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At least 37 records · Page 2

Air Handling Unit Shutdowns During Scheduled Unoccupied Hours: US Commercial Building Stock Prevalence and Energy Impact

Commercial buildings account for 18% of U.S. energy consumption, with 44% used for heating, ventilation, and air conditioning (HVAC). American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 90.1 requires HVAC systems to shutdown fans and outdoor air ventilation during unoccupied times, only allowing fans to cycle on, without outdoor air, to maintain thermostat setpoints. However, it is minimally understood how often existing building operations align with energy code requirements and the energy implications of not doing so. This study used building automation system data from 843 buildings containing 5706 air handling units (AHUs) to determine three unoccupied AHU shutdown control schemes ranging in efficiency and then estimated their prevalence in the U.S. commercial building stock, segmented by building type. ComStock was then used to analyze the energy savings potential of implementing the most energy efficient unoccupied shutdown control scheme in non-participating buildings across the U.S commercial building stock. Results show that only 23% of AHUs align completely with the ASHRAE 90.1 requirement. ComStock modeling results show 4% annual stock energy savings by switching all non-participating buildings to the most efficient scheme, with 19% annual energy savings demonstrated for the median building switching from the least efficient scheme to the most efficient. Findings also show 114.5 TBtu electricity and 75.8 TBtu natural gas fuel savings when converting to the most efficient scheme. Furthermore, these findings help stakeholders understand the high prevalence of buildings not aligning with the ASHRAE-90.1 requirements for unoccupied AHU shutdowns and the energy savings potential of utilizing the most efficient unoccupied AHU shutdown scheme.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A measured energy use, solar production, and building air leakage dataset for a zero energy commercial building

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m 2 (3,531 ft 2 ) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour resolution by 56 microinverters (presented as daily and monthly data in this dataset). The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modeling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.

14 SOLAR ENERGY↗

Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season

This paper presents a critical advancement in Building Energy Modeling (BEM) through an empirical validation approach using a high-quality dataset from a multizone commercial office building in Oak Ridge, TN, USA. BEM is widely utilized in diverse construction applications, but its effectiveness relies on the accuracy of its predictions. The study focuses on empirical validation of input parameters in BEM, including building envelope data, infiltration modeling, and rooftop unit system performance curves. The validation of simulation input parameters leads to substantial improvements in the accuracy of simulation results. Notable both NMBE and cv (RMSE) values are reduced by 0.5 % for indoor air temperature and 17 % for indoor air relative humidity compared to the previous model. At the system level, both NMBE and cv (RMSE) values are reduced by 2 % for fan energy consumption and 4 % for cooling energy consumption, compared to the previous model. A literature review highlights a significant gap in empirical validation studies, which predominantly concentrate on either component-level or whole building validation. Furthermore, many studies employ simplified setups that may not faithfully represent the complexities of multizone commercial buildings. This paper distinguishes itself by emphasizing the critical importance of component-level input parameter validation. It underlines the need to validate data related to building envelope components and HVAC system performance curves, resulting in more accurate simulation outcomes. In conclusion, the utilization of actual multizone commercial building data enhances the study's practical relevance. In summary, this research underscores the pivotal role of input parameter validation in enhancing the accuracy and reliability of BEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Regional Carbon Emission Reduction Prediction via Retrofits of Commercial Buildings with a Case Study of US School Buildings in Hot Climates

Retrofitting commercial buildings has great potential to reduce carbon emissions as demonstrated by previous studies in some specific cities, but their regional carbon emission reduction potential is still unknown. Thus, we develop a method to predict the long-term regional carbon emission reduction potential by retrofitting commercial buildings. School buildings in hot climate zones in the continental U.S. are selected as an example. The results show that the aggregated carbon emission reduction potential of school buildings in that region reduces from 3.33 to 2.01 megatons from 2024 to 2050 due to the increased penetration of renewable energy.

building energy simulation↗

Efficient Air Dehumidification Can Save 15%-50% of Cooling Energy in Commercial Buildings

