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At least 343 records · Page 19

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DOE OSTI2023

End-Use Analysis of ASHRAE Standard 90.1-2019

This article summarizes the analysis conducted by Pacific Northwest National Laboratory (PNNL), assessing expected end-use energy consumption in commercial buildings, based on recent editions of the model energy code for the commercial sector, ANSI/ASHRAE/IES Standard 90.1, Energy Standard for Buildings Except Low-Rise Residential Buildings. The results represent simulated energy use based on) Commercial Prototype Building Models1 across representative climate zones in the United States, as defined by Standard 90.1. PNNL examined the resulting simulation outputs to assess how energy is used across primary systems within prominent U.S. commercial building types to understand how energy is used in each building type at the end-use level and to identify areas for improvements in future code cycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Building the Financial Business Case for Resilience

This fact sheet is designed to help owners, operators, occupants, and investors in commercial buildings and other sectors to understand and address emerging issues in resilience. It includes resources from DOE’s Better Buildings Financing and Resilience Roadmap to identify key issues in measuring, managing, and mitigating resilience risk.

Resilience, Resiliency, Commercial building, comme↗

DOE OSTI2022

Modeling Air Handling Units to Create a Diverse Fault Dataset for FDD Innovation: Lessons Learned and Recommendations

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault datasets for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling unit and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for the air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, two detailed AHU models, which included the single duct AHU and dual duct AHU developed in the Modelica language and HVACSIM+ were employed to carry out annual simulations of numerous common sensor faults, mechanical faults, and control sequence faults. The fault inclusive data were then validated by comparing fault effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. We report some lessons learnt during the efforts of validating the high volumes of the FDD data sets. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

DOE OSTI2022

Development of a Annual Air Handling Unit Fault Dataset for FDD Tools: Lessons Learned and Considerations for FDD Developers

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault data for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling units and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for a single duct air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, a detailed AHU model was employed to carry out annual simulations of numerous common sensor and mechanical faults, which were then validated by comparing their effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗

DOE OSTI2021

Research challenges and directions in HVAC fault prevalence

This study provides a review of the current state of knowledge, gaps, and potential value in research on the prevalence of faults in commercial buildings. Two separate efforts were made in this study: (1) we performed a literature review to determine the extent of currently available fault prevalence data for heating, ventilation, and air-conditioning (HVAC) systems, and (2) we conducted dozens of interviews with subject matter experts and stakeholders to determine the HVAC fault data that would be of greatest value. Through the literature review and interviews, we discovered unmet needs for empirical data on the prevalence of faults at the desired level of granularity, consistency, and scale; this lack of data leads us to recommend future work studying commercial buildings’ HVAC fault prevalence, with robust fault taxonomy and a variety of meaningful fault prevalence metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads

Protection equipment are used to prevent damages to induction motor loads by isolating those from the power network in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's response moments after a fault has occurred. This article proposes an optimization based framework to generate composite protection models for commercial building motor loads. Introducing a mathematical abstraction, the task of finding a suitable (simplified) model of the composite protection scheme is formulated as a nonlinear regression problem. Numerical examples are provided to illustrate the application of the framework.

Kundu, Soumya↗

DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Identifying Regions Favorable for Geothermal Heating and Cooling Storage

Space heating and cooling represents the single largest category of in building energy use for U.S. residential and commercial buildings, with heating representing 61% of residential and 46% commercial energy consumption. Building heating technologies are dominated by natural gas technologies, and are an important opportunity for building electrification to enable a transition to a low CO 2 energy system. FLXenabler study is a joint analysis effort among multiple analysis teams at NREL and focused on examining the role of geothermal heating and cooling (GHC) system with thermal energy storage (TES) providing flexibility. Utilizing information from ResStock the amount of energy consumption associated with heating and cooling by state was calculated. We applied adjusted load shapes to estimate the a maximum grid savings potential of using TES to address building space conditioning. Normalizing grid, fuel, and emissions impacts locations with higher favorability for further study in FLXenabler were identified.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Characterization of the indoor near-field aerosol transmission in a model commercial office building

To evaluate the exposure potential of infectious aerosols containing SARS-CoV-2 in an office building setting, synthetic test aerosols were used to experimental study airborne particle transmission in a multizone small office test building at the Oak Ridge National Laboratory. Nine measurement points in a single zone using active aerosol impactors report that the coefficient of variation of the time-averaged concentration is <10% in two campaigns and < 15% in one campaign, so a nearly well-mixed condition was noted. To understand the effect of HVAC system operation on the dynamic concentration of aerosols in office spaces, an aerosol transport model that includes factors such as outside air (OA) ratio, filtration, return air fraction, transport loss in air ducts, and particle deposition has been developed. The results of model fitting demonstrate strong agreement with experimental data. Overall, our investigation finds the return air fraction effects outweigh other mechanisms for the aerosol recirculation in this study, and the impact of air change rate (ACR) is more important than the small particle deposition for aerosol removal. Because ACR dominates the aerosol transport, the full model can be simplified to just one factor, the ACR, while maintaining an acceptable representation of the experimental data.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Cloud-Control of Legacy Building Automation System: A case study

As Internet of Things devices and cloud-based platforms become more mature, Energy Management and Information Systems (EMIS) are increasingly gaining momentum in the building industry. In large commercial buildings, Fault-Detection and Diagnostic (FDD) and energy information systems (EIS) are now established technologies with tens of providers and thousands of deployment sites across North America. The new frontier for the EMIS technology is now represented by control systems that use advanced system optimization (ASO) methods to improve the operations of the HVAC system. Given the complexity of the integration of such systems with the existing building automation systems (BAS) and the higher risk involved with direct control of the HVAC, these systems are still emerging in the market. This paper presents the results of a project in which a start-up company partnered with a research institution to develop a cloud-based software EMIS solution and deployed it in a university campus in California. The software system included advanced sensing, data acquisition, storage and advanced control and analytics applications developed on top of the native BAS. The new platform controls ten buildings on the campus and the FDD and the ASO applications deployed on this platform were able to generate energy savings of up to 35% and 25% in certain buildings for each functionality respectively. Where the platform did not save energy, it improved building service (air quality). Lessons learned include the importance of collaborating with and training the building operators and evaluating whether the legacy system can work reliably with the new technology.

