http://www.rssboard.org/rss-specification 720 https://escholarship.org/uc/lbnl_et_btus/rss Recent eScholarship items from Bldg Technology Urban Systems Sat, 12 Sep 2026 12:20:06 +0000 https://escholarship.org/uc/item/5rv708gk Buildings are becoming ever more complex to manage during operations, driven by increasing dynamics in energy demand, intermittent on-site power generation, and distributed energy resources, compounded by variable grid pricing signals and the rising threat of extreme weather events causing large-scale power outages. To achieve optimal performance in energy efficiency, demand flexibility, energy resilience, and occupant comfort, new methods and tools are essential for transforming design and operations across a building’s entire life cycle. Digital Twins (DTs), enabled by recent advances in ubiquitous sensing, big data, cloud computing, and AI, offer a transformative approach to creating a real-time, bi-directional digital counterpart of a physical building. This paper presents ten critical questions highlighting the most foundational issues underpinning the successful deployment of digital twins for buildings. The questions are holistically structured around three core themes... https://escholarship.org/uc/item/5rv708gk Wed, 9 Sep 2026 00:00:00 +0000 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Li, Han https://orcid.org/0000-0003-4638-9907 Zhu, Yimin Dong, Bing Zhang, Liang Choudhary, Ruchi https://escholarship.org/uc/item/66d9c3z6 The U.S. Department of Energy Industrial Efficiency and Decarbonization Office’s Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. One such ITV project is to demonstrate the performance of an electrochemical water treatment technology on a cooling tower at an automotive plant. Cooling towers are vital equipment for dissipating heat from industrial processes. However, they face challenges related to scaling, corrosion, and the growth of biological contaminants. Effective cooling tower water filtration and treatment is essential to reduce these contaminants, along with other total suspended solids (TSS) and total dissolved solids (TDS) in the system. Various treatment systems, such as sand-based filters, centrifugal separators, and disc filters, offer distinct advantages and limitations.... https://escholarship.org/uc/item/66d9c3z6 Thu, 3 Sep 2026 00:00:00 +0000 Earni, Shankar https://orcid.org/0000-0003-1953-9156 Pevzner, Amy Karki, Unique Sheaffer, Paul Rao, Prakash Charland, Ross Weissert, Josh https://escholarship.org/uc/item/1bq6q873 Brightening the Earth’s surface can increase the outflux of sunlight to space. This diminishes the net (downward minus upward) solar flux into the Earth’s radiative system, providing negative solar radiative forcing that can cool the atmosphere. We are quantifying the extent to which surface-brightening projects, such as installing solar-reflective roofs and pavements, can raise bottom-of-atmosphere (BOA) albedo, increase top-of-atmosphere (TOA) solar outflux, and reduce regional and global atmospheric temperatures. We compared four approaches to assessing BOA albedo: roof- or pavement-product documentation; local measurements with an albedometer (back-to-back pyranometers); extrapolation from extended-color aerial images (blue, green, red, and near-infrared); and multispectral satellite images sharpened by convolution with aerial images, selecting the last. We developed a technique to calculate the atmosphere’s upward solar transmittance anywhere in the Earth’s tropical and temperate... https://escholarship.org/uc/item/1bq6q873 Thu, 3 Sep 2026 00:00:00 +0000 Levinson, Ronnen https://orcid.org/0000-0003-1463-1359 Vahmani, Pouya Klink, Frank Akbari, Hashem https://escholarship.org/uc/item/7808983d While many options exist to improve industrial demand-side energy efficiency, energy management systems (EnMSs)—particularly those aligned with ISO 50001—are proven to drive continuous and meaningful energy performance improvements. Governments leverage these EnMSs in their policies to advance national objectives including enhancing industrial competitiveness and achieving environmental goals. Existing research has focused on the impact of EnMSs at the company level, while comprehensive work on EnMSs in a global policy context is lacking. We seek to close this gap by investigating the extent to which current national policies incorporate the utilization of EnMSs, particularly the ISO 50001 standard. Our paper employs a hybrid approach, combining a literature review and expert interviews across 28 governments representing > 86% of global primary energy consumption. We dissect policy mechanisms, governance levels, underlying motivations, and trends in present EnMS policies. We... https://escholarship.org/uc/item/7808983d Mon, 31 Aug 2026 00:00:00 +0000 Moreno, Francisco Luis Fuchs, Heidi https://orcid.org/0000-0003-0010-5411 Miller, William Therkelsen, Peter https://orcid.org/0000-0003-1413-8636 https://escholarship.org/uc/item/6jw731z7 Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated... https://escholarship.org/uc/item/6jw731z7 Fri, 28 Aug 2026 00:00:00 +0000 Ham, SW https://orcid.org/0000-0003-1776-2610 Excell, L Kim, D https://orcid.org/0000-0002-1868-6341 https://escholarship.org/uc/item/6722d4zv Correction to: Scientific Datahttps://doi.org/10.1038/s41597-024-03319-8, published online 23 May 2024 In this article the author’s name Marcelo Salles Olinger was incorrectly given as Marcello Salles Olinger. The original article has been corrected. https://escholarship.org/uc/item/6722d4zv Fri, 28 Aug 2026 00:00:00 +0000 Machard, Anaïs Salvati, Agnese P. Tootkaboni, Mamak Gaur, Abhishek Zou, Jiwei Wang, Liangzhu Leon Baba, Fuad Ge, Hua Bre, Facundo Bozonnet, Emmanuel Corrado, Vincenzo Luo, Xuan Levinson, Ronnen https://orcid.org/0000-0003-1463-1359 Lee, Sang Hoon Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Salles Olinger, Marcelo Machado, Rayner Maurício E Silva da Guarda, Emeli Lalesca Aparecida Veiga, Rodolfo Kirch Lamberts, Roberto Afshari, Afshin Ramon, Delphine Ngoc Dung Ngo, Hoang Sengupta, Abantika Breesch, Hilde Heijmans, Nicolas Deltour, Jade Kuborn, Xavier Sayadi, Sana Qian, Bin Zhang, Chen Rahif, Ramin Attia, Shady Stern, Philipp Holzer, Peter https://escholarship.org/uc/item/5ms743n4 Retrofitting existing central plants with high-efficiency heat pump technologies can play a crucial role in achieving long-term planning goals. Modern heat pump technologies are able to use waste heat recovery to meet a building's heating demand, but there is a lack of accessible tools designed for non-HVAC experts, such as building owners, to quickly and easily conduct what-if analysis, e.g., estimating retrofit costs and payback period for their partial or full equipment replacement. This paper introduces an open-source software toolkit designed to facilitate the initial screening and decision-making of heat pump retrofits in existing central plants using a building's yearly load profile from metered or utility bill data. The toolkit evaluates the technical and economic viability of replacing traditional central plant equipment with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users... https://escholarship.org/uc/item/5ms743n4 Fri, 28 Aug 2026 00:00:00 +0000 Excell, L Anderson, I Breda, J Ham, SW https://orcid.org/0000-0003-1776-2610 White, G Kim, D https://orcid.org/0000-0002-1868-6341 https://escholarship.org/uc/item/92r451mq The beautification of urban facades in China often includes covers for the outdoor units of air conditioners. Although these covers improve cityscapes, they reduce cooling efficiency, increase noise pollution, risk system failures and embody carbon emissions. A call urges rethinking their necessity, and presses for sustainable, efficient design to counteract extreme heat. https://escholarship.org/uc/item/92r451mq Thu, 27 Aug 2026 00:00:00 +0000 Wang, Wei Deng, Yuwen Wu, Jiyuan Wang, Zhe Wei, Hailu Hu, Qinran Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Qian, Tao https://escholarship.org/uc/item/7jh4s386 Heat pumps account for a significant portion of electricity consumption in buildings, making their energy efficiency a critical area of research. Control optimization is recognized as an effective approach for enhancing the efficiency of building HVAC systems. Specifically, since the efficiency of heat pumps increases with reduced superheat and the optimal refrigerant charge level varies with operating conditions, zero-superheat active charge control is a promising strategy to maximize the system’s COP. However, due to its complexity, this control strategy remains in the research phase and has only been tested under limited operating conditions. This paper proposes a methodology to evaluate the seasonal performance improvement of zero-superheat active charge control across a full range of heating conditions in buildings. The methodology includes the development of an optimal controller that utilizes an accumulator to store excess refrigerant and manages the active charge level... https://escholarship.org/uc/item/7jh4s386 Thu, 27 Aug 2026 00:00:00 +0000 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Shen, Bo Hlanze, Philani Cai, Jie https://escholarship.org/uc/item/7h09w0kh Housing sufficiency is an emerging concept in the provision of environmentally sustainable housing. It aims for demand-side strategies that reduce excessive, aggregate consumption levels to promote efficient resource utilization and sustainability in the construction sector while providing everyone with a decent standard of housing. However, it is challenging to implement as it interferes with housing-related social and cultural norms. This paper poses and answers ten questions that highlight the challenges, opportunities, and examples of sufficiency strategies in the context of housing provision and the environmental crisis. Question 1 discusses the need for sufficiency as a tool to complement supply-side strategies including efficiency and renewable energy strategies in providing housing. Question 2 examines the concept of housing sufficiency from different perspectives, such as ecological economics and social ecology. Question 3 summarizes the methods used to measure housing... https://escholarship.org/uc/item/7h09w0kh Thu, 27 Aug 2026 00:00:00 +0000 Arceo, Aldrick Touchie, Marianne O'Brien, William Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Malik, Jeetika https://orcid.org/0000-0003-0398-5303 Mayer, Matan Peters, Terri Saxe, Shoshanna Tamas, Ruth Villeneuve, Hannah Schmaltz, Benoît https://escholarship.org/uc/item/7fq9d8ng Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the... https://escholarship.org/uc/item/7fq9d8ng