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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessing uncertainty in the timing of energy use during cost-optimal distributed energy technology selection and sizing

This paper empirically derives uncertainty ranges in cost-optimal solar PV and storage sizing by comparing results from the REopt Lite optimization platform from metered data and a set of simulated Department of Energy Commercial Reference Building (CRB) profiles at 65 sites. We find load profile shape alone does not explain a site’s optimal configurations (i.e., PV, Storage, PV and Storage, No System). Still, load profile shape does introduce uncertainty to optimal PV and storage capacities. Across all cases where PV is part of an optimal configuration, we find the average ratio of power capacities derived from metered loads to capacities derived from CRB profiles to be 0.97 (and as high as 1463), where 1 would be a perfect match in system size. For storage, the ratio is 1.6 (and as high as 42). We also assess how, in the absence of complete metered data, a CRB profile can be selected that would be expected to yield the most similar solar PV and storage capacities. From those metrics that can be available from billing data (i.e., peak demand, monthly load totals), we find that uncertainty is most reduced by selecting the CRB’s with an annual peak occurring at the most similar time, or those with the lowest average root mean square error (RMSE) among monthly peak loads. This research can help improve the implementation and interpretation of results derived from simulated load profiles and is an important next step in advancing smart grid solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Managing weather- and market price-related financial risks in algal biofuel production

Large-scale algae production has garnered interest due to its potential as a biofuel feedstock. Previous research assessing the profitability of algae products has been mostly based on values averaged over time, but algae production and resulting financial returns exhibit significant variability due to weather and fluctuations in selling prices for algae-based products. In other sectors, producers often reduce weather- and market price-related financial risk with financial instruments such as insurance, but little research has been performed on the design of insurance products to protect algae producers. Furthermore, this study develops a novel index-based insurance instrument that pays-out during unfavorable weather and market conditions, then explores the instrument's effectiveness, combined with a cash reserve, in reducing revenue stream variability for an algae producer. Results indicate that a biophysically based index-insurance product tailored to the specific financial risks in algae production can reduce variability in net revenues and can do so at a lower cost than relying solely on cash reserves, the most common financial risk management tool. Assessing the performance of index-insurance in algae production is particularly timely given the passage of the 2018 Farm Bill, which newly opens opportunities for the USDA to provide crop insurance to algae producers.

09 BIOMASS FUELS↗
DOE OSTI2020

Virtual storage capability of residential buildings for sustainable smart city via model-based predictive control

This paper evaluates the virtual storage capability of a residential air-conditioning (AC) system by utilizing the building mass as a thermal storage to enable sustainable cities through model-based predictive control (MPC). The control-oriented building model was developed with a grey-box model structure based on the experimental data to predict the indoor air temperature. Based on the model, the operation cost-saving potential of the MPC was investigated in a single house with different comfort levels, electricity prices, and prediction horizons. The cost-saving of the MPC was approximately 10.6 % compared to the conventional control. The MPC was expanded to a residential building cluster considering the peak demand charge. In an hourly shedding and load-up scenario, the performances of the MPC and the heuristic prior-based control (PBC) are promising. When shedding was enforced all day, the peak demand saving of the MPC was 36~38 %, whereas that of the PBC was 25.7 % compared to the baseline. In addition, the monthly electricity bill, including the operation and peak demand cost, was investigated with different demand charge rates and weather conditions. The total saving decreased with a low demand charge rate and hot conditions, and the operation cost saving was compromised with more aggressive demand shedding.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Economic and embodied energy analysis of integrated circuit manufacturing processes

Integrated circuits (ICs) are the fundamental microelectronic building blocks of typical information and communication technology (ICT) devices such as laptops and smartphone. With the emergence of faster and cheaper low-power ICs for the growing ICT market, there is a limited information on their manufacturing energy and economic impacts owing to the lack of recurrent upgradation of proprietary IC manufacturing process data. In this work, economic and life cycle energy assessments (LCAs) of IC manufacturing and assembly processes were conducted using the latest bill of materials (BOM) manufacturing data in a state-of-the-art IC manufacturing cost software tool developed by IC Knowledge, LLC. IC manufacturing cost was estimated to be $\$$1.00-$\$$5.00/cm 2 ; the high-end cost represents the most advanced 3D NAND IC technology with the Wafer Level Chip Scale Package cost of $4/cm 2 . Total cumulative energy demand (CED) estimates of IC manufacturing using the OpenLCA software ranged from 9 to 38 MJ/cm 2 or 56–235 BJ/month with the largest share (~ 75%) from on-site energy. The IC manufacturing CED is projected to increase with the progress in IC technology node, which has increased by more than two times for technology node evolution from 110 to 14 nm. Furthermore, the representative detailed BOM data were considered to reduce the CED uncertainties of the estimated standard deviation of 35%- 42%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Coupled management of electric vehicle workplace charging and office building loads

