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DOE OSTI2023

Predictive model for real-time energy disaggregation using long short-term memory

To provide affordable energy-saving solutions for the small and medium-sized manufacturers (SMMs), we propose a unified framework for generating predictive models that support real-time disaggregation of power consumption from combined inputs, enabling automatic machine state identification simultaneously for joint analysis of energy usage patterns. Further, the proposed framework transforms raw power consumption into a time series with look-back and bootstrap capabilities for historical pattern detection, while a learning architecture utilizes the stacked long short-term memory (LSTM) layers as encoders for embedding generation with sequential awareness. Experimental results demonstrate 93.65% minimum accuracy in ideal case of real-time energy usage and machine state prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

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.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Predicting the Impact of Utility Lighting Rebate Programs on Promoting Industrial Energy Efficiency: A Machine Learning Approach

Implementation costs are a major factor in manufacturers’ decisions to invest in energy-efficient technologies. Emerging technologies in lighting systems, however, typically require small investment costs and offer short, simple payback periods, due, in part, to federal, state, and utility incentive programs. Recently, however, certain state and federal mandates have reduced the support for and efficacy of electricity utility incentivizing programs. To determine the impact of such support programs, this study examined historical data regarding lighting retrofit savings, implementation costs, and utility rebates gathered from 13 years of industrial energy audits by a U.S. Department of Energy Industrial Assessment Center in a midwestern state. It uses a machine learning approach to evaluate the industrial energy and cost-saving opportunities that may have been lost due to decisions attributable to legislative mandates, utility policies, and manufacturers’ calculations and to evaluate the potential effect of lighting rebates on manufacturers’ decisions to implement industrial energy-efficient lighting retrofits. The results indicate that the decision not to implement lighting energy efficiency recommendations resulted in a loss of more than USD800,000 in potential rebates by industries during the study period and that the implementation of lighting energy assessment recommendations could have increased by about 50% if electric utility rebates had been available. These findings can help industries evaluate the benefits of implementing lighting efficiency improvements, and help utilities determine feasible lighting retrofit rebate values for incentivizing such changes by the industries they serve.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Driving Affordable Decarbonization: Inclusive Utility Program Designs for Disadvantaged Communities

Our research team worked with 17 utility partners from various U.S. regions to study current utility program practices. We identified the key characteristics of these programs and the challenges and opportunities in implementing them. Through our research, we provide a pragmatic, design-oriented, and customer-centered perspective for effective program design and implementation. We identify 13 successful characteristics of program design that may be considered by utility partners.

disadvantaged communities↗

DOE OSTI2024

A Systematic Approach to Developing Sustainable Post-Disaster Shelters in the Southern Region of the United States

This study aims to propose a sustainable shelter design involving energy savings, less environmental impact, and rapid construction. The structural design of the shelter is based on 3D-printing technology. Sustainability assessments, including life cycle analysis (LCA), life cycle energy assessment (LCEA), and energy justice of the designed shelter, were conducted to prove the sustainable shelter design. The outcomes of this study for several scenarios will not only allow decision-makers to design permanent shelters with maximized utilization of limited resources but also help local communities strengthen their ability to recover with minimal outside assistance post-disaster. Furthermore, residents can utilize the sustainable shelter to maintain critical functions, including business continuity and local business in emergencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

A System Approach to Deep Heating Savings Through Measurement, Management, and Motivation