Thu, 27 Aug 2026 00:00:00 +0000 Ma, Jiacheng Thorade, Matthis Kim, Donghun https://orcid.org/0000-0002-1868-6341 https://escholarship.org/uc/item/6sk8s22t Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for... https://escholarship.org/uc/item/6sk8s22t Thu, 27 Aug 2026 00:00:00 +0000 Shu, Lei Zhao, Dong Zhang, Wanni Li, Han https://orcid.org/0000-0003-4638-9907 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/5t48x8xk As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application... https://escholarship.org/uc/item/5t48x8xk Thu, 27 Aug 2026 00:00:00 +0000 Nweye, Kingsley Kaspar, Kathryn Buscemi, Giacomo Fonseca, Tiago Pinto, Giuseppe Ghose, Dipanjan Duddukuru, Satvik Pratapa, Pavani Li, Han https://orcid.org/0000-0003-4638-9907 Mohammadi, Javad Ferreira, Luis Lino Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Ouf, Mohamed Capozzoli, Alfonso Nagy, Zoltan https://escholarship.org/uc/item/5m42r7qw As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical... https://escholarship.org/uc/item/5m42r7qw Thu, 27 Aug 2026 00:00:00 +0000 Houben, Nikolaus Heleno, Miguel https://orcid.org/0000-0001-8021-7661 Li, Han https://orcid.org/0000-0003-4638-9907 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Auer, Hans Ajanovic, Amela Haas, Reinhard https://escholarship.org/uc/item/5d71h7zg Residential building energy retrofits are essential for enhancing environmental sustainability and reducing energy costs. The selection of retrofit measures is influenced by factors such as building systems, occupant behavior, government policy, weather variability, and climate change, all of which can significantly impact energy performance. Compared to retrofitting individual homes, evaluating and selecting optimal retrofit solutions for an entire community is challenging due to diverse residential compositions and variability present. Therefore, engineering robustness is crucial for ensuring consistent energy performance and resilience across different conditions. In this context, robustness refers to the ability of a retrofit measure to maintain its functionality and remain an optimal choice despite external disturbances or changes in inputs and conditions. This study presents a framework for evaluating the robustness of multiple retrofit measures across various building systems,... https://escholarship.org/uc/item/5d71h7zg Thu, 27 Aug 2026 00:00:00 +0000 Shu, Lei Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Sun, Kaiyu Zhao, Dong https://escholarship.org/uc/item/5928q8zf This study proposes a practical and simplified demand response (DR) control strategy from the perspective of grid-interactive efficient buildings (GEBs), aiming to secure demand flexibility while ensuring occupant thermal comfort. Focusing on summer on-peak periods, a linear demand response (LDR) strategy that integrates cooling setpoint adjustment and lighting dimming was designed, and its performance was quantitatively evaluated. A case study was conducted using EnergyPlus-based simulations for a U.S. DOE small office prototype building under summer on-peak weather conditions. Compared with a conventional rapid demand response (RDR) strategy, the proposed LDR approach gradually reduced electrical loads while maintaining occupant thermal comfort indices, including predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD), within acceptable comfort ranges. Quantitative analysis of demand flexibility using the grid-interactive impact index (GII) and the flexibility... https://escholarship.org/uc/item/5928q8zf Thu, 27 Aug 2026 00:00:00 +0000 Jung, Dong Eun Seo, Byeongmo Choi, Haneul Han, Gwangwoo Jin, San Kim, Donghun https://orcid.org/0000-0002-1868-6341 Son, Sung-yong Kim, Jonghun https://escholarship.org/uc/item/5640136c Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected... https://escholarship.org/uc/item/5640136c Thu, 27 Aug 2026 00:00:00 +0000 Ma, Jiacheng Kim, Donghun https://orcid.org/0000-0002-1868-6341 Braun, James E https://escholarship.org/uc/item/54s0v55w The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential... https://escholarship.org/uc/item/54s0v55w Thu, 27 Aug 2026 00:00:00 +0000 Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Hlanze, Philani Cai, Jie https://escholarship.org/uc/item/2bd2z9sw The charge level of refrigerant in heat pump systems significantly affects their operational performance. Virtual refrigerant charge (VRC) sensing technology has been well-established for traditional refrigerants (HFCs and HCFCs) for its low cost compared to physical sensors. However, other than traditional refrigerants, HFOs are increasingly used in next-generation heat pumps; whether these conventional VRC sensing methods remain applicable for heat pump systems utilizing next-generation refrigerants requires further investigation. To address these issues, this study develops a low-cost VRC sensing method for next-generation refrigerant heat pumps used in residential buildings. The developed algorithm is evaluated by using simulation models to evaluate the accuracy, considering an R454B heat pump with a nominal heating capacity of 51K Btu/hr (14.95 kW) as an example, and compared with those of the two reference VRC sensing algorithms. Though the developed VRC sensing algorithm... https://escholarship.org/uc/item/2bd2z9sw Thu, 27 Aug 2026 00:00:00 +0000 Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Shen, Bo https://escholarship.org/uc/item/0sq1f441 Project 2 develops software infrastructure, test cases, and extensions for the Building Optimization Testing Framework (BOPTEST) to address the expanding needs of building and urban energy system controls through open international collaboration. This paper provides an overview of the new test cases available as of BOPTEST version 0.7.1. Each test case is developed using open-source Modelica libraries and Spawn of EnergyPlus, enabling the creation of high-fidelity building models that incorporate envelope dynamics, Heating Ventilation and Air Conditioning (HVAC) systems, and explicit control representations. Currently, eight test cases are available, with five additional cases under development. These test cases cover a wide range of climates, building types, and HVAC systems. This paper compiles and summarizes test case descriptions, cites original manuscripts that developed them for a more detailed description, and reports baseline control performance metrics. Furthermore, two... https://escholarship.org/uc/item/0sq1f441 Thu, 27 Aug 2026 00:00:00 +0000 Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Blum, David https://orcid.org/0000-0003-3231-7937 Arroyo, Javier Walnum, Harald Taxt Cupeiro, Iago Van Hove, Matthias Lu, Xing Chen, Yan Bae, Yeonjin Li, Guowen Zhang, Kun https://escholarship.org/uc/item/08f1371p Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations).... https://escholarship.org/uc/item/08f1371p Thu, 27 Aug 2026 00:00:00 +0000 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Ham, Sang woo https://orcid.org/0000-0003-1776-2610 Kim, Donghun https://orcid.org/0000-0002-1868-6341 https://escholarship.org/uc/item/9s30g2mq Providing fresh air to rooms can ensure indoor air quality. The direct expansion fresh air handling units are widely used, and most of them are single-stage treatment units, which are less energy-efficient under variable operating conditions. To overcome the shortcomings of existing systems, a direct expansion system using multiple stages and adjustable heat exchange areas for fresh air handling is proposed in this study. The fresh air is handled by coils stage by stage to achieve high efficiency, and the dampers of the idle coils are opened when some of the coils are working, which results in the performance improvement under partial load conditions. The simulation model is established, and operating conditions at load ratio of 95.70%, 45.38%, 31.76% and 0 are selected as typical operating conditions. The proposed system performances under different conditions are compared with traditional system. The results show that: (1) For four conditions, as the load rate decreases, the... https://escholarship.org/uc/item/9s30g2mq Wed, 26 Aug 2026 00:00:00 +0000 Zha, Fuhai Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Fang, Lin Tanaka, Toshio Matsui, Nobuki Li, Xianting https://escholarship.org/uc/item/9km6t35v While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher... https://escholarship.org/uc/item/9km6t35v Wed, 26 Aug 2026 00:00:00 +0000 Ko, Yun-Dam Jung, Hyeyun Eunice Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Jain, Rishee https://escholarship.org/uc/item/99z5314d Electrification of residential buildings is a key strategy for increasing the use of renewable energy sources. Central to this transition is understanding the capacity of existing electrical infrastructure—specifically electrical panels—to safely and effectively manage increased electricity demands from electrification technologies. However, comprehensive nationwide data on electrical panel capacities in U.S. single-family homes is currently lacking. To address this gap, we conducted a nationwide survey of single-family homes, collecting detailed data on electrical panel capacities, breaker slot availability, major electric and gas appliances, electrical panel models, and home characteristics such as construction year and floor area. Photographic documentation was used to verify electrical panel data and appliance information. Results show that approximately 60% of surveyed homes have electrical panels rated at ≥200 amperes (A), indicating that a significant portion of the existing... https://escholarship.org/uc/item/99z5314d Wed, 26 Aug 2026 00:00:00 +0000 Gul, Sadia Meier, Alan https://orcid.org/0000-0002-1260-2151 https://escholarship.org/uc/item/8nq156tb The multi-stage air treatment system has been proposed recently, and lower grade chilled/hot water could be used and energy efficiency could be improved. However, it has not been studied which division method of air treatment processes has higher energy efficiency. In this study, the model to calculate the energy consumption of multi-stage air treatment process is introduced, and the effects of two division methods, i.e. multi-stage air treatment process divided by the same temperature difference (ST method) or same enthalpy difference (SE method) between inlet and outlet at each stage, under 9 different air inlet parameters in the 2-stage and 3-stage air treatment processes are analysed and compared. The results show that (1) the system energy consumption of the SE method is generally lower than