Current approach to dehumidification in commercial buildings with chilled/hot water AHU systems is to overcool return + supply air to dewpoint, and then reheat before supply to zone. This is energy inefficient, with reheat often being gas-fired. To reduce energy consumption, building operators will often operate at little-to-no outside air, sacrificing IAQ. Decarbonizing commercial buildings requires solutions to reduce and fully electrify dehumidification energy consumption. The Altaire ADAPT and Conservant HEDS systems aim to solve this problem by decoupling humidity control from cooling reduces energy consumption while enabling improved IAQ management.

commercial buildings↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Impact Analysis of Transitioning to Heat Pump Rooftop Units for the U.S. Commercial Building Stock

Twenty percent (25%) of the energy consumed by the U.S. commercial building sector is from on-site combustion of fossil fuels for space heating. Part of decarbonizing U.S. energy systems to meet climate initiatives will require electrification of space heating equipment, often by transitioning to heat pumps. Rooftop units (RTU) are the most prominent commercial building HVAC system type and should therefore be prioritized for electrification solutions. However, there is limited understanding of the impact on emissions when considering regional electricity generation methods, as well as the impact of ambient temperature on capacity and efficiency, defrost operation, realistic sizing methodologies, and supplementary heating on overall heat pump performance. This study explores the effects of transitioning all installed, existing RTUs to high-performance heat pump RTUs for the U.S. commercial building stock. The analysis is performed using ComStock (TM), the U.S. Department of Energy's calibrated model of the U.S. commercial building stock. Results show 10% and 9% reductions in stock aggregate energy consumption and greenhouse gas emissions, respectively. This analysis will help inform the transition to heat pump RTUs for the U.S. commercial building stock.

commercial building↗

ComStock: Commercial Building Stock Energy Consumption Dataset

The commercial building sector stock model, or ComStock, is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States.

building↗

Decarbonizing the Building Sector: A Human-Centered Study Focused on Small/Light Commercial Building Energy Equity

Decarbonization of the building sector is no small feat; buildings account for 40% of primary energy consumption, and fossil-fuel combustion in buildings leads to roughly 30% of total greenhouse gas emissions. Energy efficiency, electrification and smart technologies are fundamental strategies to reduce consumption and shift away from fossil-fuel use in buildings. This energy transition carries significant societal risks unless the shift is carried out with equity and justice as a top priority. Low-income, vulnerable and communities of color have higher energy burdens compared to affluent populations. Furthermore, systemic racism and historic exclusionary policies have resulted in increased risks (environmental, climatic, economic, and social) to low-income and communities of color, and underserved communities often do not have financial resources for, or access to, advanced building technologies. The U.S. Department of Energy is funding research to characterize and develop solutions to the challenges of equity and justice that complicate the ability of communities to contribute to goals for decarbonization. Our project has a specific focus on small commercial buildings and the businesses that occupy them. Significantly less is known about the burdens and risks these businesses experience or the challenges they face in pursuing decarbonization, or how those are affected by income and race, in comparison to research on energy equity and justice for diverse households. The project team includes the Pacific Northwest National Laboratory, Arizona State University and Clark Atlanta University. Researchers are conducting semi-structured interviews with small business owners in underserved communities in Phoenix and Atlanta, followed by a survey distributed to the larger community to learn more about the equity and justice issues that communities with different racial, economic, and cultural backgrounds face. Results will help inform an actionable and replicable framework for engaging small commercial building owners/operators to catalyze the reduction of energy burdens and increase equity.

