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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Directed-energy process technology efforts

A summary of directed-energy process technology for solar cells was presented. This technology is defined as directing energy or mass to specific areas on solar cells to produce a desired effect in contrast to exposing a cell to a thermal or mass flow environment. Some of these second generation processing techniques are: ion implantation; microwave-enhanced chemical vapor deposition; rapid thermal processing; and the use of lasers for cutting, assisting in metallization, assisting in deposition, and drive-in of liquid dopants. Advantages of directed energy techniques are: surface heating resulting in the bulk of the cell material being cooler and unchanged; better process control yields; better junction profiles, junction depths, and metal sintering; lower energy consumption during processing and smaller factory space requirements. These advantages should result in higher-efficiency cells at lower costs. The results of the numerous contracted efforts were presented as well as the application potentials of these new technologies.

Alexander, P.↗
DOE OSTI2020

Empowering Energy Efficiency in Existing Big-Box Retail/Grocery Stores (Final Optimization Report)

The Center for Sustainable Energy (CSE), in partnership with the National Renewable Energy Laboratory (NREL), TRC Energy Services, P2S Engineering Inc, Walmart, and five innovative technology providers, are to demonstrate the impact of an integrated suite of pre-commercial energy efficiency (EE) technologies in a large, existing, retail building located within an inland disadvantaged community. Proposed technology packages include three categories of advanced EE solutions: heating, ventilating, air-conditioning, and refrigerating (HVAC/R); lighting; and integrated system and building level controls. The project is designed to impact Walmart’s future store specifications, which can be replicated and deployed in other buildings across California with similar end-use and system characteristics. The following lists the technologies considered for this project: DualCool (HVAC evaporative cooling); Software Motor Company (SMC) (HVAC and refrigeration fan motor); I2S: DC LED lighting; LocBit: building energy management and optimization; Saya: water monitoring.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021. Dataset Description: Pooled Rideshare Acceptance Survey - Phase 1 (2021, N = 5,385). This dataset captures responses from a nationally representative sample of 5,385 adults across the United States to understand public acceptance, preferences, and behavioral intentions related to pooled rideshare (PR) services. The primary objective of this research is to provide actionable insights to inform the design, deployment, and policy development of sustainable shared mobility systems. Data was collected via an online survey administered through a national panel provider. Participants ranged in age from 18 to 95 years, and representation from all U.S. regions. The survey instrument was designed to explore numerous dimensions related to PR adoption including demographic traits, current travel habits, rideshare familiarity, trust, safety, environmental attitudes, and user experience preferences. Both rideshare users and non-users were included, offering a diverse range of perspectives. - Phase_1_Final - The dataset includes survey items developed from literature reviews, and prior field studies. Each row represents an individual respondent, and each column corresponds to a variable such as willingness to use pooled rideshare, attitudes toward specific service features, and sociodemographic data. The data is available in both .CSV and .SAV formats. - Phase_1_Final_MapFile - The accompanying data dictionary explains all variable labels, response scales, and codes. An .XLSX format of the full survey instrument is also included to support interpretation and reuse of the dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Chapter 22: Compressed Air Evaluation Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures (September 2011 - August 2020)

Compressed-air systems are used widely throughout industry for many operations, including pneumatic tools, packaging and automation equipment, conveyors, and other industrial process operations. Compressed-air systems are defined as a group of subsystems composed of air compressors, air treatment equipment, controls, piping, pneumatic tools, pneumatically powered machinery, and process applications using compressed air. A compressed-air system has three primary functional subsystems: supply, distribution, and demand. Air compressors are the primary energy consumers in a compressed-air system and are the primary focus of this protocol. The two compressed-air energy efficiency measures specifically addressed in this protocol are: high-efficiency/variable speed drive (VSD) compressor replacing modulating, load/unload, or constant-speed compressor; compressed-air leak survey and repairs. This protocol provides direction on how to reliably verify savings from these two measures using a consistent approach for each.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Mobility Energy Productivity Evaluation of Prediction-Based Vehicle Powertrain Control Combined with Optimal Traffic Management