Prakash, Anand Krishnan↗

DOE OSTI2020

Scaling Energy Efficient Retrofits for Small Commercial Apartment Buildings

With support from the U.S. Department of Energy’s (DOE) Building Technologies Office (BTO), the International Center for Appropriate and Sustainable Technology (ICAST) recently completed a three-year cooperative agreement to scale energy efficiency retrofits (EER) on small multifamily (MF) buildings. ICAST EER strategies ranged from low-hanging “direct install” of measures such as LED lighting, low-flow showerheads and aerators, and smart thermostats to major strategies such as HVAC replacement with high-efficiency boilers or heat pumps. As feasible, some projects also included the addition of renewable energy sources such as photo voltaic (PV) solar. When ICAST began the BTO project, it operated in two states and oversaw EER at approximately 80 MF buildings per year. With assistance from BTO, ICAST has grown significantly and now has staff in six states with MF EER projects in another seven, and performed EER on 956 MF buildings. ). ICAST was able to successfully execute this project by 1) Improving viability and efficiency of its processes, 2) Launching two new services and 3) Creating an affiliate program. For the most part, ICAST focused on a specific type of MF property: naturally occurring affordable housing (NOAH), because it is a significantly underserved market within the hard-to-serve MF market. NOAHs are typically smaller properties (5 to 64 units), owned by small organizations or individual investors looking for positive cash flow. ICAST believes the NOAH market can be successfully served with a one-stop-shop approach that makes it easy, hassle-free, and cost-effective for owners to acquire green upgrades for their property(ies). With the assistance of BTO funding, ICAST successfully used the cited EER methods and strategies to scale-up its OSS approach to service a greater number of MF housing and expand into new geographies. Additionally, support from BTO helped ICAST create self-sustaining programs which will not need to rely on on-going funding.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Advanced Energy Design Guide for K-12 School Buildings (AEDG) Training: Cooperative Research and Development Final Report, CRADA Number CRD-18-00761

U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (BTO), Commercial Buildings Integration (CBI) Program supports the adoption of zero energy ready buildings design practices through targeted Science, Technology, Engineering, and Mathematics (STEM) workforce development. The National Renewable Energy Laboratory (NREL) identified the opportunity to provided targeted training to those professionals that have the greatest potential to impact adoption and successful design outcomes of zero energy ready buildings projects. In January 2018, ASHRAE released Achieving Zero Energy: Advanced Energy Design Guide for K-12 School Buildings (AEDG). The AEDG was developed in collaboration with NREL, American Institute of Architects (AIA), American Society of Heating, Refrigeration and Air-conditioning Engineers (ASHRAE), U.S. Green Building Council (USGBC), and Illuminating Engineers Society (IES). The purpose of this CRADA was to create a partnership between NREL, AIA, ASHRAE, USGBC, and IES to create and host on-demand, web-based training based on the AEDG.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Las Vegas Block Group Buildings Data

These data include a comprehensive summary of all residential and commercial buildings in the Las Vegas Assessors office dataset as it was on Feb 28th 2021. Building level data has been summarized to the US Census 2020 Block Group geographies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.

advanced metering infrastructure (AMI)↗

DOE OSTI2023

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

AMI↗

DOE OSTI2024

Leveraging NREL's ResStock & ComStock Dataset to Evaluate Building Stock Electrification: Preprint

Residential and commercial buildings accounted for 40% of U.S. energy consumption in 2022 and represent a significant opportunity for decarbonization through energy efficiency and electrification, and for grid planning. Building stock energy modeling is a powerful tool that can evaluate what-if scenarios as utilities, municipalities, policymakers, building owners and others work towards equitable building decarbonization and climate goals. This presentation will highlight several high-impact use cases of the National Renewable Energy Laboratory (NREL)'s highly granular, bottom-up building stock energy modeling tools, ResStock and ComStock. These use cases cover a wide range of project scale, from neighborhood electrification analysis and municipality long-term energy planning, to state energy code development and national policy evaluation. This presentation will showcase specific real-world applications for which ResStock and ComStock have been utilized across the country, including California codes and standards cost-effectiveness analysis, New York City affordable housing electrification cost gap analysis, and California targeted electrification and gas decommissioning analysis. For each use case, this presentation will illustrate how ResStock and ComStock played a crucial role in accurately characterizing regional building stocks, providing discrete and aggregated end-use load shapes, and calculating lifecycle consumption, emissions, and costs for a variety of building electrification strategies and scenarios. Finally, this presentation will demonstrate how the data provided by ResStock and ComStock can help unlock significant outcomes for these use cases, including but not limited to, customer bill impact, incentive and program design, and energy equity analyses.

building stock modeling↗

DOE OSTI2020

DE-EE0007069 – Location, Location, Efficiency! (L.L.E!) (Final Technical Report)

As a participant in Department of Energy's national Better Buildings Challenge, the City of Milwaukee's Environmental Collaboration Office and local partners developed a program to bundle and deliver energy efficiency services to commercial buildings and help bring energy efficiency technologies developed by DOE's Building Technology Office to market. This report summarizes the programs and its results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