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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

HunStat – a simple and low-cost potentiostat for analytical and educational purposes

We have developed a truly low-cost (15 USD), simple do-it-yourself (DIY) potentiostat with compact dimensions. The output potential range of this device is between ±1.65 V. The developed instrument takes advantage of a Seeeduino XIAO microcontroller equipped with 10 bit digital-to-analog (D/A) and 12 bit analog-to-digital (A/D) converters and supports various voltammetry techniques, including cyclic voltammetry (CV), differential pulse voltammetry (DPV), and chronoamperometry (CA). Interested users are provided with circuit diagrams, bill of materials, and design files. Additionally, software components are also provided free of charge, including an Arduino sketch and control software. The software enables easy manipulation of electrochemical parameters and visualization of results. The presented design introduces a simple and low-cost DIY potentiostat recommended for both analytical and educational purposes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

HunStat2 – a simple and low-cost potentiostat with electrochemical impedance spectroscopy capability

We have developed a low-cost (30 USD), simple do-it-yourself (DIY) potentiostat with cyclic voltammetry (CV), open circuit potential (OCP) and electrochemical impedance spectroscopy (EIS) capability. The HunStat2 potentiostat is based on Analog Devices' AD5941 Analog Front End chip, which significantly simplifies the construction of potentiostats for both direct and alternating current (DC and AC, respectively) techniques. Interested readers are provided with circuit diagrams and a bill of materials to build the potentiostat on their own. In addition, control software is also provided free of charge. The software enables acquisition and visualization of data. In summary, HunStat2 introduces a simple and low-cost DIY potentiostat recommended for both analytical and educational purposes.

Vamos, Istvan [Lajos Petrik Vocational Chemistry S↗
DOE OSTI2022

Synthetic data generation for machine learning model training for energy theft scenarios using cosimulation

Abstract Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Methodology to assess “no-touch” building audit software using simulated utility data

Building audits are conducted in many commercial buildings to identify opportunities to reduce energy costs and improve building operation. Because audits require significant effort by building engineers, they are usually only affordable for larger commercial buildings. “No-touch” building audit tools have thus been developed to identify potential savings based on a simplified analysis of building energy consumption patterns via high-level energy data such as monthly utility bills. This paper presents a comprehensive and standardized methodology to evaluate the accuracy of no-touch audit tools in detecting and diagnosing building energy problems and quantifying potential energy savings. The test suite is based on output data from a well-characterized set of building energy models, and the methodology is illustrated by applying it to a representative no-touch building audit tool. Results show that the tool estimates building energy end uses with reasonable accuracy but is less accurate in identifying probably causes of high energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Magnetic fluctuations and the spin–orbit interaction in Mott insulating CoO

Motivated by the presence of an unquenched orbital angular momentum in CoO, a team at Chalk River, including a recently hired research officer Roger Cowley, performed the first inelastic neutron scattering experiments on the classic Mott insulator. Despite identifying two magnon modes at the zone boundary, the team was unable to parameterise the low energy magnetic excitation spectrum below TN using conventional pseudo-bosonic approaches, instead achieving only qualitative agreement. It would not be for another 40 years that Roger, now at Oxford and motivated by the discovery of the high-Tc cuprate superconductors, would make another attempt at the parameterisation of the magnetic excitation spectrum that had previously alluded him at the start of his career. Upon his return to CoO, Roger found a system embroiled in controversy, with some of its most fundamental parameters still remaining undetermined. Faced with such a formidable task, Roger performed a series of inelastic neutron scattering experiments in the early 2010s on both CoO and a magnetically dilute structural analogue Mg 0.97 Co 0.03 O. These experiments would prove instrumental in the determination of both single-ion and cooperative magnetic parameters for CoO. Both these sets of parameters would eventually be used in a spin–orbit exciton model, developed by his longtime friend and collaborator Bill Buyers, to successfully parameterise the complex spectrum that both measured at Chalk River almost 50 years prior. The story of CoO is of one that has come full circle, one filled with both spectacular failures and intermittent, yet profound, little victories.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A comparative analysis of US state-level policies and programs to advance energy justice

Abstract The US energy system is undergoing massive changes that have environmental, technological, and societal implications. Decisions and actions taken now will dramatically alter the trajectory of our future energy system. Though new technologies can lessen the dangers of anthropogenic climate change, an effective and sustainable transition requires addressing social justice issues as a priority. To this end, many states have implemented policies and programs that address energy justice. A formal survey of state-level energy justice policies and programs is needed to better understand the methods used to assist communities targeted and the impacts of these efforts. Such an analysis should include an analysis of the metrics used to judge the effectiveness of the enacted policies and programs. In this paper, we analyze the energy justice policies and programs of seven different US states. From this analysis, we identify three important aspects of state energy policies. First, most policies and programs do not articulate their goals, nor cite metrics to judge their successes. This lack of transparency and accountability is a major roadblock to truly just solutions. Second, states focus on a very narrow range of solutions for energy justice issues. The most prevalent being utility bill assistance, which does not address the systemic and enduring challenges faced by many low-income or historically marginalized communities. Lastly, comprehensive energy policy does not acknowledge and address housing, employment, education, and healthcare inequities that exacerbate energy system inequities. The work presented in this paper sheds light on the progress of state-level energy justice policies and programs across the United States, and we argue more work needs to be done to understand best practices in energy justice policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Endowing low fatigue for elastocaloric effect by refined hierarchical microcomposite in additive manufactured NiTiCuCo alloy