that of the ST method; (2) there is generally a larger energy consumption reduction rate of SE method when the air relative humidity is 70% compared to relative humidity of 50% and 90%;... https://escholarship.org/uc/item/8nq156tb Wed, 26 Aug 2026 00:00:00 +0000 Wang, Wentao Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Zha, Fuhai Li, Xianting https://escholarship.org/uc/item/8gm2d39b U.S. Commercial buildings account for about 20% of total U.S. energy consumption. Because the thermal performance of windows significantly affects building energy efficiency and HVAC system performance, best practice guidance often includes window and envelope improvements in conjunction with HVAC upgrades to optimize energy use and improve occupant comfort. It is an open question, however, regarding how often these best practices are implemented in the field. This paper aims to address that gap by conducting a literature review and a series of interviews with commercial building auditing and management professionals to explore the factors that drive window retrofits in commercial buildings. The paper explores a range of case studies from deep energy retrofits across the globe, comparing projects with and without window retrofits. The primary goals of this review are to: (1) provide data from real-world case studies illustrating the role of windows in deep energy renovations and... https://escholarship.org/uc/item/8gm2d39b Wed, 26 Aug 2026 00:00:00 +0000 Cort, Katherine Palani, Hevar Kono, Jamie Stanislaus, Travis Bhandari, Mahabir Hart, Robert https://escholarship.org/uc/item/8553f80m The growing energy demand of the industrial sector and the need for sustainable solutions highlight the importance of efficient decision making in solar photovoltaic (PV) implementation. Selecting optimal PV configuration is complex due to the interdependent technical, economic, environmental, and social factors involved. This study introduces an integrated decision-making method combining a morphological matrix and fuzzy TOPSIS to systematically select and rank optimal PV system configurations for manufacturing firms. While the morphological matrix exhaustively examines possible design solutions based on sensing, smart, sustainable, and social (S4) attributes, the fuzzy TOPSIS method ranks the alternatives by handling uncertainty in decision making. A case study conducted in a Mexican manufacturing company validates the methodology’s effectiveness. The optimal PV configuration identified comprehensively addresses operational and sustainability criteria, covering all lifecycle... https://escholarship.org/uc/item/8553f80m Wed, 26 Aug 2026 00:00:00 +0000 Briceño, Citlaly Pérez Ponce, Pedro Fayek, Aminah Robinson Anthony, Brian Bradley, Russel Peffer, Therese https://orcid.org/0000-0001-5569-7448 Meier, Alan https://orcid.org/0000-0002-1260-2151 Mei, Qipei https://escholarship.org/uc/item/826584wd With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize... https://escholarship.org/uc/item/826584wd Wed, 26 Aug 2026 00:00:00 +0000 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Ham, Sang woo https://orcid.org/0000-0003-1776-2610 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Moon, Hyeun Jun https://escholarship.org/uc/item/7vb673m7 The authors regret an error in the acknowledgments section regarding the U.S. Department of Energy Solar Energy Technologies Office award number. The previously listed grant number, 2597–1625, was incorrect. The corrected acknowledgment should read: “This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Building Technologies of the United States Department of Energy (DOE), under Contract No. DE-AC02–05CH11231. This material is based upon work supported by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office Award Number DE-EE00040384. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of Energy.” The authors would like to apologise for any inconvenience caused. https://escholarship.org/uc/item/7vb673m7 Wed, 26 Aug 2026 00:00:00 +0000 Malik, Jeetika https://orcid.org/0000-0003-0398-5303 Wei, Max Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/7676p1xs K-12 school buildings account for the highest energy consumption within the public sector. Implementing advanced HVAC controls in grid-interactive K-12 schools could bring substantial economic advantages and grid flexibility. Our previous study demonstrated that a low-cost model predictive control (MPC) solution, which coordinates multiple packaged units, can enable demand flexibility without major hardware upgrades. However, a significant gap remains between academic pilots and market-ready scalable solutions. This paper extends the previous single-site pilot to a multi-site demonstration involving three school campuses (95 total units) through a commercial technology transfer process. Addressing the challenge of verifying performance with sparse field data, we present a new statistical approach using Bayesian methods to estimate the MPC’s effect on peak demand. Unlike traditional methods, this approach robustly quantifies uncertainty in non-normal, limited datasets. The results... https://escholarship.org/uc/item/7676p1xs Wed, 26 Aug 2026 00:00:00 +0000 Ham, Sang Woo https://orcid.org/0000-0003-1776-2610 Hariri, Mohamad El Kim, Donghun https://orcid.org/0000-0002-1868-6341 Barham, Tanya https://escholarship.org/uc/item/75n9f2w1 Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor... https://escholarship.org/uc/item/75n9f2w1 Wed, 26 Aug 2026 00:00:00 +0000 Nihar, Kopal Li, Han https://orcid.org/0000-0003-4638-9907 Malik, Jeetika https://orcid.org/0000-0003-0398-5303 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/5874h222 Supplying fresh air is important for indoor air quality, but the energy consumption to treat fresh air is significant. The main problems in existing fresh air system include: supplying single-temperature water to treat fresh air and not applying natural energy sufficiently restrict the efficiency improvement of cooling and heat sources; unused air handling devices under most operating conditions throughout the year increase the fan energy consumption. Thus, this study proposes an efficient fresh air system that uses lake water to pre-treat fresh air and two-stage heat pumps for further treatment, and the unused air handling devices in the system are bypassed. A fresh air system in northern China is selected as a case to show the annual energy performance of the proposed system, and a comparative analysis is conducted between the proposed system and a traditional system. The results show that the annual energy-savings of the proposed system compared to the traditional system come... https://escholarship.org/uc/item/5874h222 Wed, 26 Aug 2026 00:00:00 +0000 Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Li, Xianting https://escholarship.org/uc/item/3ng7f19j To achieve energy efficiency in the operation of heating devices and ensure thermal comfort in indoor environments, the integrated convective/radiant terminals have become an important development direction for heating systems. This study selected a 14 m 2 bedroom hot summer and cold winter region in China as a case study. Computational Fluid Dynamics (CFD) methodology was used to investigate the design of integrated convective/radiant terminals to ensure thermal comfort for both the entire room and partial space. The results indicate that focusing on partial space during the steady-state stage can achieve energy savings of 31.1% compared to guaranteeing the entire room. Additionally, during the start-up stage, there is a significant reduction of convective unit capacity by 17.6% when the start-up time is 15 minutes. These findings provide data support for the design and engineering applications of products of integrated convective/radiant terminals. Besides, the excess convection... https://escholarship.org/uc/item/3ng7f19j Wed, 26 Aug 2026 00:00:00 +0000 Chi, Junjie Yang, Zixu Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Wang, Baolong Li, Xianting Shi, Wenxing https://escholarship.org/uc/item/3d86v8rd Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities,... https://escholarship.org/uc/item/3d86v8rd Wed, 26 Aug 2026 00:00:00 +0000 Chung, Jihoon Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 Malik, Jeetika https://orcid.org/0000-0003-0398-5303 Shelden, Dennis https://escholarship.org/uc/item/3056t653 The unprecedented growth in artificial intelligence (AI) workloads, recently dominated by large language models (LLMs) and vision-language models (VLMs), has intensified power and cooling demands in data centers. This study benchmarks LLMs and VLMs on two HGX nodes, each with 8× NVIDIA H100 graphics processing units (GPUs), using liquid and air cooling. Leveraging GPU Burn, Weights & Biases, and IPMItool, we collect detailed thermal, power, and computation data. Results show that the liquid-cooled systems maintain GPU temperatures between 41-50$^\circ$C, while the air-cooled counterparts fluctuate between 54-72$^\circ$C under load. This thermal stability of liquid-cooled systems yields 17% higher performance (54 TFLOPs/ GPU vs. 46 TFLOPs/GPU), performance-per-watt, reduced energy overhead, and greater system efficiency than the air-cooled counterparts. These findings underscore the energy and sustainability benefits of liquid cooling, offering a compelling path forward for... https://escholarship.org/uc/item/3056t653 Wed, 26 Aug 2026 00:00:00 +0000 Latif, Imran Shafique, Muhammad Ali Ullah, Hayat Newkirk, Alex C https://orcid.org/0000-0002-6213-6865 Yu, Xi Munir, Arslan https://escholarship.org/uc/item/2tm676r4 Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including... https://escholarship.org/uc/item/2tm676r4 Wed, 26 Aug 2026 00:00:00 +0000 Ham, Sang woo https://orcid.org/0000-0003-1776-2610 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Rossetti, Michael Sipple, John https://escholarship.org/uc/item/2r84r4qs Urban Building Energy Modeling (UBEM) is an important reference for urban energy-related policymaking. Because of the significant impact of urban microclimates on the energy simulation, UBEM requires simulations of many microclimate-prototype pairs. Surrogate modeling is commonly used to reduce the cost of simulation computations. In UBEM surrogate modeling, it is important to determine the percentage of microclimates related to a prototype used for generating surrogate model training data. This study analyzes the prototype-wise variations and sensitivities of surrogate model estimation accuracy to the microclimate sampling ratios. The results of the study can help determine the number of