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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Evaluating the Relationship between the Population Trends, Prices, Heat Waves, and the Demands of Energy Consumption in Cities

The demands of energy consumption have been projected as a key factor that affects an economy at the city, national, and international level. Contributions to total U.S. greenhouse gas emissions in 2012 by various urban sectors include electricity (31%), transportation (28%), industry (20%), agriculture (10%), and commercial and residential (10%). Moreover, the heavy demands of energy consumption in the cities by residents, commercial businesses, industries, and transportation are important for maintaining and sustaining sufficient economic growth. The purpose of this study is to investigate the relationships between population trends, historical energy consumptions, the changes of average electricity price, average annual temperature, and extreme weather events for three selected cities: New York, Chicago, and Los Angeles. These cities are exemplary of, metropolitan areas in the East, Middle, and the Western regions of the U.S. Here, we find that the total energy consumptions of New York, Chicago, and Los Angeles are influenced to various degrees by changes in population, temperature and the average price of electricity and that only one city, Los Angeles, does price significantly affect electricity use. Our finding has implications for policy making, suggesting that each city s climate, size and general economic priorities must be considered in developing climate change mitigation strategies and incentives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Urban-scale building energy consumption database: a case study for Wuhan, China

Building energy consumption accounts for 30% of the overall energy end use worldwide. This number is even much higher in urban areas. With rapid urbanization in China, cities are expanding with new constructions. It is essential to create an updated urban-scale building energy consumption database to represent energy use for different types of buildings in China, which could help urban planners, managers and decision makers to understand temporal and spatial building energy consumption distribution and ensure required electricity and/or gas supply. However, such urban-scale database is rarely found in China. This paper creates baseline EnergyPlus models for residential, small office and large office buildings and validates the baseline models using survey data from literature. Parametric simulations are conducted to consider different design factors, such as building enclosure, lighting power density, equipment power density, HVAC schedule, etc. In total 351 EnergyPlus models are generated to cover different energy use intensity scenarios. Data-driven regression analysis is conducted to predict building energy consumption using building price/rent. The prediction results are expected to provide design decision support for urban planning and power distribution for new constructions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Urban heat island impacts on building energy consumption: A review of approaches and findings

Urban heat island (UHI) could have significant impact on building energy consumption by increasing space cooling demand and decreasing space heating demand. However, the impact of UHI on building energy use was understudied due to challenges associated with defining UHI-induced temperature change and evaluating building energy use. In this paper, we reviewed the existing literature to understand the quantitative impact of UHI on building energy, which is represented by the difference in energy consumption of a representative building in urban and rural areas. The previous studies found that UHI could result in a median increase of 19.0% in cooling energy consumption and a median decrease of 18.7% in heating energy consumption. Moreover, the reported UHI impact showed strong spatial variation within and among cities; the impact on cooling energy use ranges between 10% and 120% while the impact on heating ranges between 3% and 45%. Building on the previous studies, the future research could extend the study of UHI impact in four ways: 1) exploring the spatial pattern of the UHI impact within a city by considering the intra-city variation of UHI intensity and building characteristics; 2) investigating the inter-city variation of the UHI impact and the influence of different characteristics such as geographical location, city size, and development stage; 3) expanding studies in developing countries where rapid urbanization is expected in the next few decades; and 4) projecting UHI impact with future patterns of urbanization and climate change.

urbanization, urban heat island, building energy c↗
DOE OSTI2021

Hybrid electric buses fuel consumption prediction based on real-world driving data

Estimating fuel consumption by hybrid diesel buses is challenging due to its diversified operations and driving cycles. Here, long-term transit bus monitoring data were utilized to empirically compare fuel consumption of diesel and hybrid buses under various driving conditions. Artificial neural network (ANN) based high-fidelity microscopic (1 Hz) and mesoscopic (5–60 min) fuel consumption models were developed for hybrid buses. The microscopic model contained 1 Hz driving, grade, and environment variables. The mesoscopic model aggregated 1 Hz data into 5 to 60-minute traffic pattern factors and predicted average fuel consumption over its duration. The prediction results show mean absolute percentage errors of 1–2% for microscopic models and 5–8% for mesoscopic models. The data were partitioned by different driving speeds, vehicle engine demand, and road grade to investigate their impacts on prediction performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Correlation of FMISO simulations with pimonidazole-stained tumor xenografts: A question of O{sub 2} consumption?