Significant building energy savings are realized through heating, ventilation, and air conditioning (HVAC) setpoint adjustment and daylighting control. Workplace charging (WPC) enables colocation of electric vehicles (EVs) with office building loads. We proposed managing energy use of workplace EV charging and the office building and determined the number of EVs that building energy savings can facilitate charging. We simulated building energy savings in typical medium offices in Chicago IL, Baltimore MD, and Houston TX, spanning three US climate regions. Considering the EV hosting capacity of the saved building energy and travel patterns of roundtrip commuting, we minimized EV charging costs under time-of-use electricity pricing. Managed WPC can reduce charging electricity bills compared to first-come, first-served charging. The ratio of EVs to chargers, the coincident period of commuters’ dwell time and lower electricity prices, and the number of EVs in the office impacted the economic benefits achieved through charging management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Environmental life cycle impacts of small wastewater treatment plants: Design recommendations for impact mitigation

The objective of this study was to quantify potential mitigation of environmental impacts from the operation and construction of wastewater treatment plants (WWTP) from implementing specific design recommendations. The study investigated small WWTPs, many of which are serving slow growing or declining populations. Life Cycle Assessment methodology was used to evaluate and compare the inventory and environmental impacts of nine small WWTP case studies. Detailed inventory data was collected from the facilities’ engineering design plans and utility bills. One recommended practice was to avoid significant overdesign by planning for no lower than a 75% capacity utilization by the facilities’ end-of-life. A theoretical correction to a 75% capacity utilization was estimated to mitigate 0.4% of lifetime electricity usage and 1% of secondary process concrete for every 1% reduction in design average flow rate. Relatedly, a 0.4% mitigation in the Carcinogenic and Global Warming impacts could be achieved for every 1% reduction in design average flow toward a 75% capacity utilization. Other suggested practices were focused on conveyance, namely, to minimize non-process facility area and to use polyvinyl chloride pipe instead of ductile iron pipe where possible. Furthermore, the latter practice was estimated to mitigate between 1.1 and 4.8% of the Carcinogenic impact in the nine case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Optimizing Desalination Operations for Energy Flexibility

Despite the value of energy optimization in desalination processes, modeling dynamic operations for monthly billing periods has remained a computational challenge. This work proposes a framework for energy flexibility optimization, which includes new modeling features for independent operation of parallel skids, start-up delays associated with chemical stabilization, the consideration of industrial energy tariff structures, and inclusion of hourly electrical carbon intensities. This is done using a modular and computationally efficient formulation that guarantees a globally optimal solution with standard optimization solvers. In this study, the approach is demonstrated in two distinct case studies: a seawater desalination plant in Santa Barbara, CA, and an indirect potable reuse facility in San Jose, CA. Trends predicted from the model are validated against operational facility measurements from a demand response shutdown event. Preliminary results show that optimizing energy flexibility can result in 18.51% monthly cost savings over energy efficiency-optimized operation. The value extracted from a facility-wide shutdown during peak electricity price hours is hampered by start-up delays in post-treatment chemical stabilization. In cases in which a facility does not have much excess capacity, using a flow equalization tank or operating over a wide recovery range may be cost-effective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modeling the potential effects of rooftop solar on household energy burden in the United States

Policymakers at the federal and state level have begun to incorporate energy burden into equity goals and program evaluations, aiming to reduce energy burden below a high level of 6% for lower income households in the United States. Pairing an empirical household-level dataset spanning United States geographies together with modeled hourly energy demand curves, we show that rooftop solar reduces energy burden across a majority of adopters during our study period from a median of 3.3% to 2.6%. For low- and moderate-income adopters (at or below 80% and 120% of area median income, respectively), solar reduces median 2021 energy burden from 7.7% to 6.2%, and 4.1% to 3.3%, respectively. Importantly, solar reduces the rate of high or severe energy burden from 67% of all low-income households before adoption to 52% of households following adoption, and correspondingly from 21% to 13% for moderate-income households. Here, we show rooftop solar can support policy goals to reduce energy burden along with strategies such as weatherization and bill assistance.

14 SOLAR ENERGY↗
DOE OSTI2020

Benefits and costs of a utility-ownership business model for residential rooftop solar photovoltaics

The rapid growth of rooftop solar photovoltaic systems can pose a number of financial challenges for electric utility shareholders and their customers. One potential pathway to resolving these perceived challenges involves allowing utilities to own and operate rooftop solar systems. However, the financial benefits and costs of this business model are not well understood. Here we model the financial performance of a large-scale utility-owned residential rooftop solar programme. Furthermore, over a 20 yr period, the programme increases shareholder earnings by 2–5% relative to a no-solar scenario, compared to a 2% earnings loss when an equivalent amount of rooftop solar is instead owned by non-utility parties. Such a programme could therefore be attractive from the perspective of utility investors. The impacts on utility customers, however, are more mixed, with average bills of non-solar customers increasing by 1–3% compared to the no-solar scenario, similar to the 2% increase under traditional, non-utility-ownership structures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The effect of residential solar on energy insecurity among low- to moderate-income households

Each year, millions of Americans experience energy insecurity, or the inability to afford enough energy to meet their basic needs. Here, this study evaluates whether residential rooftop solar can serve as a preventative solution to energy insecurity among low- to moderate-income households. Using a national, matched sample of solar and non-solar households based on detailed and address-specific data, we find that solar leads to large, robust and salient reductions in five indicators of energy insecurity. Moreover, the benefits of solar ‘spill over’ to improve a household’s ability to pay other energy bills. The results suggest that rooftop solar may be an effective tool for policymakers who seek to reduce energy insecurity.

14 SOLAR ENERGY↗
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↗