricity Efficiency Programs Funded by Utility Customers: Program Spending and Savings Projections to 2030

Electric utility customers spent about $5.8 billion on energy efficiency programs in 2016 to cost-effectively offset a portion of growth in U.S. power needs. That, in turn, affects the need for investment in new electricity infrastructure, across generation, transmission and distribution systems. A new study by Berkeley Lab provides a bottom-up assessment of the potential impact of existing and likely state policies and market conditions to promote or constrain future spending and savings for electricity efficiency programs funded by utility customers in all U.S. states.

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Beyond Widgets -- Systems Incentive Programs for Utilities

Utility incentive programs remain one of the most significant means of deploying commercialized, but underutilized building technologies to scale. However, these programs have been largely limited to component-based products (e.g., lamps, RTUs). While some utilities do provide ‘custom’ incentive programs with whole building and system level technical assistance, these programs require deeper levels of analysis, resulting in higher program costs. This results in custom programs being restricted to utilities with greater resources, and are typically applied mainly to large or energy-intensive facilities, leaving much of the market without cost effective access and incentives for these solutions. In addition, with increasingly stringent energy codes, cost effective component-based solutions that achieve significant savings are dwindling. Building systems (e.g., integrated façade, HVAC and/or lighting solutions) can deliver higher savings that translate into large sector-wide savings if deployed at the scale of these programs. However, systems application poses a number of challenges – baseline energy use must be defined and measured; the metrics for energy and performance must be defined and tested against; in addition, system savings must be validated under well understood conditions. This paper presents a sample of findings of a project to develop validated utility incentive program packages for three specific integrated building systems, in collaboration with Xcel Energy (CO, MN), ComEd, and a consortium of California Public Owned Utilities (CA POUs) (Northern California Power Agency(NCPA) and the Southern California Public Power Authority(SCPPA)). Furthermore, these program packages consist of system specifications, system performance, M&V protocols, streamlined assessment methods, market assessment and implementation guidance.

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Multi-technology building system retrofits for utility incentive programs: Savings, costs and baseline considerations

Utility incentive programs are an important channel to support the deployment of energy efficiency in buildings. To date, these programs have largely been limited to single-component strategies. However, many utilities are now motivated to identify and develop multi-component system retrofits to achieve deeper energy savings, which are essential to achieving broader energy and greenhouse gas reduction goals in the buildings sector. In this paper we present the energy savings, demand reductions, and cost-effectiveness of 16 systems retrofit packages in six utility regions in the United States. These results are being used by these utilities to inform and develop incentive programs for systems retrofits. Our analysis shows that packages with proven lighting and HVAC measures can provide 5–22% whole building annual energy savings, and 13–22% annual energy costs savings, using utility incentive program baselines (code and existing building). The packages are reasonably cost effective for replace-on-burnout but generally not for a retrofit scenario prior to end of equipment life. Demand response can increase both the energy savings and energy cost savings, further improving the cost effectiveness of these packages. We analyzed the impact of using existing building vs. code baselines for calculating savings, showing that the choice of baseline in developing utility incentive programs has a substantial impact on the attributable energy savings to a program, with significant implications for the overall viability of a program (generally savings against existing building condition are higher and improve project and program cost-effectiveness).

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Building commissioning costs and savings across three decades and 1500 North American buildings

B.V. Building commissioning (Cx) is a process for assuring efficient building operations that can be applied to new construction and existing buildings, resulting in energy and non-energy benefits. Quantifying the benefits of commissioning is challenging, but a 2009 study of 643 commercial buildings provided a solid initial data set to which we added 839 additional buildings for a significantly expanded and updated meta-analysis representing 34.7 million square meters (373 million square feet) of floor area. Since 2009 the commissioning industry has continued to grow, driven by building codes, utility programs, and rising awareness of commissioning benefits. In parallel, building controls have become more sophisticated, and analytics software has emerged to assist with commissioning. We find that delivery mechanism and market segment are key determinants of outcomes, although significant and cost-effective savings are found across the spectrum. Median primary energy savings for Cx projects in existing buildings ranged from 5 percent for those conducted under utility programs, 9 percent for monitoring-based commissioning utility programs (i.e., augmented with submetering and diagnostics), and 14 percent for Cx projects outside of utility programs. Across all project types, median savings ranged from 3 percent for the lodging market segment to 16 percent for public order and safety facilities. Outcomes did not vary significantly by building size or by market segment. Energy savings are rarely estimated for new construction commissioning. We found that the median costs of Cx were lower for the 2018 sample than for the 2009 sample—$\$$2.85 per square meter ($\$$0.26 per square foot) for existing buildings (a 33 percent reduction) and $\$$8.78 per square meter ($\$$0.82 per square foot) for new construction (a reduction of almost 50 percent). The median simple payback time for existing buildings was 1.7 years, with a 25th–75th percentile range of 0.8–3.5 years. Overall, this article summarizes these and other key findings, and discusses how the 2018 data reflects shifts in commissioning practice and outcomes.