Antonopoulos, Chrissi A.↗

Paths Forward: Approaches to Achieve Plug and Process Load Efficiency and Control in Commercial Buildings: Preprint

To accomplish net-zero carbon in the built environment by 2050, we must equitably decarbonize commercial buildings, which includes reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not directly associated with major building end uses like lighting and heating, ventilating, and air conditioning. PPLs account for a growing portion of U.S. commercial building energy consumption. Although commercial building PPL strategies and technologies are available today, they have not been adopted at a level sufficient to achieve significant savings and load flexibility across the building stock. In our "Pathways to Plug and Process Load Efficiency and Control" study, we investigated why these technologies and strategies have not seen widespread adoption and identified five behavior and technology pathways to increase PPL reduction in commercial buildings. In this paper, we expand beyond identifying the pathways and discuss approaches for achieving them. We discuss the importance of collecting and sharing data and case studies on PPL energy consumption and savings from control technology implementation, including code-required measures, for increasing adoption. Centralizing case studies and data, engaging industry organizations, and promoting awareness of PPL efficiency benefits to relevant groups are also key approaches. Additionally, funding, incentives, and rebate programs play important roles in driving PPL efficiency and control adoption. Finally, we discuss integrating PPL efficiency into broader company goals, such as environmental, social and governance (ESG) strategies and green building certifications, to further drive adoption.

adoption pathways↗

Connecting Electric Vehicle Charging Infrastructure to Commercial Buildings

Electric vehicles (EVs) are growing in popularity and gaining meaningful market share with record sales year over year in the last decade. EV charging equipment, also known as EV chargers (EVC) or EV supply equipment (EVSE), must proportionally match the growing number of new EVs on the road for a comparable experience to gas-powered vehicles. The majority of EV charging currently happens at residential buildings. However, demand for EV charging at commercial buildings will significantly increase with wider mainstream EV adoption and as businesses return to more normal operation following COVID-19 pandemic disruptions. Charging equipment can include various sub-systems like power conditioning module, control software, safety devices, metering, communication, cooling, connectors, and its wiring. EV charging at commercial buildings could be used for public, workplace, and commercial fleet charging. This document aims to describe how EVC can be connected to commercial buildings, including considerations for facility managers, and the effects that charging will have on the buildings electrical distribution system. More specifically, this resource provides an overview of: understanding EV charging basics: how charging equipment connects to the building and to EVs; required infrastructure updates needed at the building site to connect EVC to existing distribution systems; network strategies for cost-effective operation; metering and utility considerations for billing and incentives; charging equipment ownership options; future trends in EVC connection to buildings.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Environmentally Friendly Use of Carbon Ore for Advanced Building Materials for Homes and Commercial Buildings

Through this effort, X-MAT CCC sought to confirm the utility and commercialization potential of carbon-derived building materials (CDBM) technology licensed from our partner, Semplastics. These CDBM products contain at least 52% coal-derived carbon by mass. Including the binders within the resin, the products contain at least 71% carbon by mass overall, meeting a key criterion for DE-FOA-0002185 – Area of Interest (AOI) 5 – Design Research and Development, Validation, and Fabrication of a Prototype Carbon-Based Building. The Phase II project has resulted in a technology demonstrator prototype structure, a detailed design for a carbon-based building, and updated techno-economic analysis (TEA) including detailed market surveys to show the commercial viability of CDBM products. We pursued the following objectives in Phase II: (1) construction of a partial building shell as a technology demonstrator, (2) testing of CDBM products, individually and in assemblies, (3) demonstration of bonding of CDBM and traditional building materials (TBM) in structural applications, (4) production of a detailed design for a carbon-based building, and (5) an update of the TEA that was performed in Phase I. In Phase II, X-MAT CCC and our industry team performed the development and testing needed to improve the maturity of the technology from a Technology Readiness Level (TRL) of 5 to TRL 6. CDBM have been shown by our partner Semplastics to exhibit a number of high-performance characteristics, including high strength (five times the flexure strength of the best commercial brick, and more than twice the compressive strength of construction-grade concrete block), lower density, improved mechanical durability and abrasion resistance, very high temperature stability, and resistance to chemicals, acids, salts, and water. These properties offer significant improvements over conventional building materials. Phase II built upon the work accomplished in Phase I by performing technical and economic research and development to confirm the viability of CDBM as commercial products in various markets. Acknowledgment: This material is based upon work supported by the Department of Energy under Award Number DE-FE0031985.