Purpose: To compare a dedicated simulation model for hypoxia PET against tumor microsections stained for different parameters of the tumor microenvironment. The model can readily be adapted to a variety of conditions, such as different human head and neck squamous cell carcinoma (HNSCC) xenograft tumors. Methods: Nine different HNSCC tumor models were transplanted subcutaneously into nude mice. Tumors were excised and immunoflourescently labeled with pimonidazole, Hoechst 33342, and CD31, providing information on hypoxia, perfusion, and vessel distribution, respectively. Hoechst and CD31 images were used to generate maps of perfused blood vessels on which tissue oxygenation and the accumulation of the hypoxia tracer FMISO were mathematically simulated. The model includes a Michaelis–Menten relation to describe the oxygen consumption inside tissue. The maximum oxygen consumption rate M{sub 0} was chosen as the parameter for a tumor-specific optimization as it strongly influences tracer distribution. M{sub 0} was optimized on each tumor slice to reach optimum correlations between FMISO concentration 4 h postinjection and pimonidazole staining intensity. Results: After optimization, high pixel-based correlations up to R{sup 2} = 0.85 were found for individual tissue sections. Experimental pimonidazole images and FMISO simulations showed good visual agreement, confirming the validity of the approach. Median correlations per tumor model varied significantly (p < 0.05), with R{sup 2} ranging from 0.20 to 0.54. The optimum maximum oxygen consumption rate M{sub 0} differed significantly (p < 0.05) between tumor models, ranging from 2.4 to 5.2 mm Hg/s. Conclusions: It is feasible to simulate FMISO distributions that match the pimonidazole retention patterns observed in vivo. Good agreement was obtained for multiple tumor models by optimizing the oxygen consumption rate, M{sub 0}, whose optimum value differed significantly between tumor models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Impact of Time-Varying Passenger Loading on Conventional and Electrified Transit Bus Energy Consumption

Transit bus passenger loading changes greatly over the course of a workday. Therefore, time-varying vehicle mass as a result of passenger load becomes an important factor in instantaneous energy consumption. Battery-powered electric transit buses have restricted range and longer 'fueling' time compared with conventional diesel-powered buses; thus, it is vital to know how much energy they require. Our previous work has shown that instantaneous transit bus mass can be obtained by measuring the pressure in the vehicle's airbag suspension system. This report leverages this novel technique to determine the impact of time-varying mass on energy consumption. Sixty-five days of velocity and mass data were collected from in-use transit buses operating on routes in the Twin Cities, MN metropolitan area. The simulation tool Future Automotive Systems Technology Simulator was modified to allow both velocity and mass as time-dependent inputs. This tool was then used to model an electrified and conventional bus on the same routes and determine the energy use of each bus. Results showed that the kinetic intensity varied from 0.27 to 4.69 mi-1 and passenger loading ranged from 2 to 21 passengers. Simulation results showed that energy consumption for both buses increased with increasing vehicle mass. The simulation also indicated that passenger loading has a greater impact on energy consumption for conventional buses than for electric buses owing to the electric bus's ability to recapture energy. This work shows that measuring and analyzing real-time passenger loading is advantageous for determining the energy used by electric and conventional diesel buses.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Virtual Metering for Monitoring Building Energy Consumption

The United States Department of Energy (DOE) has standard metering requirements of commercial buildings for optimizing energy performance. The guiding principles are to continuously track and optimize energy performance and install building-level meters for electricity, natural gas, and steam. Some buildings at Los Alamos National Laboratory (LANL) have physical submeters monitoring their energy consumption, but these meters have proven to be unreliable. And, in most cases, replacing them has proven to be a slow process. Installing new submeters also requires a temporary lockout of the circuit on which they are being installed. Many buildings at LANL contain laboratories with ongoing experiments or data centers, which makes an equipment power outage nearly impossible to plan. This inability to plan power outages results in long-term submeter failures. Although most submeters are eventually replaced, failures lead to missing consumption data for some unpredictable, extended time. A building automation system (BAS) is a system that provides control and monitoring on a building to maintain the operational performance of the building and occupancy comfort. Many buildings at LANL currently have a BAS, and all new renovations and installs will include installing a BAS if one does not already exist. The intended purpose for a BAS is primarily to monitor the health and efficiency of a building; however, it is also possible to calculate equipment power and energy consumption using BAS information. This project aims to use virtual meters to monitor building energy consumption as a cost-effective and minimally labor-intensive alternative to installing physical submeters. The fault detection and diagnostics tool, SkySpark, provides a centralized database for all the data from the various BAS that are active at LANL. This data includes the information that is needed to create virtual meters for heating, ventilating, and air conditioning (HVAC) systems in most buildings, including heating and cooling loads. 9 This report begins with a detailed summary of the project, including the reasoning, procedure, and results. The specific processes of creating the various virtual meters are then identified. Then the limitations are discussed. And, lastly, the results and future potential are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Impact of anatomical fractionation of corn stover on hammer mill throughput and energy consumption

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on loss of very wet stover that causes failures in the first stage grinder and that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbohydrate content (minimum total carbohydrate specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed stover not meeting the total carbohydrate specification to the conversion reactor. Laboratory data on the impacts of moisture content and tissue fraction on throughput and energy consumption in a stage 2 hammer mill were received from FCIC Subtask 5.1. Additional air classifier throughput, energy consumption and separation efficiency data were obtained from FCIC Subtask 5.1 for the new air classifier, which has three exit streams (lights, middle and heavies). These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents and particle sizes had not been analyzed in the laboratory at the time of the model runs, we assumed that the ash distributed proportionally with total mass into the lights and heavies in an air classifier having two exit streams (lights and heavies) and that the lights fraction from the air classifier was not removed. Key takeaways from this Case Study are that due to lower energy consumption, it is more cost effective to hammer mill fractionated corn stover tissues than whole stover. Reduction of grinding energy was significant and may possibly be connected to particle-particle interactions in the grinder that lead to increased residence time of leaves and husks, resulting in decreased throughput and higher generation of fines when milling whole stover. While we did not see significant impacts to throughput, this was due to moisture failures of the first stage grinder in each system dominating failures and downtime. The operating cost savings of reduced grinding energy savings in the second stage hammer mills alone was high enough to offset the added capital cost of the air classifier and extra grinding line.