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Implications of a regional resource adequacy program on utility integrated resource planning: Study for the Western United States

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. This report is focused on an active policy discussion to develop a novel voluntary program to share capacity resource 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 calculation: (1) variable renewable resources, (2) demand-side resources, (3) hydropower, and (4) contracts. It will then 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 not be significantly impacted. The report includes (i) a review of traditional resource adequacy practices in IRP; (ii) a case study of an existing regional RA program that interacts with IRP (Southwest Power Pool) and (iii) an overview of the NWPP regional resource adequacy proposal that is the object of this work. This paper does not (1) advocate for or against a regional RA program for the NWPP, (2) make detailed design recommendations for this program, or (3) assess its benefits and costs.

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DOE Voluntary Partnership Program with Utilities and Local Governments Supports the Design of New Data Access Solutions

The Better Buildings Energy Data Accelerator (BBEDA) is a unique effort that has supported 22 pairs of local governments and their utility companies to help building owners gain access to their whole-building energy data. Municipal and Utility BBEDA Partners committed to develop streamlined and easy-to-use solutions to provide whole-building energy data, especially for multitenant commercial buildings, by the end of 2015. As a result, building owners would be able to make data-driven decisions about their buildings by utilizing readily available energy consumption data for entire buildings. Traditionally, data access was difficult to implement due to technical barriers and the lack of clear value propositions for the utilities. During the past two years, BBEDA has taken a hands-on approach to overcome these barriers by offering a platform for the partners to discuss their challenges and solutions. Customized support was also provided to Partners building their local strategies. Based on the lessons learned from the partners, BBEDA developed a final toolkit with guiding documents that addressed key barriers and served as a resource for the other cities and utilities attempting to establish whole-building data access, including an exploration of opportunities to apply the whole-building data to various aspects of utility demand-side management (DSM) programs. BBEDA has been a catalyst for market transformation by addressing the upstream (to efficiency implementation) barrier of data access, demonstrated through the success of the BBEDA partners to address policy, engagement, and technical hurdles and arrive at replicable solutions to make data access a standard practice nationwide. As a result of best practices identified by the BBEDA, 18 utilities serving more than 2.6 million commercial customers nationwide will provide whole-building energy data access to building owners by 2017. This historic expansion of data accessibility will increase building energy benchmarking, the first step many building owners take to improve the energy efficiency of their buildings.

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Processing Meteorological Data for the CAP-88 PC Model at Los Alamos National Laboratory

The Environmental Protection and Compliance-Compliance Programs (EPC-CP) group at Los Alamos National Laboratory (LANL) uses the Clean Air Act Assessment Package 1988 (CAP-88, Littleton 2020) PC model (Version 4.1) to estimate radiological doses for a set of areal sectors surrounding a release location, in order to satisfy the Environmental Protection Agency (EPA) National Emission Standards for Hazardous Air Pollutants (NESHAP) dose calculation requirement in 40 CFR 61 Subpart H. Among several types of data that must be prepared for CAP-88 input is a text file of meteorological data (“WIND” file), consisting of the joint frequency of wind direction, wind speed, and atmospheric stability categories. EPC-CP produces customized WIND files by running a CAP-88 utility program on a user generated text file of wind data in a different format, known as a STability ARray (STAR) file (Turner, 1964). At LANL, EPC-CP meteorologists prepare customized STAR files with data over desired time periods at selected meteorological towers. A custom program written in Precision Visuals -Workstation Analysis and Visualization Environment (PV-WAVE), a commercial Fortran-like language, is used to read LANL meteorological data and write a STAR file; the executable filename is “Star.out”. However, the outdated PV-WAVE utility program is being phased out by EPC-CP, due to the inefficient process to run it and an inability to modify the code. To preserve the ability to create customized meteorological data for CAP-88 in a way that will be easy to use and maintain, a new replacement utility program, written in the Python programming language, has been developed. The new, improved program reads a data file from any LANL meteorological tower, and at each desired observation time, determines the wind direction, wind speed, and stability categories defined in the CAP-88 documentation. The frequencies of all combinations of the three sets of categories are calculated and written to a file in the STAR format, which can later be converted to a WIND file for input into CAP-88.

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Chapter 17: Residential Behavior Evaluation Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures, September 2011 - August 2020

This document has been updated in August 2020. This document was developed for the U.S. Department of Energy Uniform Methods Project (UMP). The UMP provides model protocols for determining energy and demand savings that result from specific energy-efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The protocols are updated on an as-needed basis. The UMP protocols can be used by utilities, program administrators, public utility commissions,evaluators, and other stakeholders for both program planning and evaluation. To learn more about the UMP, visit the website, https://energy.gov/eere/about-us/ump-home, or download the UMP introduction document at http://www.nrel.gov/docs/fy17osti/68557.pdf.