simulations used for generating surrogate modeling data, avoid redundant simulations, and reduce the computational cost for UBEM surrogate modeling and its time. https://escholarship.org/uc/item/2r84r4qs Wed, 26 Aug 2026 00:00:00 +0000 Pan, Xiyu Mohammadi, Neda Taylor, John E Xu, Yujie https://orcid.org/0000-0002-1805-1872 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/1r95j7rd Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution:... https://escholarship.org/uc/item/1r95j7rd Wed, 26 Aug 2026 00:00:00 +0000 Yang, Jiahui Soga, Kenichi Sulzer, Matthias https://orcid.org/0000-0003-2094-2460 Chen, Kecheng https://escholarship.org/uc/item/1bs9m05r Natural refrigerants are increasingly adopted in next-generation heat pump systems, among which CO₂ heat pumps have attracted significant attention. However, due to their high operating pressures, the leakage risk is higher, resulting in undercharge conditions and degraded heat pump performance. Thus, developing an accurate refrigerant charge level detection technique is necessary to guarantee safe and efficient operation. Although virtual refrigerant charge (VRC) level calculation algorithms for CO₂ heat pumps exist, they typically rely on empirically selected features without a systematic selection framework, leading to multicollinearity and potential overfitting, which limit their prediction accuracy and generalizability. To address these issues, this study proposes a VRC algorithm framework with a systematic feature selection method that identifies physically meaningful and statistically significant features, and is applied using a residential CO₂ heat pump as a case study.... https://escholarship.org/uc/item/1bs9m05r Wed, 26 Aug 2026 00:00:00 +0000 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Liang, Chenjiyu https://orcid.org/0009-0003-6454-5915 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Shen, Bo Hu, Yifeng https://escholarship.org/uc/item/0gb1x475 Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action... https://escholarship.org/uc/item/0gb1x475 Wed, 26 Aug 2026 00:00:00 +0000 Guo, Fangzhou https://orcid.org/0000-0001-6234-3090 Ham, Sang woo https://orcid.org/0000-0003-1776-2610 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Kim, Sun Ho Moon, Hyeun Jun https://escholarship.org/uc/item/7pp3n21m It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2)... https://escholarship.org/uc/item/7pp3n21m Tue, 25 Aug 2026 00:00:00 +0000 Singh, Reshma Jain, Yashima https://escholarship.org/uc/item/4gt7h0d8 Upgrading electrical panels and services in U.S. homes represents a significant barrier to building modernization, imposing considerable costs, delays, and procedural uncertainties on homeowners, contractors, utilities, and building departments. Although cost databases document individual infrastructure activities, they rarely capture the integrated, whole-project perspective required to understand how electrical upgrades are planned, executed, and regulated. Existing research is often geographically constrained, narrowly scoped, or derived from limited samples, leaving significant knowledge gaps unaddressed. This study examines the timelines and costs associated with residential electrical panel and service upgrades using data from a national cross- sectional survey conducted in summer 2025. The survey captured responses from 140 stakeholders across 34 states, including building industry professionals, utility staff, and building department staff. Findings indicate that project... https://escholarship.org/uc/item/4gt7h0d8 Tue, 25 Aug 2026 00:00:00 +0000 Casquero-Modrego, Nuria https://orcid.org/0000-0001-5677-4142 Venkatraman,, Meena Gul, Sadia Less, Brennan Walker, Iain https://orcid.org/0000-0001-9667-1797 https://escholarship.org/uc/item/3d94n54n Despite being recognized as the best practice for advanced building controls, ASHRAE Guideline 36 (G36) has seen slow adoption in retrofit cases. Decisionmakers lack credible field evidence to justify the time and person-power investment. Most prior analyses have relied on software simulations, which overlook implementation challenges and fail to persuade owners to move from models to real-world deployment. This paper presents a multi-site field study of G36 performance, drawing on measured results from 17 projects across diverse building types and climate zones. The analysis disaggregates outcomes by the most widely adopted air handling unit (AHU) based G36 strategies, including trim-and-respond approaches to supply air temperature (SAT) and duct static pressure (DSP) reset, and economizer controls. Results for controls re programming implementations are encouraging, with HVAC savings ranging from 2% - 49%, with a median of 18%. The range aligns with simulation study findings... https://escholarship.org/uc/item/3d94n54n Tue, 25 Aug 2026 00:00:00 +0000 Deshpande, Reva Casillas, Armando Velmurugan, Guhan Granderson, jessica https://orcid.org/0000-0002-4536-9560 https://escholarship.org/uc/item/39f7p4vn Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error).... https://escholarship.org/uc/item/39f7p4vn Tue, 25 Aug 2026 00:00:00 +0000 Newkirk, Alex C https://orcid.org/0000-0002-6213-6865 Fernandez, Jared Koomey, Jonathan Latif, Imran Strubell, Emma Shehabi, Arman https://orcid.org/0000-0002-1735-6973 Samaras, Constantine https://escholarship.org/uc/item/3582z6mq To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a... https://escholarship.org/uc/item/3582z6mq Tue, 25 Aug 2026 00:00:00 +0000 Hart, Robert Yu, Tammie https://escholarship.org/uc/item/7rs224s8 Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can... https://escholarship.org/uc/item/7rs224s8 Mon, 24 Aug 2026 00:00:00 +0000 Bavaresco, Mateus Machado, Rayner Maurício E Silva Krelling, Amanda F https://orcid.org/0000-0003-2585-4320 Melo, Ana Paula Park, Won Young Lamberts, Roberto https://escholarship.org/uc/item/9m22n8z3 High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower... https://escholarship.org/uc/item/9m22n8z3 Fri, 21 Aug 2026 00:00:00 +0000 Yu, Lili Liu, Jingjing Walker, Iain https://orcid.org/0000-0001-9667-1797 Granderson, Jessica https://orcid.org/0000-0002-4536-9560 https://escholarship.org/uc/item/9ds6z1c2 The growing need for smart, energy-efficient, and occupant-centric buildings has created a demand for advanced control systems that can optimize building operations to balance energy savings, demand flexibility, and comfort. However, current building energy simulation tools, such as EnergyPlus, have limitations that hinder the development and evaluation of these complex control systems. To address this challenge, we introduce a high-fidelity building emulator that dynamically couples EnergyPlus with Radiance for enhanced daylight modeling. The introduced workflow allows researchers and practitioners to rapidly develop and evaluate innovative control solutions. An example study looking at a south-facing office zone revealed up to 67% deviation in predicted light levels, which can significantly impact building assessment. https://escholarship.org/uc/item/9ds6z1c2 Fri, 21 Aug 2026 00:00:00 +0000 Yu, Tammie Wang, Taoning https://orcid.org/0000-0002-3410-5068 Gehbauer, Christoph https://escholarship.org/uc/item/2d13c3nd Solar shadow calculations are needed in building energy modeling and performance simulation of PV systems installed on roofs or facades of buildings. We present a quantum computing approach for calculation of building surface sunlit fractions by recasting solar visibility as a binary optimization problem solved by quantum annealing. Each triangulated surface centroid is encoded as a binary qubit indicating sunlit or shaded status. Geometric visibility constraints are derived from the Möller-Trumbore intersection algorithm and converted into a constrained quadratic binary model compatible with contemporary quantum annealers. The coefficients were embedded to D-Wave quantum computer. To demonstrate feasibility, we conducted a case study in San Francisco for a target building with 52 triangles and roughly 2700 nearby triangles within 50 m evaluated at representative winter and summer solar positions. The results demonstrated that quantum annealing can reliably calculate and... https://escholarship.org/uc/item/2d13c3nd Fri, 21 Aug 2026 00:00:00 +0000 Deng, Zhipeng Xu, Yujie https://orcid.org/0000-0002-1805-1872 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/03z1h0g7 A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained... https://escholarship.org/uc/item/03z1h0g7 Fri, 21 Aug 2026 00:00:00 +0000 Geisler-Moroder, David Maskarenj, Marshal Ward, Greg Wang, Taoning https://orcid.org/0000-0002-3410-5068 Lee, Eleanor S https://orcid.org/0000-0002-7019-2568 Altomonte, Sergio https://escholarship.org/uc/item/72n8x6v2 Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos,... https://escholarship.org/uc/item/72n8x6v2 Thu, 20 Aug 2026 00:00:00 +0000 Casillas, Armando Ham, Sang Woo Yang, Tao Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Crabtree, Peter https://escholarship.org/uc/item/5bw2b61n Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry. https://escholarship.org/uc/item/5bw2b61n Thu, 20 Aug 2026 00:00:00 +0000 Langevin, Jared https://orcid.org/0000-0002-0028-7932 Wilson, Eric JH https://escholarship.org/uc/item/2br7v1xq Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties... https://escholarship.org/uc/item/2br7v1xq Thu, 20 Aug 2026 00:00:00 +0000 Dutton, Spencer Helmns, Dre Huang, Weiping Casillas, Armando Walker, Iain https://orcid.org/0000-0001-9667-1797 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/26f3g212 Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is... https://escholarship.org/uc/item/26f3g212 Thu, 20 Aug 2026 00:00:00 +0000 Yu, Lili Hart, Robert https://escholarship.org/uc/item/23k4s94t Why is this Facility Different? Measuring Energy Culture to Achieve Continual Improvement in Energy Efficiency https://escholarship.org/uc/item/23k4s94t Thu, 20 Aug 2026 00:00:00 +0000 Wising, Ulrika Liu, Jingjing Vetromile, Julia https://escholarship.org/uc/item/15v2424w The US energy system is in a period of high uncertainty about load growth, its implications for the energy generation mix, and downstream impacts on customer energy costs. In this context, there is a need for comprehensive, credible, and readily-customized projections of energy demand to ensure that planning decisions account for end-use management opportunities to improve system reliability and affordability. Here we introduce the Buildings Sector Scenarios (BSS) dataset, which includes a benchmark suite of such projections for the buildings sector — a key source