Transportation vehicle and network system efficiency can be defined in two ways: 1) reduction of travel times across all the vehicles in the system, and 2) reduction in total energy consumed by all the vehicles in the system. The mechanisms to realize these efficiencies are treated as independent (i.e., vehicle and network domains) and, when combined, they have not been adequately studied to date. This research aims to integrate previously developed and published research on Predictive Optimal Energy Management Strategies (POEMS) and Intelligent Traffic Systems (ITS), to address the need for quantifying improvement in system efficiency resulting from simultaneous vehicle and network optimization. POEMS and ITS are partially independent methods which do not require each other to function but whose individual effectiveness may be affected by the presence of the other. In order to evaluate the system level efficiency improvements, the Mobility Energy Productivity (MEP) metric is used. MEP specifically measures the connectedness of a system while accounting for time and energy externalities of modes that provide mobility in a given location. A SUMO model is developed to reflect real traffic patterns in Fort Collins, Colorado and data is collected by a probe SUMO vehicle which is validated against data collected on a real vehicle driving the same routes through the city. Individual vehicle and system level efficiencies are calculated using SUMO outputs for scenarios which integrate POEMS and ITS independently as well as jointly. Results from application of POEMS and ITS show improvement in energy consumption and travel times respectively when compared to the respective baseline scenarios. Our conclusion is that there are promising synergistic benefits to travel time and energy efficiency when POEMS and ITS are combined.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2006

Magnetic Nozzle and Plasma Detachment Experiment

High power plasma propulsion can move large payloads for orbit transfer (such as the ISS), lunar missions, and beyond with large savings in fuel consumption owing to the high specific impulse. At high power, lifetime of the thruster becomes an issue. Electrodeless devices with magnetically guided plasma offer the advantage of long life since magnetic fields confine the plasma radially and keep it from impacting the material surfaces. For decades, concerns have been raised about the plasma remaining attached to the magnetic field and returning to the vehicle along the closed magnetic field lines. Recent analysis suggests that this may not be an issue of the magnetic field is properly shaped in the nozzle region and the plasma has sufficient energy density to stretch the magnetic field downstream. An experiment was performed to test the theory regarding the Magneto-hydrodynamic (MHD) detachment scenario. Data from this experiment will be presented. The Variable Specific Impulse Magnetoplasma Rocket (VASIMR) being developed by the Ad Astra Rocket Company uses a magnetic nozzle as described above. The VASIMR is also a leading candidate for exploiting an electric propulsion test platform being considered for the ISS.

Chavers, Gregory↗
DOE OSTI2022

Initial Findings from US Department of Energy’s Better Plants Virtual in-Plant Training on 50001 Ready

Manufacturing facilities use about 35% of the domestic energy in the United States every year. Implementing an effective energy management system (EnMS) is one of the most important approaches to improve energy efficiency. However, the implementation of EnMS is low for many countries (including the US) and even for energy-intensive sectors. The reasons for the low implementation rate of energy management systems had been investigated by multiple researchers, but very few studies have focused on the barriers and challenges of implementing ISO 50001-based energy management systems. To contribute to this understudied area, this paper discusses the implementation and outcomes of the first Better Plants 50001 Ready Virtual In-plant Training. This paper first provides an overview of 50001 Ready and the 50001 Ready Navigator Tool. Then, it provides details on this training event and its outcomes. Finally, it discusses findings from the responses to 40 live polling questions about the status of the 25 tasks of the 50001 Ready Navigator for participating companies, key components of the participating manufacturing companies’ energy management systems, and challenges and barriers that these companies are facing. The findings suggest that although many companies understood the importance of an effective energy management system, about half of them do not understand the required resources for building energy management systems, and most of them have only just begun establishing these systems and need more assistance and resources in multiple areas. More specifically, more assistance is necessary for the following: (1) improving corporate management’s understanding of the time and resources needed to build an EnMS as well as the benefits; (2) creating linear regression models for more accurate energy performance tracking; (3) understanding energy use, collecting and analyzing energy performance data; (4) optimizing equipment operational controls, and creating action plans.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Preliminary Process and Instrumentation Design of Advanced Reactor Integration with Refineries and Hydrogen Production Facilities