01 COAL, LIGNITE, AND PEAT↗

Commercial Building Sensors and Controls Systems - Barriers, Drivers, and Costs

Optimized building sensors and controls systems could lead to 29% annual energy savings in commercial buildings and are integral to the growth of grid-interactive efficient buildings. However, only 8% of small commercial buildings have installed sensors and controls systems-which is largely due to cost barriers. This publication seeks to increase the transparency of system costs and identify specific barriers and drivers for increased adoption. Qualitative interview data was collected from 20 interviews with industry and qualitative cost data was collected from invoices during the interviews. The greater understanding of costs and barriers associated with commercial building sensors and controls systems lays the groundwork for future steps in increasing system adoption, reducing energy consumption, and market transformation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

CIECAT (Cyber-Informed Engineering Commercial Buildings Analysis Tool) [SWR-25-172]

The Cyber-Informed Engineering Commercial Buildings Analysis Tool (CIECAT) was developed in collaboration with the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER). This tool is a energy source subcomponent integrated into the CIEMAT ecosystem and is developed to enhance the security and resilience of Commercial Buildings by incorporating Cyber-Informed Engineering (CIE) principles into the Commercial Buildings.

Etigowni, Sriharsha [National Laboratory of the Ro↗

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗

Pathways to commercial building plug and process load efficiency and control

Abstract To accomplish net-zero carbon emissions in the built environment by 2050, we must equitably decarbonize commercial buildings, including reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not associated with major building end uses like lighting and HVAC. Research shows PPL energy reduction strategies and control technologies have the potential to save energy. But even when implemented, these savings have rarely been achieved and there has not been widespread uptake in U.S. commercial buildings. We investigate why these technologies and strategies have not seen widespread adoption and identify behavior and technology pathways to increase PPL reduction in U.S. commercial buildings. We examined behaviors of commercial building stakeholders through 44 interviews and cross-referenced qualitative analysis findings with in-depth technical knowledge of existing PPL control technologies and reduction strategies. PPL control implementation must be paired with management strategies, such as occupant engagement and training, to achieve optimal savings, and best practices should be disseminated across the industry. We found that increasing access to cost and energy savings data will promote uptake of PPL control technologies and allow designers to better incorporate PPLs into building design. Improving access to funding for PPL energy efficiency projects and addressing the split-incentive problem will increase adoption of PPL efficiency and control. Code bodies should continue to include PPL monitoring and reduction measures in energy codes. Key building stakeholders, including cybersecurity and information technology teams, should be involved in PPL monitoring and reduction strategy processes for successful implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Commercial Building Sensors and Controls Systems: Barriers, Drivers, and Costs

Building sensors and controls systems, including building automation systems, consists of the sensor-based devices installed in buildings and the control and automation of those devices. Optimized sensors and controls systems could lead to 29% annual energy savings in commercial buildings and are integral to the growth of grid-interactive efficient buildings. Only 8% of small commercial buildings, however, have installed sensors and controls systems. This is largely due to cost barriers. This work seeks to increase the transparency of system costs and identify specific barriers and drivers for increased adoption. To gather industry insights, the team reached out to building owners, vendors, and contractors and conducted 20 interviews with the goal of collecting cost data and market characteristics regarding building sensors and controls. The qualitative interview data was analyzed using grounded theory to identify overarching concepts, such as barriers, drivers, and future directions on the field. From this analysis, primary barriers were found to be complexity, a lack of knowledge, and money. Primary drivers were found to be the knowledge of data, savings, and remote access. The qualitative cost data was collected in the form of invoices during the interviews. The cost values were used to develop a percentage-based cost stack which identifies the average fraction of the total cost attributed to each category (hardware, software, labor, fees, and taxes). This greater understanding of costs and barriers associated with commercial building sensors and controls systems lays the groundwork for future steps in increasing system adoption, reducing energy consumption, and market transformation.

advanced building controls↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