of energy consumption, peak electricity demand, and consumer energy expenditures. The dataset contains projections through 2050 covering the contiguous United States (CONUS) resolved down to the county, hourly level by sector and end use for electricity demand and to the state, annual level by sector and end use for non-electric fuels. We summarize the BSS analysis workflow and the tools and datasets that support it,... https://escholarship.org/uc/item/15v2424w Thu, 20 Aug 2026 00:00:00 +0000 Langevin, Jared https://orcid.org/0000-0002-0028-7932 Pigman, Margaret Parker, Andrew Wilson, Eric JH Putra, Handi Chandra Xu, Yujie https://orcid.org/0000-0002-1805-1872 Murthy, Sam Sun, Kaiyu Zhang, Wanni Ringold, Eric Adhikari, Rajendra Lou, Yingli Satchwell, Andrew J Zhuang, Xinwei Whiting, Matia https://escholarship.org/uc/item/132008ps Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure,... https://escholarship.org/uc/item/132008ps Thu, 20 Aug 2026 00:00:00 +0000 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Blum, David https://orcid.org/0000-0003-3231-7937 Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Ham, Sang Woo Casillas, Armando Prakash, Anand Paul, Lazlo Huang, Weiping Yang, Tao Qamar, Afshan Gerber, Daniel Liu, Jingjing Piette, Mary Ann https://escholarship.org/uc/item/0sb9w0jr Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling,... https://escholarship.org/uc/item/0sb9w0jr Thu, 20 Aug 2026 00:00:00 +0000 Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Blum, David https://orcid.org/0000-0003-3231-7937 Gautier, Antoine Raftery, Paul Cheng, Hwakong https://escholarship.org/uc/item/7xp8m1v8 Semantic ontologies have enabled the creation of formalized, machine-readable descriptions of heterogenous building systems by providing dictionaries of well defined concepts that can be applied to model them. Within a semantic model of a particular building, a subset of an ontology's concepts may be applied in different ways to represent a particular perspective of the building's systems. How the concepts were applied can only be understood by examining the large amount of instance data within a semantic model, which leads to usability challenges. We propose a concise, ontology-agnostic method for defining building-specific schema (b-schema) graphs that summarize the structure and content of a semantic model. This approach provides a queryable and concise representation of the model's contents, separate from the instance data within a model, that can mitigate the challenges posed by the size and complexity of semantic models in processes such as visualization, querying, validation,... https://escholarship.org/uc/item/7xp8m1v8 Wed, 19 Aug 2026 00:00:00 +0000 Paul, Lazlo Mulayim, Ozan Baris Saka, Umut Mete Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Fierro, Gabe Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/6hz9r3nc Exposure to low indoor air temperature is a major contributor to temperature-related mortality during extreme cold events, especially when power outages disrupt operation of space heating systems. This study explores the impact of high-performance windows on the thermal resilience of residential buildings during extreme cold weather and grid power outages, as well as their long-term benefits through energy efficiency and reduced risk of property damage. Building performance simulations were conducted for reference residential buildings in three construction vintages and two major U.S. cities located in cold climate zones, considering two types of extreme cold events: short and severe, and long and milder. Our research found that even houses compliant with current energy codes struggle to maintain safe indoor temperatures for more than a few hours during power outages, necessitating rapid evacuations. High-performance windows can extend the thermal survivability time by up to 3.8... https://escholarship.org/uc/item/6hz9r3nc Wed, 19 Aug 2026 00:00:00 +0000 Krelling, Amanda F https://orcid.org/0000-0003-2585-4320 Jiang, Yilin Sun, Kaiyu https://orcid.org/0000-0002-6621-4971 LaFrance, Marc Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/46x480kg When Knowledge Graph (KG) queries fail to match a pattern in a KG, they return no results. Identifying the statements causing these failures is tedious, especially for LLM-generated queries, which tend to be longer and more complex than queries written by hand. Query relaxation addresses this by systematically loosening query constraints until results are recovered. To evaluate the effectiveness of query relaxation against LLM generated queries, we propose a two-stage relaxation method combining triple deletion and path relaxation and test it against 1,823 failed queries for building KGs. https://escholarship.org/uc/item/46x480kg Wed, 19 Aug 2026 00:00:00 +0000 Paul, Lazlo Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/2r03p5qj The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort... https://escholarship.org/uc/item/2r03p5qj Wed, 19 Aug 2026 00:00:00 +0000 Lee, Sang Hoon Bianchi, Carlo Carvallo, Juan Pablo https://orcid.org/0000-0002-4875-8879 https://escholarship.org/uc/item/0sm7z80f In an office building equipped with a Variable Air Volume (VAV) system, this paper introduces a novel method for controlling the minimum supply airflow fraction in each zone’s VAV box, having a capability to consider indoor CO2 level and energy consumption. The EnergyPlus simulation using the medium office prototype model was employed, which evaluated the performance of the energy and CO2 concentration for five VAV box airflow control strategies. The paper focuses on CO2 concentration-based airflow control method and compares it with other four methods including conventional single-max, reduced minimum single-max, demand-controlled ventilation(DCV), and dualmax control methods according to guidelines and common practices. The newly proposed control strategy directly correlates the minimum airflow fraction to CO2 concentration. A general trend emerged when comparing CO2 concentrations—lower minimum airflow fractions were associated with higher concentrations. The proposed control... https://escholarship.org/uc/item/0sm7z80f Wed, 19 Aug 2026 00:00:00 +0000 Lee, Jong Man Lee, Kwang Ho Moon, Jin Woo Lee, Sang Hoon Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/9gg3471t USB-C has become the universal plug standard for charging consumer electronics, typically through AC/DC wall adapters. As new standards in USB power distribution allow USB-C ports to provide up to 240W at 48V, many discuss the possibility of USB-C emerging as a plug-load standard, especially in DC buildings. This work proposes the use of USB-C wall outlets to power the emerging USB-C ecosystem without need for a wall adapter. We first study the market feasibility of USB-C outlets through a series of customer discovery interviews. We then perform several experiments to evaluate the technical feasibility. These include a comparative evaluation of efficiency and a thermal experiment to study how the heat from outlet's conversion loss can be dissipated through an exterior wall section. https://escholarship.org/uc/item/9gg3471t Tue, 18 Aug 2026 00:00:00 +0000 Gerber, Daniel L https://orcid.org/0000-0002-1972-0679 Shackelford, Jordan https://orcid.org/0000-0001-7042-6814 Goudey, Howdy Meier, Alan https://orcid.org/0000-0002-1260-2151 Chen, David Saturno, Donnie Espino, Marvin Manango, Mark https://escholarship.org/uc/item/3cv18403 Home renovation and remodeling projects can involve costly and time consuming electrical infrastructure upgrades at the household level. From the grid perspective they also lead to costly replacement of local infrastructure, such as transformers, and can add stress to the grid at peak times. The emergence of innovative, power-efficient household appliances offers a way to minimize these problems. These appliances are designed for lower power consumption, simplifying installation through standard plug-in connections, reducing the need for new electric circuits/panels/service, and minimizing the peak power demand for the home. Key examples include low-power heat pump water heaters (HPWHs) and cold climate window heat pumps that operate on standard 120V outlets. To assess the real-world impact of these solutions, we compiled and analyzed power metering data from several US field studies. This data provides insights into the effects on peak power demand of selecting lower-power appliances.... https://escholarship.org/uc/item/3cv18403 Tue, 18 Aug 2026 00:00:00 +0000 Less, Brennan https://orcid.org/0000-0002-6134-3926 Sanchez, Lino Walker, Iain https://orcid.org/0000-0001-9667-1797 https://escholarship.org/uc/item/4170h3ns Model Predictive Control (MPC) has demonstrated potential for reducing building energy costs and integrating buildings into the electric grid, yet adoption in large commercial buildings remains limited. We developed, deployed, and demonstrated an MPC in a large office building from 2020 to 2025, an uncommonly long duration for MPC field research that has enabled us to gain valuable insights. The MPC achieved 45% energy savings in efficiency mode and an estimated 61% annual cost reduction under experimental dynamic prices compared to baseline rule-based control, leveraging thermal mass for load shifting across all four seasons. However, the demonstration revealed critical barriers to broader adoption: uncertain cost-to-benefit ratios, including dependence on specialized expertise for deployment, integration hurdles due to proprietary and many different data streams (APIs/protocols), gaining facility staff trust, and updating the Building Management System (BMS). There were also... https://escholarship.org/uc/item/4170h3ns Mon, 17 Aug 2026 00:00:00 +0000 Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Blum, David https://orcid.org/0000-0003-3231-7937 Prakash, Anand https://orcid.org/0000-0002-3694-3225 Paul, Lazlo Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/300792q8 Smart home technologies have been deployed to reduce or shift residential energy demand by employing scheduling strategies such as time-of-use electricity pricing. This study evaluates behavioral aspects of users equipped with smart home technologies by incorporating cost-related notifications into multiple smart appliances in real-world settings. Smart thermostats, smart plugs, clothes washers, dryers, and dishwashers were installed in eight households for one year to evaluate changes in user behavior and power load shifting. During this period, three cost-related notification features were introduced: (1) mode choices for