With the ongoing push to decarbonize energy use and especially greenhouse gas emissions across all sectors, there are incentives to investigate how nuclear reactors may be used to generate clean energy and be used in various energy economies beyond just the electrical grid. Two initial integrations, high temperature steam electrolysis (HTSE) and oil refineries, are investigated in this first DOE Integrated Energy Systems (IES) program detailed industrial integration design report. Increasingly detailed reports are anticipated both for the industries discussed in this report and for additional industries in the future of the program. This report is a robust starting point showing how integration thermodynamic analysis establishes the requirements on the reactor and methods by which those requirements can be evaluated for specific reactor designs. Two Advanced Reactor Demonstration Program awardees are selected as representative designs for their respective technologies: NuScale for light-water reactors (LWRs) and X-Energy for high temperature gas reactors (HTGRs). Other reactor technologies or specific reactor configurations would require specific analysis similar to what is done in this report, thus this report can be a reference point by which to extend this work to other nuclear plant designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Design and performance assessment of a dual-mode latent thermal storage integrated heat pump across multiple climate zones

The electrification of space cooling and heating systems risks overloading the existing electrical grid during peak hours. Heat pumps integrated with thermal energy storage (HP-TES) offer a promising solution by shifting peak loads to off-peak hours, reducing grid strains. This work presents the design and assessment of a dual-mode HP-TES that uses a single 22°C phase-change material (PCM) as a heat source or sink in heating and cooling modes, respectively. Performance assessment was conducted using Modelica-based transient models, and full-year simulations were conducted across eight US climate zones using typical weather data. Two HP-TES performance metrics: peak energy reduction and recharge energy increases, were defined by comparing HP-TES energy consumption with base HP peak consumptions. Annual heating demand reductions (40–65%) exceeded cooling demand reductions (15–20%) due to the elimination of peak-hour backup heating. Cooling mode recharge energy requirements (0–10%) were reduced in locations with lower summer nighttime temperatures, while heating recharge requirements were lower than the high base-peak energy demand from backup heating. Simplified rapid methods that were 10 7 times faster than annual simulations were developed to predict seasonal cooling and heating energy reductions, and recharge energy requirements, with maximum deviations of ±2.5% and ±3.5% points. These methods enabled rapid parametric studies that identified optimal location-specific PCM temperatures between 22°C and 27°C, highlighting the need to consider both discharge and recharge energy requirements to achieve sustainable, energy-efficient peak load shifting across various climate zones.

25 ENERGY STORAGE↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2020

Austin Sustainable and Holistic Integration of Energy Storage and Solar PV [Austin SHINES]. Final Report, Version 2