Across multi-tenant commercial office and multifamily buildings, centrally metered fuel use represents a substantial fraction of whole-building energy use. Energy audit practitioners understand that improving heating distribution efficiency is typically more of an opportunity than combustion efficiency and that differing thermal comfort preferences between tenants are the bane of operators across these building typologies. There is an unmet market need for retrofit technologies that allow for the delivery of the right amount of heat to the right spaces, at the right time. The Energy Management and Information System (EMIS) package fills this gap through enhanced controls and metering, incorporating low-cost sensors and wireless communication infrastructure to provide a platform for ongoing commissioning and tenant feedback, including heat cost allocation. With support from the US DOE Building Technologies Office, Steven Winter Associates, Inc. (SWA) partnered with Sentient Buildings, E Source, building owners, and utility and policy stakeholders, to demonstrate a market viable EMIS that achieves a reduction in space heating energy use by reducing heating load, improving control, and positively impacting behavior while providing an acceptable financial return. In this study, EMIS packages were implemented in two New York City multifamily rental buildings. Both buildings conducted basic mechanical work (e.g., repairing steam traps) to ensure the heating system was operating well before any tenant feedback was layered in. Heating Energy Use Reports (HEUR) were created to provide tenants with social comparisons and energy savings tips to influence their behavior; these were provided monthly to all tenants in both buildings. Additionally, one building allocated heating costs to a portion of the tenants. Heat cost allocation (HCA) has a long history in the European Union (EU), although it is not common in the US or in steam-heated buildings. SWA leveraged existing EU best practices and stakeholder feedback to develop a Heat Cost Allocation algorithm that was considered equitable and intuitive. Energy use and tenant behavior impacts were tracked throughout the study. The basic mechanical repair work saved between 11-20% of heating energy. Those savings rose to 17-24% with the addition of tenant feedback. While it may not be possible to precisely determine the impact of COVID-19 on research studies like this, there may have been additional savings realized had the study taken place in a period of normal occupancy patterns. These types of central heating systems have been a blind spot for utilities, who have traditionally had little visibility into detailed behind-the-meter gas usage. Heating energy savings stayed consistent during the coldest months, indicating the potential for utilities to utilize EMIS packages for peak gas demand reductions or demand response programs. Tenant comfort was also improved. Post installation, room temperatures more closely matched thermostat set points. Perhaps due to this greater level of control, the vast majority of tenants being billed for heating were accepting of the allocation costs. And tenants receiving heat cost allocations were more likely to reduce their thermostat setpoints than tenants receiving behavioral feedback without financial impacts were. Variation in building specifics makes it difficult to provide precise energy and financial savings estimates. But within the range of expected conditions, the study identified a few key variables that can have the greatest impact on financial returns: the cost of fuel, the ability and willingness to allocate heating costs to tenants, and a well-functioning heating system as a starting point. This study focused on two multifamily buildings, but additional use cases, such as commercial buildings and affordable housing, should be explored to better understand the full market potential. While this type of upgrade has the potential for deep energy reductions and cost savings, future projects should take into account the balance of costs and benefits between owners and tenants, especially in the affordable, regulated, or other low-to-moderate income (LMI) segments of the market. Rent credits, utility allowances, or a shared savings program are possible options to accelerate adoption of this strategy in these market segments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗

DOE OSTI2021

From occupants to occupants: A review of the occupant information understanding for building HVAC occupant-centric control

Occupants are the core of the built environment. Traditional Heating, Ventilation, and Air-Conditioning (HVAC) systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information. These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort. In recent years, with the aid of Information & Communication Technology (ICT) and Computer Science (CS), it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment. This mechanism is called HVAC “Occupant-centric Control (OCC).” HVAC OCC strategy starts with collecting the occupant’s information (e.g., presence/absence) and then applies it to meet the occupant’s requirement (e.g., thermal comfort). However, even though some research studies and field pilot demonstrations have been devoted to the field of OCC, there is a lack of systematic knowledge about occupant data, which is the principal component of OCC for HVAC researchers and practitioners. To fill this gap, this review paper discusses OCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time. Finally, we provide a fine-grained, comprehensive picture of occupant information, discuss its features, the modalities of information feed-in into the HVAC control, and the application of commonly utilized occupant information for OCC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

High Efficiency Heat Pumps Can Pave the Path for Building Decarbonization in Cold Climates: Preprint

Heat pumps play an instrumental role in buildings decarbonization strategies. Recent advances in heat pump systems employ variable-speed compressor technology and electronically commutated fan motors. Inherently, the heating capacity and efficiency of heat pumps decrease with falling outdoor temperatures. Compared to single-speed heat pumps, variable speed systems can maintain higher heating and cooling efficiencies over a wider range of outdoor temperatures. The goal of this multi-phase project was to determine the energy savings of a high efficiency, variable-speed, air-source, split system heat pump designed for cold climate applications. The first project phase was to evaluate the performance of the heat pump in the laboratory under varying outdoor conditions in heating and cooling modes. The second phase was to translate the laboratory-measured performance into lookup tables for EnergyPlus hourly building simulation engine. Then, two sets of annual building simulations were performed using typical meteorological year weather from the Chicago-O'Hare airport for three different building types (a single-family residence, a strip mall, and a low-rise office building). The first set simulated a standard efficiency heat pump while the second set utilized the phase two performance tables to model a high efficiency heat pump. The high efficiency heat pump produced significant annual heating energy savings in all three buildings. The variable speed compressor and fan control also contributed to cooling energy savings. The simulated annual energy savings ranged from 22% to 35% over their respective baseline. The project's findings helped a Midwest electric utility, Commonwealth Edison (ComEd), design new incentives around high efficiency heat pumps.

cold climate heat pump↗

DOE OSTI2021

Energy Analysis: Ways to Save Energy and Reduce the Emissions in Wastewater Treatment Plants

The key of this study is to explore the primary energy consumers in wastewater treatment plants, which is considered as one of the major energy consumers, and introduces the best solution to save energy and reduce emissions in these facilities. This study is based on the energy assessment and analyses of eleven wastewater treatment plants. Through the investigation, it was found that plants can save up to 44,158 MWh of the energy consumption which is 47% from the total electricity consumption with a 17% reduction in the total utility bills and that about 2.5 million dollars cost savings after reviewing the currently facilitated energy system. Additionally, an average of five years' payback period resulted in most energy-saving recommendations. A vast potential of greenhouse gas emissions can be reduced with a total range reduction between 13 to 35 million kg of CO 2 based on the speed reduction percentage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Inequalities in global residential cooling energy use to 2050