thermostat control and associated mode-specific cost and temperature displays, (2) delay nudges that encouraged users to postpone appliance use during peak periods by showing potential savings, and (3) monetary incentives for deferred operation. Results revealed that mode-specific cost information led users to make clear trade-offs between cooling preferences... https://escholarship.org/uc/item/300792q8 Mon, 17 Aug 2026 00:00:00 +0000 Son, Seonghyuk Graeber, Keith Shimada, Hideki Suk, Jae Yong https://escholarship.org/uc/item/2ds6r8cr Technologies such as USB and Ethernet can be used to power devices in buildings, but have burdens of cost and energy efficiency that make them unsuitable as a primary means of distributing power to most loads in buildings. This paper describes a proposed standard for 48V DC power distribution in buildings suitable for powering most loads in residential and commercial buildings. It includes both general data communication as well as communication for managing the distribution of power. The maximum power is targeted at 1000 W with options for low- and high-power circuits to minimize costs.11This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies Office, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies Office, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. https://escholarship.org/uc/item/2ds6r8cr Mon, 17 Aug 2026 00:00:00 +0000 Nordman, Bruce Brown, Richard https://orcid.org/0000-0002-4219-7214 Parker, Lauren Gerber, Daniel https://orcid.org/0000-0002-1972-0679 Kanteti, Aditya Baldwin, Jim Poon, Jason https://escholarship.org/uc/item/85r6v96n Digital twins, created by generating a virtual replica of a building, enable safe evaluation of operational scenarios and applications like fault detection and diagnosis and advanced controls. However, a prerequisite is the creation of a machine-readable digital representation of a building, currently hindered by fragmented information scattered across mechanical drawings, point lists, and natural language sequences. As a result, digital twin development remains labor-intensive, error-prone, and difficult to validate. To address these challenges, two efforts from ASHRAE aim to support the digitalization of buildings. ASHRAE s223 establishes a semantic model of buildings, representing system components, configuration, and data sources. ASHRAE s231 defines a vendor-neutral programming language for expressing their control logic. As the industry evaluates implementing them in their products, understanding the challenges that vendors and implementers may face is crucial. In this... https://escholarship.org/uc/item/85r6v96n Thu, 13 Aug 2026 00:00:00 +0000 Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Paul, Lazlo Huang, Weiping Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Ham, Sang Woo Blum, David https://orcid.org/0000-0003-3231-7937 Kim, Donghun https://orcid.org/0000-0002-1868-6341 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 De Andrade Pereira, Flavia Duarte Roa, Carlos https://escholarship.org/uc/item/6r42g2pt The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among... https://escholarship.org/uc/item/6r42g2pt Thu, 13 Aug 2026 00:00:00 +0000 Wetter, Michael https://orcid.org/0000-0002-7043-0802 Dee, Virak Fu, Hongxiang Hu, Jianjun Nyenhuis, Eric Sulzer, Matthias Tech, Andrew https://escholarship.org/uc/item/6mb622fk With electricity consumption across the United States (US) and Canada anticipated to grow, energy efficiency program administrators have a key role to play in helping to ensure energy affordability and reliability in support of the broader economic systems utilities and grid support. Connected, demand side load balancing solutions, such as load shifting heating, ventilation and air conditioning (HVAC) systems and managed charging for electric vehicles (EVs), can dynamically manage energy, allowing for more volumetric electricity consumption without incurring the expense of upgraded transmission and distribution capabilities. When combined, or aggregated, many small loads can be managed to have meaningful impact on energy demand on the grid. Utilities and their partners have an opportunity to leverage decades of experience and the infrastructure needed to assess, design, implement, and measure programs to scale up the adoption of equipment with built-in load flexibility capabilities. Current... https://escholarship.org/uc/item/6mb622fk Thu, 13 Aug 2026 00:00:00 +0000 Hamilton, Ryan Grant, Peter https://orcid.org/0000-0003-1240-2018 Olson, Eric Hunt, Brenda O'Connor, Bill https://escholarship.org/uc/item/6504p705 Oversizing, the common engineering practice of specifying devices with capacity exceeding the actual load requirement, is a widespread practice across virtually all building technologies end-use categories, including HVAC, electrical systems, lighting, appliances, and plug loads. This practice, driven by factors like design uncertainty, institutional pressures, and risk aversion, results in wasted capital investment, control difficulties, and excessive energy consumption due to inefficient part-load operation. Part-load operation, where devices run below maximum capacity, is the dominant operating mode in most energy systems and presents a complex design challenge. Solutions to match output to load fall into three broad categories: constraining the output, adjusting the device’s internal behavior, and linking output to energy storage or other waste-heat reuse applications. The energy implications of part-load are critical, as efficiency often drops sharply as load decreases across... https://escholarship.org/uc/item/6504p705 Thu, 13 Aug 2026 00:00:00 +0000 Meier, Alan https://orcid.org/0000-0002-1260-2151 Merrill, Wyatt https://escholarship.org/uc/item/5px652tv The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation, and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during... https://escholarship.org/uc/item/5px652tv Thu, 13 Aug 2026 00:00:00 +0000 Adua, Lazarus Asamoah, Amma Barrows, John Brookstein, Pamela Chen, Bing Coleman, Debra Rucker Denzer, Anthony Desjarlais, Andre O Falconer, Whit Fernandes, Luis Fisler, Diana Foley, Craig Gaillard, Clement Gladen, Adam Guzowski, Mary Hill, Terence Hun, Diana Kishore, Ravi Klingenberg, Katrin Kosny, Jan Levinson, Ronnen https://orcid.org/0000-0003-1463-1359 McGinley, Mark Myer, Michael Nicodemus, Julia Rempel, Alexandra Riggins, Jim Riggs, Russel Robinson, Brian Ruan, Xiulin Schwarz, Robby Sharp, M Keith Shrestha, Som Sofos, Marina Tabares-Velasco, Paulo Cesar Tenent, Robert Toye, Cory Usher, Todd Walker, Andy https://escholarship.org/uc/item/44d015x3 Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one... https://escholarship.org/uc/item/44d015x3 Thu, 13 Aug 2026 00:00:00 +0000 Grant, Peter https://orcid.org/0000-0003-1240-2018 Woo-Shem, Brian Huang, Weiping https://escholarship.org/uc/item/3t22m5pm Field studies show that demand flexibility in residential buildings can save up to 20% in energy costs, but requires secure, automated, and reliable coordination across multiple devices and stakeholders. Integration between platforms is typically done on a one-to-one basis, requiring device-specific and platform-specific programming and updates. This manual process is expensive, as developers must manage protocol translation and data exchange through proprietary or reverse-engineered APIs, often without a consistent or standardized data format. This fragmented approach hinders scalability and slows the adoption of demand flexibility technologies. Recently, several communication protocols have emerged in the US to address these challenges by defining common data models and standard interfaces for device-to-grid and device-to-device interactions. Although many of these protocols intend to provide comprehensive interoperability, in practice, each addresses a specific segment of... https://escholarship.org/uc/item/3t22m5pm Wed, 12 Aug 2026 00:00:00 +0000 Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Woo-Shem, Brian Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Paul, Lazlo Grant, Peter Huang, Weiping Liu, Jingjing Piette, Mary Ann Nordman, Bruce Jackson, Don https://escholarship.org/uc/item/4mb9z2jj Correction to: Nature Communications; https://doi.org/10.1038/s41467-024-50088-4, published online 14 July 2024 In the version of the article initially published, Jessica Granderson (Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA) was not included in the author list and now appears in the HTML and PDF versions of the article. https://escholarship.org/uc/item/4mb9z2jj Tue, 11 Aug 2026 00:00:00 +0000 Ding, Chao https://orcid.org/0000-0003-0373-0167 Ke, Jing Levine, Mark Granderson, Jessica https://orcid.org/0000-0002-4536-9560 Zhou, Nan https://escholarship.org/uc/item/9cf4q897 The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying... https://escholarship.org/uc/item/9cf4q897 Thu, 30 Jul 2026 00:00:00 +0000 Granderson, Jessica https://orcid.org/0000-0002-4536-9560 Hoffman, Ian Holecek, Billie Crowe, Eliot Smith, Sarah Frick, Natalie Mims https://escholarship.org/uc/item/6637f9c6 As the impact of water scarcity in the United States (U.S.) continues to grow through the 21st century, it is critical to develop strategies to reduce water use and improve the security of water resources. One such strategy is to diversify the sources from which water is supplied. Industrial withdrawals represent the fourth largest category of U.S. water use, the majority of which is sourced from fresh surface and groundwater. In this study, we critically explore the potential of industrial wastewater to serve as an alternative water resource through direct treatment and reuse. We begin by reviewing the state of the art of water use, treatment, and reuse across six representative industries: food and beverages, primary metals, pulp and paper, petroleum refining, chemicals, and data centers and campuses, highlighting key challenges and opportunities toward the expansion of reuse. We then employ a technoeconomic assessment of water treatment processes to analyze the capital investment,... https://escholarship.org/uc/item/6637f9c6 Mon, 27 Jul 2026 00:00:00 +0000 Meese, Aidan Francis Kim, David J Wu, Xuanhao Le, Linh Napier, Cade Hernandez, Mark T Laroco, Nicollette Linden, Karl G Cox, Jordan Kurup, Parthiv McCall, James Greene, David Talmadge, Michael Huang, Zhe Macknick, Jordan Sitterley, Kurban A Miara, Ariel Evans, Anna Thirumaran, Kiran Malhotra, Mini Gonzalez, Susana Garcia Rao, Prakash Stokes-Draut, Jennifer https://orcid.org/0000-0003-0240-1361 Kim, Jae-Hong https://escholarship.org/uc/item/21m5f7vk