The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system. The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S. Department of Energy SHINES program metric of $0.14/kWh, in a defined boundary, while enabling a high penetration of distributed PV. Research was categorized in 6 reports (Final Deliverables = FD) listed below, with titles and descriptions indicating which area of understanding was investigated: FD-1: System Levelized Cost of Electricity (System LCOE) Methodology The creation and use of the System LCOE to Serve Load metric that encompasses the holistic, system-level costs and benefits of all resources, and enables them to be evaluated based on their ability to support an efficient and low-cost integrated grid ecosystem. FD-2: Software Platform Product Description The creation of new DER control methodologies deployable within a utility-grade software platform that enable DER's to maximize their benefit within a grid, that is capable of serving load enabling a high penetration of distributed PV generation. FD-3: Optimal Design Methodology Optimal design methodologies for individual DER installations that enable utilities to determine the optimal combinations and sizing for individual DER sites. FD-4: Austin SHINES Ownership and Operation Models for DER System Performance A comparison of multiple DER aggregation and ownership methodologies including direct utility control, third-party aggregator, and autonomous. FD-5: Economic Modeling & Optimization A comparison of multiple DER technology mixes and configurations within the distribution system, providing insight into an optimal blend of technologies that best enable the distribution system to serve load at the lowest cost at high penetrations of solar. FD-6: Fielded Assets Deployed DER assets within the Austin Energy SHINES circuits. Austin SHINES provided an opening for state-of-the-art technology products to be deployed, providing a rich opportunity for improving how each of the products perform as stand-alone products, and in concert with other complementary products. The Austin SHINES project comprised of two key metrics for System LCOE: SystemLCOE_SHINES<$0.14/kWh Modeled ΔSystemLCOE_SHINES/ΔSystemLCOE_Base≥20% at same solar penetration The System LCOE calculation uses the costs of the utility-owned infrastructure as it exists today, the cost of the DERs that exist in the system today, and the cost of the purchase of energy from ERCOT wholesale markets over the course of the calendar year. All costs are on an annualized basis. The capital and operating costs are derived from the rate case, which produces a yearly cost. The net cost of energy and services imported to the system is integrated over the test year, as is the load served and solar penetration. The first metric was easily achieved by every scenario considered. The goal was set when the Department of Energy’s SHINES Funding Opportunity Announcement was written in 2015 and was a more difficult target at the time. Due mostly to rapidly declining costs for DERs and the significant decrease in the Electric Reliability Council of Texas (ERCOT) energy market prices, which results in lower net cost of energy purchases, the System LCOE is well below this target for all scenarios considered. A fleet of DERs can assume different mixtures, each of which serves the load at a different LCOE. The optimal mixture of DERs serves load at the smallest System LCOE. The second metric (hereinafter %delta metric) asks that the holistic DERMS controls reduce the incremental cost above the baseline of going to a high solar penetration future by at least 20% as compared to the case of a DER deployment with no sophisticated controls (autonomous). Many comparison sets were created throughout this project. Physical technology was installed for informing utility engineering and testing several types of operational control schemes, through the DERMS. The types of operational control which were compared for valuation of the System LCOE Metric were: Holistic control = using the full suite of the DERMS platform to decide and optimize how/why the systems operate depending on weather, market, and reliability signal input. Autonomous control = a local mode at the asset site, wherein a schedule operates the asset, with visibility into performance only No control = the baseline for comparing value against the other two types of control The types of ownership control included: Direct Utility control = the utility dispatches a signal to each asset Third-Party Aggregator = a third party aggregates a fleet of assets and the utility dispatches one signal for all Autonomous = a local mode is set for operation at the asset site, wherein a schedule operates the asset, with visibility into performance only The types of control methodologies deployable within a utility-grade software platform included: Utility Peak Load Reduction = Lower transmission cost obligation Day-Ahead Energy Arbitrage = Realize economic value through price differential Real-Time Price Dispatch = Realize economic value from real-time price spikes Voltage support = Reduce losses and increase solar generation Distribution Congestion Management = Increase local grid reliability Demand Charge Reduction = Lower customer bills and realize system benefit The fielded assets deployed for the project were: Utility Scale Kingsbery Energy Storage System: 1.5 MW / 3 MWh Li-Ion battery storage Mueller Energy Storage System: 1.75 MW / 3.2 MWh Li-Ion battery storage, 7 Energy Storage Units (250 kW each) La Loma Community Solar: 2.6 MW Commercial Scale Aggregated storage installations at 3 sites, with existing solar (300+ kW): One 18 kW / 36 kWh Li-Ion battery storage Two 72 kW / 144 kWh Li-Ion battery storage Residential Scale Aggregated storage installations: -Six stationary battery storage systems (10 kWh each) at homes with existing solar -One Electric Vehicle installed as Vehicle-to-Grid (V2G) Utility-Controlled Solar via Smart Inverters at 12 homes Autonomously-Controlled Smart Inverters at 6 homes Over the course of the project, Austin SHINES undertook installing more than 3 MW of distributed battery energy storage, smart PV inverters, a DER control platform, and other enabling technologies utilizing customer and utility locations and aggregation models. All of these resources were to be integrated and optimized at the utility level. DER assets and control methodologies were designed to achieve a credible pathway to a System LCOE for energy delivered to load of $0.14//kWh or less by 2020, while maximizing distributed solar generation and maintaining acceptable standards of power quality. The project also established a template for other regions to follow, to maximize the adoption of distributed solar PV in support of an economic and efficient grid. In total, the Austin SHINES project added value to the DER subject area in each layer of integration. From utility, to commercial to residential scales, the sheer hierarchy of communication and coordination was a significant accomplishment in addition to learnings from what these communications revealed was unique to each. Economically, the most effective method demonstrated was the criticality of planning phases. Contingencies and multiple projection scenarios helped guide the project to deploy optimal design as close as feasible, in real world conditions. The project and reports will serve public benefit by outlining specific areas of DER strategy and installation where many stakeholders and needs can be addressed with improved efficiency. Overall, communities and utilities should use the results to guide the increasing options available for powering the grid with DER, renewables, and carbon considerate energy.