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OpenStudio: A Platform for Ex Ante Incentive Programs

Many utilities operate programs that provide ex ante (up front) incentives for building energy conservation measures (ECMs). A typical incentive program covers two kinds of ECMs. ECMs that deliver similar savings in different contexts are associated with pre-calculated 'deemed' savings values. ECMs that deliver different savings in different contexts are evaluated on a 'custom' per-project basis. Incentive programs often operate at less than peak efficiency because both deemed ECMs and custom projects have lengthy and effort-intensive review processes--deemed ECMs to gain confidence that they are sufficiently context insensitive, custom projects to ensure that savings are claimed appropriately. DOE's OpenStudio platform can be used to automate ex ante processes and help utilities operate programs more efficiently, consistently, and transparently, resulting in greater project throughput and energy savings. A key concept of the platform is the OpenStudio Measure, a script that queries and transforms building energy models. Measures can be simple or surgical, e.g., applying different transformations based on space-type, orientation, etc. Measures represent ECMs explicitly and are easier to review than ECMs that are represented implicitly as the difference between a with-ECM and without-ECM models. Measures can be automatically applied to large numbers of prototype models--and instantiated from uncertainty distributions--facilitating the large scale analysis required to develop deemed savings values. For custom projects, Measures can also be used to calibrate existing building models, to automatically create code baseline models, and to perform quality assurance screening.

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The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

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Status and Trends in the U.S. Voluntary Green Power Market (2015 Data)

The voluntary green power market refers to the sale and procurement of renewable energy for voluntary purposes by residential and commercial customers. This report reviews seven green power procurement mechanisms: utility green pricing programs, utility green tariffs, voluntary unbundled renewable energy certificates, competitive supplier green power, community choice aggregations, voluntary power purchase agreements (PPAs), and community solar. This report details the status of trends of those seven green power procurement mechanisms in 2015. Three trends -- significant growth of the voluntary PPA project pipeline, innovative green power mechanisms developed by utilities, and geographic expansion of green power mechanisms -- suggest that the green power market is likely to continue to grow in coming years.

2015↗

Status and Trends in the U.S. Voluntary Green Power Market (2016 Data)

Annual report of sales and number of customers in voluntary green power markets, including utility green pricing programs, utility green partnerships, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

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State of the Voluntary Green Power Market (2016 Data)

Annual report of sales and number of customers in voluntary green power markets, including utility green pricing programs, utility green partnerships, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

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Status and Trends in the U.S. Voluntary Green Power Market (2017 Data)

Green power refers to renewable electricity voluntarily purchased by retail electricity customers. Renewable energy sources for green power include solar, wind, biomass, geothermal, and small-scale hydropower. This report summarizes data on the various ways in which voluntary purchasers - including residential, commercial, and institutional customers - purchase green power. We summarize key historic trends in U.S. voluntary green power markets and the current status of green power sales through seven products: utility green pricing programs, utility renewable contracts, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

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State of the Voluntary Green Power Market

Green power refers to renewable electricity voluntarily purchased by retail electricity customers. Renewable energy sources for green power include solar, wind, biomass, geothermal, and small-scale hydropower. This presentation summarizes data on the various ways in which voluntary purchasers - including residential, commercial, and institutional customers - purchase green power. We summarize key historic trends in U.S. voluntary green power markets and the current status of green power sales through seven products: utility green pricing programs, utility renewable contracts, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Status and Trends in the Voluntary Market (2018 Data)

Green power refers to renewable electricity voluntarily purchased by retail electricity customers. Renewable energy sources for green power include solar, wind, biomass, geothermal, and small-scale hydropower. This report summarizes data on the various ways in which voluntary purchasers - including residential, commercial, and institutional customers - purchase green power. We summarize key historic trends in U.S. voluntary green power markets and the current status of green power sales through seven products: utility green pricing programs, utility renewable contracts, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Status and Trends in the Voluntary Market (2019 Data)

Green power refers to renewable electricity voluntarily purchased by retail electricity customers. Renewable energy sources for green power include solar, wind, biomass, geothermal, and small-scale hydropower. This report summarizes data on the various ways in which voluntary purchasers - including residential, commercial, and institutional customers - purchase green power. We summarize key historic trends in U.S. voluntary green power markets and the current status of green power sales through seven products: utility green pricing programs, utility renewable contracts, competitive suppliers, unbundled renewable energy certificates, community choice aggregations, power purchase agreements, and community solar.

42 ENGINEERING↗