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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

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

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

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Integration of a Smart Outlet-Based Plug Load Management System with a Building Automation System

The growth of and reliance on renewable energy necessitate a multi-pronged approach to achieve grid reliability and economics. As they represent a notable portion of U.S. energy consumption, commercial buildings must play an active role in this effort. Conserving energy and responding to grid conditions through demand flexibility can be achieved through the integration of major building systems. Integration of plug and process loads with lighting and heating, ventilation, and air conditioning systems maximizes the effectiveness of integrated building energy management. In this research, we demonstrate the integration of smart outlets into a building automation system. We cover the installation process as well as the architecture required for smart outlets to communicate data to the building automation system and to receive commands back. After recording power measurements for one week as a baseline, we configured the building automation system to turn the smart outlets on and off according to a set schedule. This resulted in energy savings of 66% during 1 week on 25 plug loads. This work demonstrates that grid-interactive efficient buildings are achievable through building system integration.

building automation system↗
DOE OSTI2023

Geophysical Constraints on Decarbonized Systems—Building Spatio-Temporal Uncertainties into Future Electricity Grid Planning

Future electricity grids will be characterized by the high penetration of renewables to support the decarbonization process. Yet, this transition will further expose grids to a broad spectrum of geophysical forces, such as weather and climate, land and space, minerals and materials. Understanding their role is thus important to support the grid decarbonization process. Here, we synthesize the current body of knowledge on the relationship between geophysical constraints and electricity grid planning. Additionally, we show that there have been promising advances in the data, methods, and modelling tools needed to incorporate the effect of geophysical constraints on demand, resource availability, and grid operations. There are, however, multiple research avenues that deserve further attention. More system-specific and finer-scale analyses are necessary to better understand how spatio-temporal variability---and associated uncertainty---in geophysical forces affect grid planning. Moreover, we need a broader focus on the multi-sectoral implications of grid decarbonization efforts, so as to limit the risk of unintended consequences. Importantly, all these efforts are challenged by the computational requirements of existing power system models, which often limit our ability to characterize uncertainty, scale analyses across larger domains, or study the multi-sector implications of grid expansion decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Guidance for Integrating Energy Justice and Equity in Building Technology Deployment Programs: Tracking, Reporting, and Maximizing the Flow of Benefits from Building System Technology Deployment Activities to Disadvantaged Communities and Target Sectors

The Federal Justice40 Initiative directs at least 40% of the overall benefits of certain clean energy investments to flow to disadvantaged communities and requires that all federal programs covered by Justice40 consult stakeholders to determine the program benefits, and that the flow of benefits to disadvantaged communities is tracked and reported. Unequal distribution of benefits, in terms of access to clean energy research, design, development, and deployment, can disproportionately benefit or burden certain communities. This can result in higher rates of pollution, negative health effects, and increased energy burdens and insecurities in disadvantaged communities. Programs focused on decarbonizing the built environment can enhance health, quality of life, and economic opportunities for impacted communities. This guidance document, developed by Pacific Northwest National Laboratory and funded by the U.S. Department of Energy’s Building Technologies Office, provides best practices and approaches for incorporating energy justice and equity principles into building technology deployment activities. It provides best practices and recommendations for communicating with and involving disadvantaged communities and target building sectors in program activities, along with methods to monitor and report the distribution of benefits to these sectors. This document lays out a set of strategies, metrics, and best practices that can be implemented over time to apply energy justice and equity approaches, whether the program is just starting out or ongoing. Although this guidance was designed for Building Technologies Office technology deployment programs, the best practices, recommendations, and methods can be valuable to any program concerned with the equitable deployment of clean energy technologies. The goal of this project is to enable the equitable development, deployment, and adoption of clean energy technologies and practices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Processed data from the Building Management System for the System Engineering Building.

The dataset spans November 2018 to May 2020 and includes time-series measurements corresponding to supply and return temperatures of air and water, air, hot water and cold water flow rates, energy and power consumption, set-points etc. as a single CSV file. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A critical review of cyber-physical security for building automation systems

Modern Building Automation Systems (BASs), as the brain that enable the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as the cloud, to enable low-cost remote management, optimized automation via outsourced cloud analytics, and increased building-grid integrations. As smart buildings move towards open communication technologies, providing access to BASs through the building's intranet, or even remotely through the Internet, has become a common practice. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols (i.e., BACnet, KNX, LonWorks, and Modbus) are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. Furthermore, the impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Automated fault detection and diagnosis deployment Internet of Things solution for building energy system

The building sector is the highest energy consumer and ranks first in terms of carbon emissions among all sectors. To address these issues, decarbonization and electrification in the building energy sector are two critical missions of the new US administration. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50–52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostic (AFDD) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. Here, this study reviews existing IoT solutions developed for building energy–related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

42 ENGINEERING↗
DOE OSTI2023

Convergence Rate of Model Reference Adaptive Control with Application to Building HVAC Systems

Model reference adaptive control (MRAC) has been studied for decades and successfully applied in multiple areas, including heating, ventilation, and air conditioning (HVAC) systems for buildings. MRAC is efficient in capturing the time-varying characteristics of buildings' indoor temperatures and outdoor weather environments. In this paper, the rate of convergence of MRAC is investigated, where a direct adaptive control with temperature set point reference tracking is used to regulate the indoor temperatures for buildings. Numerical results show that by controlling the HVAC systems of residential buildings using MRAC, the indoor temperatures converge Q-sublinearly to the desired temperature set points. In addition, the rate of convergence for MRAC is compared with a baseline adaptive model-free control method.