14 SOLAR ENERGY↗
DOE OSTI2020

Validated model of a thermoelectric heat pump clothes dryer using secondary pumped loops

The energy associated with clothes drying makes up 4% of the total residential electrical energy consumption in the US. The cost is high since most clothes dryers use electric resistance heating which is inexpensive but also energy inefficient. State-of-the-art vapor-compression heat pump clothes dryers offer significant energy savings but have limited market penetration in the US. Here, a new configuration of clothes dryer was studied that utilizes a solid-state thermoelectric heat pump with pumped secondary water loops and conventional fin-and-tube water-to-air heat exchangers. Experimental results are presented for the thermoelectric dryer prototype with a combined energy factor of 6.89 lb BDW /kWh (specific moisture extraction rate of 1.71 kg w /kWh) and a dry time of 84 min for a standard load size of 8.45 lb (3.83 kg) with 57.5% starting moisture content. This is a 85% energy efficiency improvement over baseline electric resistance dryers. The efficiency and drying time results achieved are similar to vapor compression heat pump dryers. Compared to previous air-based thermoelectric clothes dryers, the energy efficiency has been increased by 6%, but drying time has been reduced by as much as 47% using secondary pumped loops and separate heat exchangers, which represents a significant advancement in the technology. In addition to the experimental prototype, a model was also developed to study the performance. The model was validated against experimental prototype data and used to identify the range of performance (dry time and efficiency) that could be expected of the design.

42 ENGINEERING↗
DOE OSTI2020

Design and analysis of optimal pre-cooling in residential buildings

Existing pre-cooling strategies provide a means of shifting or reducing the peak demand and/or energy cost in residential buildings. However, majority of them are rule-based and therefore may not be optimal in terms of cost saving, leaving room for improvement. In this paper, an integer linear programming problem that accounts for the thermal properties of a specific home, HVAC system capacity, utility rate structure, and weather conditions and makes use of a home thermal model is formulated. This problem determines the HVAC on/off control signal that minimizes the 24-h energy cost while maintaining thermal comfort and calculates the corresponding optimal indoor air temperature. The model is constructed using home thermal properties identified via data training in real-time. Through simulation, the energy performance of the proposed optimal pre-cooling strategy is investigated and compared with three rule-based operation strategies from the literature. It is found that the optimal strategy requires the least energy consumption without sacrificing thermal comfort. The superb energy performance of the optimal strategy is attributed to a longer runtime of the HVAC system in cool outdoor air conditions and to the elimination of deadband in HVAC operation, which is required by the rule-based strategies, to allow the indoor air temperature to stay near the thermal comfort upper bound as much as possible. In terms of energy cost, the rule-based operation strategies require 3.52, 1.90, and 2.79, respectively, while the optimal strategy only requires 1.52. These figures represent a saving of 56.82%, 20.00%, and 45.52%, respectively. The results suggest that the optimal strategy is indeed significantly more effective than the existing rule-based operation strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments

The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

An Integrated Circuit for Radio Astronomy Correlators Supporting Large Arrays of Antennas

Radio telescopes that employ arrays of many antennas are in operation, and ever larger ones are being designed and proposed. Signals from the antennas are combined by cross-correlation. While the cost of most components of the telescope is proportional to the number of antennas N, the cost and power consumption of cross-correlationare proportional to N2 and dominate at sufficiently large N. Here we report the design of an integrated circuit (IC) that performs digital cross-correlations for arbitrarily many antennas in a power-efficient way. It uses an intrinsically low-power architecture in which the movement of data between devices is minimized. In a large system, each IC performs correlations for all pairs of antennas but for a portion of the telescope's bandwidth (the so-called "FX" structure). In our design, the correlations are performed in an array of 4096 complex multiply-accumulate (CMAC) units. This is sufficient to perform all correlations in parallel for 64 signals (N=32 antennas with 2 opposite-polarization signals per antenna). When N is larger, the input data are buffered in an on-chipmemory and the CMACs are re-used as many times as needed to compute all correlations. The design has been synthesized and simulated so as to obtain accurate estimates of the IC's size and power consumption. It isintended for fabrication in a 32 nm silicon-on-insulator process, where it will require less than 12mm2 of silicon area and achieve an energy efficiency of 1.76 to 3.3 pJ per CMAC operation, depending on the number of antennas. Operation has been analyzed in detail up to N = 4096. The system-level energy efficiency, including board-levelI/O, power supplies, and controls, is expected to be 5 to 7 pJ per CMAC operation. Existing correlators for the JVLA (N = 32) and ALMA (N = 64) telescopes achieve about 5000 pJ and 1000 pJ respectively usingapplication-specific ICs in older technologies. To our knowledge, the largest-N existing correlator is LEDA atN = 256; it uses GPUs built in 28 nm technology and achieves about 1000 pJ. Correlators being designed for the SKA telescopes (N = 128 and N = 512) using FPGAs in 16nm technology are predicted to achieve about 100 pJ.