We present a structured dataset that characterizes select technologies and facilities across U.S. industry. This dataset enables consistent, cross-sector techno-economic and energy/emissions characterization of U.S. industrial production for modeling and benchmarking analysis. The dataset covers six manufacturing sectors—ammonia, cement, ethanol, ethylene and propylene, iron and steel, and food, and three non-manufacturing sectors—agriculture, mining, and construction. Organized as an industry-level JSON array, the dataset integrates standardized assumptions, characterizations of incumbent and emerging technologies , and inventories of existing facilities. The assumptions harmonize units and prices, normalize operating costs using common feedstock and fuel base-lines, apply chemical engineering plant cost index factors to capital costs, and index all cost values to 2018 USD. For manufacturing sectors, the dataset provides facility-level inventories including 36 ammonia, 97 cement,... https://escholarship.org/uc/item/21m5f7vk Mon, 27 Jul 2026 00:00:00 +0000 Zhu, Yongxian Supekar, Sarang Armstrong, Kristina Avery, Greg Campbell, Nica Delgado, Hernan E Hawkins, Troy R Hendrickson, Thomas https://orcid.org/0009-0003-8637-9612 Karki, Unique https://orcid.org/0000-0002-5908-2202 Nimbalkar, Sachin Okeke, Ikenna Peng, Peng Rao, Prakash Singh, Udayan Thierry, David Yu, Li Zuberi, Jibran https://orcid.org/0000-0001-9606-9384 https://escholarship.org/uc/item/05z57695 Anthropogenic heat (AH) from buildings contributes to urban overheating, especially during heat waves, yet building retrofit studies usually evaluate energy savings without assessing impacts on AH. This study quantifies how common building retrofit measures affect both building energy use and AH emissions across the City of Los Angeles. Using a bottom-up urban building energy modeling framework coupled with high-resolution local weather from the Weather Research and Forecasting model with Building Effect Parameterization (WRF-BEP), we evaluate eleven retrofit measures and two multi-measure retrofit packages. HVAC and LED lighting retrofits provide the largest city-wide annual site energy savings, while roof coating is most effective for reducing AH. A package optimized for energy savings reduces summer site energy use by about 32% (2.3 TWh), while a package incorporating AH-focused measures reduces the total AH by over 50% (137 PJ) with minimal difference in energy savings. The... https://escholarship.org/uc/item/05z57695 Thu, 16 Jul 2026 00:00:00 +0000 Xu, Yujie https://orcid.org/0000-0002-1805-1872 Vahmani, Pouya https://orcid.org/0000-0003-2519-6671 Jones, Andrew https://orcid.org/0000-0002-1913-7870 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/7614q9q6 A smart building HVAC control competition crowdsourced and compared algorithms on fair and equal ground using the standardized BOPTEST framework. The competition attracted 138 participants, but only 9% submitted valid solutions for the final stage, highlighting the complexity of advanced HVAC control design. The winning solutions showed significant potential to reduce energy use and cost by shifting demand, without compromising occupant comfort. Across scenarios, thermal energy cost reductions of 36–76% relative to a baseline, were achieved. In peak heat periods, the cost reduction leveraged limited energy use reduction (0–15%), but more significant energy price reduction (34–62%). This shows smart controls' ability to avoid as much as possible consumption during the morning peak hours, when spot prices are tendentially the highest. Hosting the competition has highlighted challenges in creating competitions that both are fair and promotes solutions that are transferable to real... https://escholarship.org/uc/item/7614q9q6 Wed, 15 Jul 2026 00:00:00 +0000 Walnum, Harald Taxt Tolnai, Balázs András Blum, David https://orcid.org/0000-0003-3231-7937 Shi, Jicheng Jones, Colin N Dessai, Deep Wang, Wenbin Xu, Wenjie Gros, Sebastien Sartori, Igor https://escholarship.org/uc/item/3859p4j7 Residential and commercial buildings are among the largest sources of carbon dioxide and other greenhouse gas (GHG) emissions in the United States, responsible for more than one-third of total U.S. GHG emissions. There are nearly 130 million existing buildings in the United States, with 40 million new homes and 60 billion square feet of commercial floorspace expected to be constructed between now and 2050. Today, most buildings consume large amounts of energy and cause significant climate pollution to meet our basic needs. Buildings account for 74% of U.S. electricity use and building heating and cooling drives peak electricity demand. Moreover, buildings are where electric vehicles (EVs), solar, storage, heat pumps, water heaters, and other distributed energy resources integrate with the electricity system. Consequently, the buildings sector will play a key role in achieving economywide net-zero emissions by 2050. https://escholarship.org/uc/item/3859p4j7 Wed, 15 Jul 2026 00:00:00 +0000 Langevin, Jared https://orcid.org/0000-0002-0028-7932 Wilson, Eric Snyder, Carolyn Narayanamurthy, Ram Miller, Julia Kaplan, Katharine Reiner, Michael Risser, Roland Mahoney, Mandy Geyer, Josh Ciraulo, Rebecca https://escholarship.org/uc/item/5m9363m6 Extreme cold snaps pose significant risks to buildings, infrastructure, energy systems, and occupants, yet standardized climatic datasets tailored for resilience-focused building performance modeling remain limited. This study presents a methodology and corresponding dataset of cold snap events for 217 U.S. cities, derived from 24 years of historical hourly temperature data obtained from the NASA POWER project. Cold snaps were detected using a percentile-based, location-specific threshold that identifies periods of “abnormal cold” with additional constraints to ensure that events reflect meaningful differences from local winter conditions. Each event was characterized using a suite of metrics, including event duration, heating degree hours, and overcooling degree. Events were further classified into four categories based on the mean outdoor air dry-bulb temperature, analogous to intensity scales used in other hazard domains. A selection procedure was applied to ensure that each... https://escholarship.org/uc/item/5m9363m6 Tue, 14 Jul 2026 00:00:00 +0000 Krelling, Amanda F Malik, Jeetika https://orcid.org/0000-0003-0398-5303 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/7830m0k1 Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow,... https://escholarship.org/uc/item/7830m0k1 Thu, 2 Jul 2026 00:00:00 +0000 Paul, Lazlo Ham, Sang Woo https://orcid.org/0000-0003-1776-2610 Prakash, Anand https://orcid.org/0000-0002-3694-3225 Casillas, Armando Yang, Tao Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/6cn2g96f Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies.... https://escholarship.org/uc/item/6cn2g96f Thu, 2 Jul 2026 00:00:00 +0000 Paul, Lazlo Zanetti, Ettore https://orcid.org/0000-0002-9056-3813 Liu, Jingjing Casillas, Armando Krishnan Prakash, Anand Blum, David https://orcid.org/0000-0003-3231-7937 Nirenberg, Robert Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/5mg0z00c There is growing recognition that Demand Flexibility (DF) can play a major role in enhancing grid reliability, with building control applications emerging as key enablers for DF. However, the traditional approach to deploying new control applications in buildings, including those for DF, remains largely manual and tailored to individual buildings, making it difficult to scale. While research efforts have explored semantics-driven portability, DF controls specification, and assessment approaches, these initiatives are fragmented and limited in scope. This paper proposes a novel methodology, grounded in design science research, to integrate these elements and create a comprehensive DF controls library for both industry and academia. This approach is applied to develop the Demand FLEXibility controls LIBrary using Semantics (DFLEXLIBS), an extensible open-source library that provides DF controls for HVAC systems in Python. DFLEXLIBS enables portable, easy-to-deploy controls that... https://escholarship.org/uc/item/5mg0z00c Thu, 2 Jul 2026 00:00:00 +0000 de Andrade Pereira, Flavia Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Casillas, Armando Granderson, Jessica https://orcid.org/0000-0002-4536-9560 Paul, Lazlo Prakash, Anand https://orcid.org/0000-0002-3694-3225 Shaw, Conor Rovas, Dimitrios Martin-Toral, Susana Finn, Donal O’Donnell, James https://escholarship.org/uc/item/4xh0900n Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM... https://escholarship.org/uc/item/4xh0900n Thu, 2 Jul 2026 00:00:00 +0000 Mulayim, Ozan Baris Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Paul, Lazlo Pritoni, Marco https://orcid.org/0000-0003-4200-6905 https://escholarship.org/uc/item/4wr0d9qw Demonstration Trials of AI/ML Edge+Cloud Suite (CRADA Final Report) https://escholarship.org/uc/item/4wr0d9qw Thu, 2 Jul 2026 00:00:00 +0000 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Mills, Thomas https://escholarship.org/uc/item/4f3194dk Graph-based representations of building metadata using ontologies like Brick are vital for smart building applications, but querying them remains a challenge for practitioners. Knowledge Graph Question Answering (KGQA) systems, meant to retrieve answers from natural language questions, traditionally require large-scale training data, making them ill-suited for the specialized and data-scarce building domain. The advent of Large Language Models (LLMs) offers a paradigm shift, enabling zero-shot natural language querying without building/domain-specific training. Yet, there is no standardized benchmark for building-specific KGQA which can guide and validate research in this area. To address this gap, our work makes three primary contributions. First, we introduce the BuildingQA Benchmark Dataset, constructed through a multi-stage process of collecting practitioner data, augmenting it with LLMs for linguistic diversity, and curating a final set of 188 questions across 4 buildings.... https://escholarship.org/uc/item/4f3194dk Thu, 2 Jul 2026 00:00:00 +0000 Mulayim, Ozan Baris Anwar, Avia Saka, Umut Mete Paul, Lazlo Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Fierro, Gabe Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Bergés, Mario https://escholarship.org/uc/item/39z1x0vq The transition to a modern and efficient future grid relies on the seamless coordination of distributed energy resources and applications such as Demand