Wu, Tumin↗
DOE OSTI2024

Decarbonizing Building Thermal Systems: A How-to Guide for Heat Pump Systems and Beyond

Buildings account for a substantial portion of carbon emissions, primarily due to the widespread use of fossil fuels in heating systems. Decarbonization of heating is essential to meet climate targets and reduce the environmental impact of buildings. Heat pumps are capable of leveraging renewable energy sources and can provide heating and cooling in an energy-efficient manner. By leveraging heat pump technology, buildings can significantly reduce their carbon footprint, minimize energy consumption, and decrease their reliance on fossil fuels. The design and construction community plays a pivotal role in facilitating the transition to heat pump systems for heating and cooling. However, this transition requires specialized knowledge and expertise. This resource was developed for architects, engineers, and contractors in response to an industry need for a comprehensive technical resource that guides them through the intricacies of heat pump system design, installation, and maintenance. This resource provides detailed information on system sizing, selection of appropriate heat systems, heat sources, and integration with existing building systems. Moreover, it emphasizes best practices for ensuring operational efficiency, system longevity, and reliability. The development of this recourse was a collaborative effort between NREL/DOE Better Buildings Design and Construction Allies and ASHRAE Task Force for Building Decarbonization. This resource is composed of two complimentary portions that will be completed and released on separate time frames. The first portion will be completed and released in 2023, while the second portion will be released in 2024.

building thermal systems↗
DOE OSTI2021

Simulation-based Performance Evaluation of Model Predictive Control for Building Energy Systems

The performance of model predictive control (MPC) can be significantly affected by different choices of controller parameters such as the time intervals for model discretization and control sampling. Due to the lack of a systematic understanding on how these parameters affect control performance, they are usually selected arbitrarily in practice.In this paper, the combined impacts of selected time intervals for model discretization and control sampling on the performance of MPC are comprehensively investigated for the first time through detailed simulations. Specifically, a typical MPC strategy is first designed to improve building operations based on a reduced-order model of building dynamics. Then, the performance of the designed MPC is evaluated against different choices of time intervals for model discretization and control sampling on a simulated office building. The detailed simulation results reveal that the time interval for model discretization has a much greater influence on the performance of MPC than the time interval for control sampling. Although the time interval for control sampling usually receives more attentions in practice, it turns out that the time interval for model discretization affects the prediction performance, cost saving, and computation time simultaneously and more significantly. Therefore, the simulation-based performance evaluation presented here sheds light on the impacts of different time intervals and facilitates their selection for practical applications of MPC to building operations

Huang, Sen↗
DOE OSTI2021

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗
DOE OSTI2025

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

Wu, Tumin [University of Tennessee, Knoxville (UTK↗
DOE OSTI2022

Model Predictive Control for a Grid-interactive Efficient Thermal Storage-integrated Heat Pump System

Building heating and cooling systems can be used to overcome the mismatch between the intermittent supply of renewable power and the fluctuating demand for electricity. A novel underground thermal energy storage integrated with a dual-source heat pump has been proposed to mitigate the mismatch while meeting the thermal demand of buildings efficiently. Conventional thermostat control with heuristic rules cannot provide intelligent decisions to maximize the thermal efficiency and flexibility of the proposed system. Advanced control strategies like model predictive control (MPC) have provided a new paradigm for grid-interactive efficient building operation with the advancement of computation and sensing. This study developed an MPC for the proposed system to provide grid service for Demand Side Management and minimize the operating cost of building owners. A control-oriented dynamic model of the proposed system has been developed. Given an objective function and proper constraints, an optimization problem is formulated to determine the optimal control strategy of the system. Dynamic Programming is adopted to solve the optimization problem. A rule-based control (RBC) is also developed to achieve similar goals. Short-term simulations are conducted to compare the system performance resulting from the two controls. The simulation results indicate that the MPC performs more intelligently than the RBC in charging thermal energy storage and selecting heat pump sources by taking advantage of the predicted cooling demands of the building and the performance of the integrated system. As a result, the MPC could save energy and reduce operating costs compared with the RBC. A case study shows that, for a 3-day operation, the MPC saves 36.9% energy and reduces 38.5% operating cost compared with the RBC.

Shi, Liang↗
DOE OSTI2021

A data-driven network optimisation approach to coordinated control of distributed photovoltaic systems and smart buildings in distribution systems

The increasing integration of distributed energy resources, including demand-side resources and distributed photovoltaics (PVs), into distribution systems has resulted in more complicated power system operation. A data-driven network optimisation approach is proposed to coordinate the control of distributed PVs and smart buildings in distribution networks considering the uncertainties of solar power, outdoor temperature and heat gain associated with building thermal dynamics. These uncertain parameters have a significant impact on the operation and control of distributed PVs and smart buildings, bringing challenges to the distribution system operation. In the proposed data-driven distributionally robust optimisation (DRO) approach, the Wasserstein ball is used to construct an ambiguity set for the uncertain parameters, which does not require the probability distributions to be known. Furthermore, a conditional value-at-risk is incorporated into the Wasserstein-based DRO model and converted into a computationally tractable mixed-integer convex optimisation problem. Benchmarked with robust optimisation and chance-constrained programming, the proposed data-driven model can give a less conservative robust solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Systems and methods for monitoring traffic on industrial control and building automation system networks

Technologies relating to monitoring communications traffic to detect potential attacks on industrial control system networks and building automation system networks are described herein. In an embodiment, a monitoring device receives a plurality of communications from a control network. The monitoring device transmits the communications to a computing device. Based on the communications, the computing device generates a listing of devices that communicated by way of the control network over a period of time, and computes a volume of traffic between each pair of devices in the listing of devices. The computing device then outputs a graphical user interface (GUI) by way of display, the GUI comprising data indicative of the computed volumes of traffic, which may be indicative of a potential attack on the control network.

Jenkins, Chris↗