ASIC↗
DOE OSTI2020

Brackish water desalination using reverse osmosis and capacitive deionization at the water-energy nexus

Here, we present a critical review of the reported performance of reverse osmosis (RO) and capacitive deionization (CDI) for brackish water (salinity < 5.0 g/L) desalination from the aspects of engineering, energy, economy and environment. We first illustrate the criteria and the key performance indicators to evaluate the performance of brackish water desalination. We then systematically summarize technological information of RO and CDI, focusing on the effect of key parameters on desalination performance, as well as energy-water efficiency, economic costs and environmental impacts (including carbon footprint). We provide in-depth discussion on the interconnectivity between desalination and energy, and the trade-off between kinetics and energetics for RO and CDI as critical factors for comparison. We also critique the results of technical-economic assessment for RO and CDI plants in the context of large-scale deployment, with focus on lifetime-oriented consideration to total costs, balance between energy efficiency and clean water production, and pretreatment/post-treatment requirements. Finally, we illustrate the challenges and opportunities for future brackish water desalination, including hybridization for energy-efficient brackish water desalination, co-removal of specific components in brackish water, and sustainable brine management with innovative utilization. Our study reveals that both RO and CDI should play important roles in water reclamation and resource recovery from brackish water, especially for inland cities or rural regions.

42 ENGINEERING↗
DOE OSTI2023

Performance Evaluation and Optimal Design Analysis of Continuous-Operation Solar-Driven Cooling Absorption Systems With Thermal Energy Storage

A solar absorption cooling system consisting of a flat plate collector, thermal energy storage tank, and absorption chiller is analyzed in this work. A dimensionless model is developed from the energy balance on each component and the chiller's characteristic performance curves. The model is used to determine the interaction and influence of different parameters such as tank size, solar collector area, chiller size, cooling load, cooling temperature, heat loss, and mass flow rates on the performance. From the analysis, smaller solar collector areas are required for lower cooling loads and smaller tank volumes. A specific cooling load of 1 x 10^-5 will require a specific solar collector area between two and six times larger, depending on the initial tank temperature, than the area required for a baseline system that considers typical commercial design and operation parameters. A similar behavior was observed for the specific tank volume. For the baseline system, the minimum specific area of the collector of 9.57 is achieved for an initial tank temperature of 1.19. For a cooling load of 1 x 10^-5, the optimum initial tank temperature will be 1.11 that results in a minimum specific solar collector area of 25.26. A specific tank volume of 4 x 10^-4 will also have an optimum initial tank temperature of 1.11 that minimizes the specific solar collector area to a value of 28.18. The approach and analysis in this work can be used to determine design parameters for solar absorption cooling systems based on a proper relation among system's dimensions to achieve optimum operation.

cooling load↗
DOE OSTI2022

Adoption Pathways for DC Power Distribution in Buildings

Driven by the proliferation of DC energy sources and DC end-use devices (e.g., photovoltaics, battery storage, solid-state lighting, and consumer electronics), DC power distribution in buildings has recently emerged as a path to improved efficiency, resilience, and cost savings in the transitioning building sector. Despite these important benefits, there are several technological and market barriers impeding the development of DC distribution, which have kept this technology at the demonstration phase. This paper identifies specific end-use cases for which DC distribution in buildings is viable today. We evaluate their technology and market readiness, as well as their efficiency, cost, and resiliency benefits while addressing implementation barriers. The paper starts with a technology review, followed by a comprehensive market assessment, in which we analyze DC distribution field deployments and their end-use characteristics. We also conduct a survey of DC power and building professionals through on-site visits and phone interviews and summarize lessons learned and recommendations. In addition, the paper includes a novel efficiency analysis, in which we quantify energy savings from DC distribution for different end-use categories. Based on our findings, we present specific adoption pathways for DC in buildings that can be implemented today, and for each pathway we identify challenges and offer recommendations for the research and building community.

24 POWER TRANSMISSION AND DISTRIBUTION↗