Abstract NiTiCu-based shape memory alloys have been considered as ideal materials for solid-state refrigeration due to their superb cycling stability for elastocaloric effect. However, the embrittlement and deterioration caused by secondary phase and coarse grains restrict their applications, and it is still challenging since the geometric components are required. Here, bulk NiTiCuCo parts with excellent forming quality were fabricated by laser powder bed fusion (LPBF) technique. The as-fabricated alloy exhibits refined three-phases hierarchical microcomposite formed based on the rapid cooling mode of LPBF, composed of intricate dendritic Ti 2 Ni–NiTi composite and nano Ti 2 Cu embedded inside the NiTi-matrix. This configuration endows far superior elastocaloric stability compared to the as-cast counterpart. The low fatigue stems from the strong elastic coupling between the interphases with reversible martensite transformation, revealed byin-situsynchrotron high-energy x-ray diffraction. The fabrication of NiTiCuCo alloy via LPBF fills the bill of complex geometric structures for elastocaloric NiTiCu alloys. The understanding of interphase micro-coupling could provide the guide for designing LPBF fabricated shape memory-based composites, enabling their applications for special demands on other functionalities.

Engineering↗
DOE OSTI2024

The resilience value of residential solar + storage systems in the continental U.S.

Abstract Behind the meter rooftop solar plus storage (PVESS) has the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Whereas the bill reduction and environmental benefits of PVESS are well studied, its monetary resilience benefits are less understood. The increasing trend of power interruptions driven by extreme weather events heightens the need to understand these benefits. This study leverages various publicly available datasets to perform a cost benefit analysis of adding to determine the resilience value of PVESS for a typical single family home in each county in the continental U.S. We find that PVESS is very effective to technically mitigate interruptions across the country. However, the monetary benefits in the base case only cover about 14% of battery costs, with no county exceeding 60%. This is somewhat expected, given that PVESS provide other monetary benefits that are not part of this analysis. Through sensitivities, we find that higher frequency of extreme weather events roughly triples the resilience value of PVESS and that higher values of lost load double the same metric. Our sensitivity analysis shows that the benefit cost ratio of PVESS for customers living in areas with higher-than-average frequency of long duration interruptions and value of lost load is already above one even without considering other value streams. We conclude with recommendations that regulators and utilities could implement to enable customers to calculate and capture the resilience value of PVESS more efficiently.

Baik, Sunhee↗
DOE OSTI2021

A Data-Driven Approach to Nation-Scale Building Energy Modeling

In 2019, 125 million U.S. residential and commercial buildings consumed $412 billion in energy bills. These buildings currently consume 40% of the nation's primary energy, 73% of electricity, 80% of energy during peak electric grid use, and responsible for 39% of greenhouse gas emissions [14]. Urban-scale building energy modeling has grown significantly in the past decade, allowing individual campuses or communities of buildings to be modeled, simulated, and cost-effective solutions for intelligent management to be identified and implemented. While traditionally limited to individual counties and usually less than 2,000 buildings, the Automatic Building Energy Modeling (AutoBEM) soft-ware suite has been developed to process unconventional, nation-scale data sources to generate unique OpenStudio and EnergyPlus models of each building. Through the use of High Performance Computing (HPC) resources, every U.S. building has been simulated. This paper showcases the data layout, node partitioning, algorithmic approaches, and analytic results that were used to create, share, and analyze 124.4 million U.S. building models.

Berres, Andy↗
DOE OSTI2022

Effectiveness of Privacy Techniques in Smart Metering Systems

Smart grid technologies enable timely energy billing for residential homes. The ability to react to energy demands during peak hours allows energy providers to conserve power and operate efficiently. However, these data streams are also susceptible to privacy attacks within the energy company and from outside hackers. We implemented four different privacy models: k-anonymous, l-diversity, t-closeness, and ε-differential privacy. We demonstrate the models’ effectiveness using a real-world dataset composed of 15 different residential households with energy consumption data spanning over a year.