Intersecting socio-demographic transformations and warming climates portend increasing worldwide heat exposures and health sequelae. Cooling adaptation via air conditioning (AC) is effective, but energy-intensive and constrained by household-level differences in income and adaptive capacity. Using statistical models trained on a large multi-country household survey dataset (n = 673,215), we project AC adoption and energy use to mid-century at fine spatial resolution worldwide. Globally, the share of households with residential AC could grow from 27% to 41% (range of scenarios assessed: 33-48%), implying up to a doubling of residential cooling electricity consumption, from 1220 to 1940 (scenarios range: 1590-2377) terawatt-hours yr. –1 , emitting between 590 and 1,365 million tons of carbon dioxide equivalent (MtCO 2 e). AC access and utilization will remain highly unequal within and across countries and income groups, with significant regressive impacts. Up to 4 billion people may lack air-conditioning in 2050. Our global gridded projections facilitate incorporation of AC’s vulnerability, health, and decarbonization effects into integrated assessments of climate change.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort Evaluating and Prioritizing Municipal Buildings for Energy Efficiency and Decarbonization Investment

The National Renewable Energy Laboratory (NREL), with support from World Resources Institute (WRI), designed and led a six-month peer-learning cohort from January through July 2024 on "Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids" as part of the U.S Department of Energy's Clean Energy to Communities (nrel.gov/c2c) (C2C) program. Representatives from 15 municipalities, municipal utilities, colleges, and Tribes from across the United States participated in monthly workshops covering best practices for planning and deploying local resilience projects. This document shares key takeaways, lessons learned, and resources from the cohort.

buildings↗

DOE OSTI2020

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗

DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate

In residential buildings, rapid improvements in sensors, communication, and information technology have enabled occupancy-based building controls. These controls utilize occupancy information and modify the operation of the heating, ventilation, and air-conditioning (HVAC) system to minimize excess HVAC energy use, especially when the building is unoccupied. This reduces the total building energy consumption and utility bills while maintaining thermal comfort. In this paper, we present two novel occupancy-driven controls - reactive control and predictive control - and compare their performance. We model an all-electric residential community based on a 27- home community in Basalt, Colorado, in the United States. We simulated various scenarios, considering different temperature setback and control algorithms, to analyze the community-scale impact of these occupancy-based controls. The results show that total HVAC energy savings in a building ranges from 1%- 20% compared to the baseline scenario without occupancy-based controls. The energy-saving potential is highly correlated with the occupancy pattern and temperature setback in the building.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate: Preprint

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2020

Guidance and Recommendations for Streamlining Reporting for Federal Energy and Water Efficiency Projects

Federal agencies are required to report on their progress in meeting various energy and water management requirements. These reporting requirements encompass energy and water projects at federal facilities, including projects that are alternatively financed, e.g., conducted through energy savings performance contracts (ESPCs) or utility energy service contracts (UESCs). The purpose of this guidance is to provide recommendations to streamline federal agency reporting. The guidance recommends the use of eProject Builder (ePB), a project development and archiving tool for energy projects. ePB carries additional value in its simplification of federal agency reporting by dovetailing with the Federal Energy Management Program’s (FEMP’s) EISA 432 Compliance Tracking System (CTS).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Trust Model Utilization for Energy Grid Communication

The internet information that is used by the Energy Grid of Things requires both preventative security measures as well as surveillance measures. The preventative security measures include certificates, encryption, and all of the basic security protocols as defined by published standards. The surveillance measures include monitoring information flow activities and evaluating these messages for indications of potential security attacks. We describe in this paper the utilization of a Distributed Trust Model that was developed specifically for monitoring communication within an Energy Grid of Things. The goal for the Distributed Trust Models is to provide a level of aggregate trust that a Distributed Energy Resource Management System can meet its grid service obligations, as opposed to a detailed individual Distributed Energy Resources assessment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Net Zero Energy Model for Wastewater Treatment Plants

The primary objective of this study is to achieve net-zero energy (NZE) wastewater treatment plants (WWTPs) by utilizing energy efficiency opportunities (EEO), combined heat and power (CHP) systems, and other renewable energy (RE) sources, e.g., solar, water, and wind powers. Herein, this study discusses an innovative energy solution for WWTPs in the United States, and one of the WWTPs with a flow capacity of 1.5 million gallons per day (MGD) was selected as a case study. An optimization tool, Hybrid Optimization of Multiple Energy Resources (HOMER) software, is used in this study to find the best energy system configuration to run the system. An energy audit for one WWTP was conducted in early 2020 and the report is used to do this study. The proposed EEOs were able to reduce WWTP energy consumption by about 11%. The excess anaerobic digester gas was utilized in a CHP system to cover about 42% of the facility’s consumption. Also, 3% of the utility energy consumption can be claimed by microturbines in the aeration tanks. Another two renewable energy systems, solar photovoltaic (PV) with 29% and water turbines with 15%, contribute to covering 100% of the WWTP energy consumption and achieving an NZE WWTP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