Response (DR). While this transformation enables greater sustainability, it inevitably increases grid complexity and decentralization, requiring the effective coordination of millions of hardware assets and software agents. Realizing this vision demands advances in interoperability to ensure these heterogeneous systems can communicate without prohibitive customization costs. Semantic interoperability aims to address this by leveraging ontologies to guarantee the unambiguous interpretation of exchanged data. However, current semantic ontologies in the commercial building and DR domains face two critical limitations. First, existing ontologies are often developed without a formal framework that reflects real-world DR requirements. Second, proposals for integrating general (e.g., Brick) and DR-specific ontologies (e.g., EFOnt) remain... https://escholarship.org/uc/item/39z1x0vq Thu, 2 Jul 2026 00:00:00 +0000 Mulayim, Ozan Baris Prakash, Anand Krishnan https://orcid.org/0000-0002-3694-3225 Agarwal, Yuvraj Bergés, Mario Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Supple, Derek Schaefer, Steve Shah, Mitali https://escholarship.org/uc/item/5n36626r Digitalizing Building Control Deployment for Retrofits: A Case Study on Demand-Flexible Control Sequences https://escholarship.org/uc/item/5n36626r Fri, 26 Jun 2026 00:00:00 +0000 Pritoni, Marco https://orcid.org/0000-0003-4200-6905 Prakash, Anand https://orcid.org/0000-0002-3694-3225 Paul, Lazlo Huang, Weiping Kukharchuk, Roman Dawson-Haggerty, Stephen Sulzer, Matthias https://orcid.org/0000-0003-2094-2460 Wetter, Michael https://orcid.org/0000-0002-7043-0802 https://escholarship.org/uc/item/6kv3p3jb Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using... https://escholarship.org/uc/item/6kv3p3jb Thu, 18 Jun 2026 00:00:00 +0000 Rodriguez-Garcia, Luis Heleno, Miguel https://orcid.org/0000-0001-8021-7661 Zhang, Wanni Li, Han https://orcid.org/0000-0003-4638-9907 Sun, Kaiyu https://orcid.org/0000-0002-6621-4971 Hong, Tianzhen https://orcid.org/0000-0003-1886-9137 https://escholarship.org/uc/item/33m6w3x0 This report updates the 2024 Data Center Energy Usage Report (2024 Report) and estimates that data centers could account for 11.8% of total U.S. electricity by 2030. The estimate also includes a range of scenarios that indicate the energy use could be between 9.5 and 15.3% of total U.S. electricity use by 2030. In comparison, the 2024 Report estimate range was 6.7% to 12.0% of total U.S. electricity by 2028. The resulting electricity usage estimates in this Report are derived from a “bottom-up” energy use model, which determines electricity use from real-world data for planned data center IT equipment shipments (purchases), models of per-device annual electricity use and cooling system performance simulations, along with information on data center facility types and locations. The Reference Case estimate for electricity use (649 TWh in 2030) is calculated based on the current understanding of expected shipments and equipment design across the data center industry. The... https://escholarship.org/uc/item/33m6w3x0 Wed, 17 Jun 2026 00:00:00 +0000 Smith, Sarah https://orcid.org/0000-0003-0179-4546 Hubbard, Alexander https://orcid.org/0009-0003-1613-0299 Newkirk, Alex https://orcid.org/0000-0002-6213-6865 Ganeshalingam, Mohan Holecek, Billie Sartor, Dale Mills, Michael Shehabi, A https://orcid.org/0000-0002-1735-6973 https://escholarship.org/uc/item/63z977bc In recent years, advanced measurement and verification (M&V) methods utilizing interval meter data have become increasingly important for quantifying energy savings from building efficiency projects. Driven by policy initiatives such as California’s Assembly Bill 802 and Missouri’s M&V 2.0 guidance, these methods leverage advanced metering infrastructure (AMI) data to assess energy savings through pre- and post-intervention analysis. However, the presence of non-routine events (NREs) poses a significant challenge to accurate energy savings estimation, as these events can obscure the effects of efficiency measures. Traditional NRE detection methods, reliant on manual inspections and expert judgment, hinder scalability and standardization in savings estimation. Recent advancements in automated detection methodologies, including machine learning and statistical techniques, show promise but face challenges related to false positives and data quality. This study builds on previous... https://escholarship.org/uc/item/63z977bc Fri, 12 Jun 2026 00:00:00 +0000 Granderson, Jessica https://orcid.org/0000-0002-4536-9560 Fernandes, Samuel Crowe, Eliot https://escholarship.org/uc/item/06c6k7c6 Bioconversion of lignocellulosic biomass offers a promising alternative to petroleum-based chemical production. However, inefficient xylose utilization and toxic compounds in cellulosic hydrolysate limit microbial fermentation, as the hydrolysate contains substantial amounts of xylose in addition to glucose. To address these challenges, we engineered Issatchenkia orientalis to produce 3-hydroxypropionic acid (3-HP) directly from sorghum hydrolysate under low-pH conditions. A heterologous xylose utilization pathway consisting of XYL1, XYL2, and XYL3 from Scheffersomyces stipitis was introduced into an engineered 3-HP producing strain, enabling efficient conversion of xylose to 3-HP. The engineered strain produced 46.8 g/L 3-HP from sorghum hydrolysate without nutrient supplementation. To eliminate the lag phase under low-pH conditions, fermentation was conducted at pH 6.0 for the first three days, after which pH control was discontinued and in situ 3-HP accumulation buffered... https://escholarship.org/uc/item/06c6k7c6 Wed, 10 Jun 2026 00:00:00 +0000 Tan, Lin-Rui Kim, Saint Moon Cho, Young B Tan, Shih-I Deshavath, Narendra Naik Wei, Na Singh, Vijay Yoshikuni, Yasuo Zhao, Huimin https://orcid.org/0000-0002-0802-0431 Jin, Yong-Su https://escholarship.org/uc/item/9ns4168n Conventional measurement and verification (M&V) methods for estimating energy savings rely on comparing pre- and post-retrofit performance. They are often time-consuming and unreliable, especially when non-routine events, such as step changes or more gradual changes in building operation, occur during the M&V process. When those events are unrelated to the retrofit intervention and significantly affect building energy consumption, the results will be confounded when the analyst applies the conventional M&V method. In this study, we demonstrated that switchable interventions, such as most HVAC control retrofits, can benefit from a new M&V method that randomly samples whether to implement the baseline or the intervention strategy at a fixed interval (e.g., daily). We tested this novel randomized M&V method on a large public dataset (hourly energy data over 2 years for 639 buildings) covering various climate zones and commercial building types, using a virtual... https://escholarship.org/uc/item/9ns4168n Fri, 5 Jun 2026 00:00:00 +0000 Zou, Aoyu Raftery, Paul Schiavon, Stefano https://orcid.org/0000-0003-1285-5682 Duarte, Carlos https://orcid.org/0000-0002-5129-2969 Brager, Gail https://escholarship.org/uc/item/9hx578g1 The main goal of this project was to demonstrate the energy saving potential from low-cost facility operation and maintenance (O&M) practices and control upgrades while maintaining a comfortable space for teaching and learning. Documented energy savings from improving air conditioning (AC) efficiency can serve as a reference for other schools to emulate. Ultimately, the project priorities were to identify good practices, highlight exemplary solutions, and demonstrate the impact of low cost, replicable O&M practices and control upgrades in schools. https://escholarship.org/uc/item/9hx578g1 Thu, 4 Jun 2026 00:00:00 +0000 Robinson, Alastair Shackelford, Jordan https://orcid.org/0000-0001-7042-6814 Regnier, Cynthia https://escholarship.org/uc/item/1gn0r079 A technology demonstration project funded by the U.S. Department of Energy (DOE) was hosted by Boston Public Schools (BPS). This project evaluated wireless controls technology for lighting systems and plug loads (energy consumed by devices plugged into electrical outlets), implemented along with LED lighting retrofits in two classrooms. This study assesses technology readiness and effectiveness to determine the deployment potential of the technology in schools. https://escholarship.org/uc/item/1gn0r079 Mon, 1 Jun 2026 00:00:00 +0000 Shackelford, Jordan https://orcid.org/0000-0001-7042-6814 https://escholarship.org/uc/item/9kv7f1dx The gray-box modeling approach, which uses a semi-physical thermal network model, has been widely used in building prediction applications, such as model predictive control (MPC). However, unmeasured disturbances, such as occupants, lighting, and in/exfiltration loads, make it challenging to apply this approach to practical buildings. In this study, we propose a hybrid modeling approach that integrates the gray-box model with a model for unmeasured disturbance. After reviewing several system identification approaches, we systematically designed the unmeasured disturbance model with a model selection process based on statistical tests to make it robust. We generated data based on the building model calibrated by real operational data and then trained the hybrid model for two different weather conditions. The hybrid model approach demonstrates an RMSE reduction of approximately 0.2–0.9 ∘C and 0.3–2 ∘C on 1-day ahead temperature prediction compared to the Conventional approach for... https://escholarship.org/uc/item/9kv7f1dx Wed, 27 May 2026 00:00:00 +0000 Ham, Sang Woo https://orcid.org/0000-0003-1776-2610 Kim, Donghun https://orcid.org/0000-0002-1868-6341 https://escholarship.org/uc/item/92b9s515 This document offers support to owners considering optimization upgrades, retrofits, or complete replacement of a central plant, with a particular focus on improving energy efficiency and reliability of the central plant, ultimately leading to reduced energy costs. It outlines recommended steps to prepare for and facilitate a thorough central plant assessment, empowering owners to move forward with the appropriate next steps. While the primary focus is on central plants serving commercial and institutional buildings, the principles and recommendations presented can also be adapted for use in other building types, such as industrial or manufacturing facilities. https://escholarship.org/uc/item/92b9s515 Wed, 27 May 2026 00:00:00 +0000 Hart, Nora Papakyriakou, Ashleigh Shah, Sonam Abram, Tom McKenzie, Nathan Granderson, Jessica https://orcid.org/0000-0002-4536-9560