Peralta-Peterson, Martin↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate

In residential buildings, rapid improvements in sensors, communication, and information technology have enabled occupancy-based building controls. These controls utilize occupancy information and modify the operation of the heating, ventilation, and air-conditioning (HVAC) system to minimize excess HVAC energy use, especially when the building is unoccupied. This reduces the total building energy consumption and utility bills while maintaining thermal comfort. In this paper, we present two novel occupancy-driven controls - reactive control and predictive control - and compare their performance. We model an all-electric residential community based on a 27- home community in Basalt, Colorado, in the United States. We simulated various scenarios, considering different temperature setback and control algorithms, to analyze the community-scale impact of these occupancy-based controls. The results show that total HVAC energy savings in a building ranges from 1%- 20% compared to the baseline scenario without occupancy-based controls. The energy-saving potential is highly correlated with the occupancy pattern and temperature setback in the building.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2024

Deep Reinforcement Learning for Microgrid Cost Optimization Considering Load Flexibility

This paper proposes a novel Soft-Actor-Critic (SAC) based Deep Reinforcement Learning (DRL) method for optimizing the cost of microgrid operation by leveraging load flexibility. The proposed SAC-DRL method is designed to coordinate the control of distributed energy resources (DERs) and flexible load, addressing practical energy billing formation by power distribution utilities. Key contributions include an innovative reward function to mitigate sparse reward challenges and a mixed control strategy for discrete and continuous variables, ensuring radial network topology and minimizing power loss. We evaluate the proposed method on the model of a real microgrid located in Southern California, U.S.. The SAC-DRL model is tested to demonstrate its efficacy in reducing grid dependence, optimizing resource use, and minimizing costs. The results highlight the potential of DRL in modern energy systems, offering a sustainable and economically efficient solution for energy management in microgrids.

deep reinforcement learning↗
DOE OSTI2020

Analysis of the Value Proposition of High-Efficiency, Multijunction Solar Modules for Residential Rooftop Installations

Utilizing detailed bottom-up models, we analyze the potential markets for high-efficiency photovoltaic modules in the United States. We first estimate the fraction of area-constrained residential rooftops that could benefit from increasing the availability of high-efficiency systems. We then model the impact of efficiency on installed system costs in these area-constrained scenarios. Finally, we explore the value proposition of high-efficiency, fixed-tilt micro-concentrator photovoltaic modules in a series of case studies of residential customers, modeling the levelized cost of energy, payback period, and annual bill savings. We find that efficiency can provide significant savings in installed system cost and improve value to the solar system owner. The improvement in value depends on location and the size of the rooftop, as well as the ability of a given technology to collect diffuse light and achieve low module costs.

14 SOLAR ENERGY↗
DOE OSTI2021

Ultraviolet Fluorescence Bleaching Rates for New Cell Cracks

Ultraviolet Fluorescence (UVF) is an inspection tool that can be used to identify cell cracks in some photovoltaic (PV) modules. Cell cracks can also be identified with electroluminescence (EL) and similar techniques, but it is generally not possible to differentiate new cracks from old ones with EL. UVF has a unique property of taking time for the cracks to show up, which could be used to differentiate new cracks (e.g., from a recent storm) from old ones (e.g., from installation damage). We perform tests on several different modules, some the same make and model but with different bill of materials (BOMs), to characterize the amount of time that it takes for crack signatures to progress in UVF.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Implications of Battery Storage for Solar Net-Metering Reforms

Compensation structures for residential solar PV are evolving toward a model that incentivizes the use of battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner often provide no grid value, due to misalignment with market prices. Incentivizing customers to discharge storage in response to market prices, particularly on infrequent peak load days would greatly enhance storage dispatch value. However, doing so requires consideration of local distribution network impacts. We illustrate a net billing design that yields a storage dispatch value equal to 50-70% of its maximum potential market value, without materially degrading solar self-consumption levels or increasing local grid stress.

Barbose, Galen↗
DOE OSTI2020

Time-of-Use and Demand Charge Battery Controller Using Stochastic Model Predictive Control

Stationary batteries in residential and commercial buildings are often used to smooth customer load profiles and to lower customer electricity bills. Controllers for these battery systems should account for customer energy consumption, rate structures, and high internal battery temperatures, which can lead to reduced performance over the battery lifetime. It is important to consider the uncertainty in forecasting energy consumption and temperature, especially for customers with highly variable and uncertain loads. We propose a novel battery controller using stochastic model predictive control that accounts for these uncertainties and can handle complex rate structures, including demand charges. We show that the controller performs better than standard model predictive control when there is significant uncertainty in the forecast. We also show improvements in the performance with more accurate forecasts and with a more aggressive control strategy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

HTS Accelerator Magnets Conceptual Design for Future Lepton Colliders

There is an interest in designing superconducting magnet systems for future lepton circular colliders. This application requires many low-field iron-dominated dipole and quadrupole magnets. Conventional room-temperature magnets are often used because of their low field, low total current, and low power losses. However, high electricity bills for large accelerators drive magnet design to superconductivity. High-temperature superconducting (HTS) magnets can substantially reduce energy losses in magnet systems. The present study investigated the conceptual design of HTS dipole and quadrupole magnets operating in persistent current mode. Energy is transferred into the magnet from an external detachable power source. A continuously circulating current generates a stable magnetic field. The iron-dominated magnet system concept was investigated using OPERA3D code, and the results confirmed the proposed approach’s validity.

43 PARTICLE ACCELERATORS↗