09 BIOMASS FUELS↗
DOE OSTI2022

Point Cloud Based Mapping of Understory Shrub Fuel Distribution, Estimation of Fuel Consumption and Relationship to Pyrolysis Gas Emissions on Experimental Prescribed Burns

Forest fires spread via production and combustion of pyrolysis gases in the understory. The goal of the present paper is to understand the spatial location, distribution, and fraction (relative to the overstory) of understory plants, in this case, sparkleberry shrub, namely its degree of understory consumption upon burn, and to search for correlations between the degree of shrub consumption to the composition of emitted pyrolysis gases. Data were collected in situ at seven small experimental prescribed burns at Ft. Jackson, an army base in South Carolina, USA. Using airborne laser scanning (ALS) to map overstory tree crowns and terrestrial laser scanning (TLS) to characterize understory shrub fuel density, both pre- and postburn estimates of sparkleberry coverage were obtained. Sparkleberry clump polygons were manually digitized from a UAV-derived orthoimage of the understory and intersected with the TLS point cloud-derived rasters of pre- and postburn shrub fuel bulk density; these were compared in relation to overstory crown cover as well as to ground truth. Shrub fuel consumption was estimated from the digitized images; sparkleberry clump distributions were generally found to not correlate well to the overstory tree crowns, suggesting it is shade-tolerant. Moreover, no relationship was found between the magnitude of the fuel consumption and the chemical composition of pyrolysis gases, even though mixing ratios of 25 individual gases were measured.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Reducing Fuel Consumption on a Heavy-Duty Nonroad Vehicle: Conventional Powertrain Modifications

This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption. Two conventional powertrain modifications are explored that provide potential pathways that significantly alter the base powertrain and include 1.) a torque converter disconnect clutch and 2.) a low voltage stop-start system that have the potential to reduce fuel consumption on the end user representative drive cycle by 10.3% and 9.8%, respectively. Details of how the powertrain modifications would be executed, physical hardware, and application to other heavy-duty nonroad vehicle applications are included in the discussion.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

With the current technological advancements revolutionizing the concept of Urban Air Mobility (UAM) and package delivery, there is also, a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Conducting safe flight operations is critical for UAM vehicles which are electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of different eVTOL

Data-driven↗
DOE OSTI2015

A microbial functional group-based module for simulating methane production and consumption: Application to an incubated permafrost soil

In this study, accurately estimating methane (CH 4 ) flux is critically important for investigating and predicting the biogeochemistry-climate feedback. Better simulating CH 4 flux requires explicit representations of microbial processes on CH 4 dynamics because all processes for CH 4 production and consumption are actually carried out by microbes. A microbial functional group based module was developed and tested against an incubation experiment. The module considers four key mechanisms for CH 4 production and consumption: methanogenesis from acetate or single-carbon compounds and CH 4 oxidation using molecular oxygen or other inorganic electron acceptors. These four processes were carried out by four microbial functional groups: acetoclastic methanogens, hydrogenotrophic methanogens, aerobic methanotrophs, and anaerobic methanotrophs. This module was then linked with the decomposition subroutine of the Community Land Model , and was further used to simulate dynamics of carbon dioxide (CO 2 ) and CH 4 concentrations from an incubation experiment with permafrost soils. The results show that the model could capture the dynamics of CO 2 and CH 4 concentrations in microcosms with top soils, mineral layer soils and permafrost soils under natural and saturated moisture conditions and a temperature gradient of -2°C, 3°C, and 5°C. Sensitivity analysis confirmed the importance of acetic acid's direct contribution as substrate and indirect effects through pH feedback on CO 2 and CH 4 production and consumption. This study suggests that representing the microbial mechanisms is critical for modeling CH 4 production and consumption; it is urgent to incorporate microbial mechanisms into Earth system models for better predicting the behavior of the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Consumption of terrestrial organic matter in the rocky intertidal zone along the central Oregon coast

Abstract Terrestrial organic matter ( TOM ) constitutes an important source of energy in many aquatic environments. This is the first study to compare the consumption of terrestrial leaves ( Alnus rubra ) to high‐quality ( Nereocystis luetkeana ) and low‐quality ( Fucus gardneri ) sources of drift kelp and low‐quality seagrass ( Phyllospadix spp.) in pools of the rocky intertidal zone on Cape Arago, Oregon, USA . On average, 1.02 kg ash‐free dry mass ( AFDM ) per day of TOM was transported by small forested streams during fall leaf abscission to the rocky intertidal zone in small pocket bays. Leaves of A. rubra (red alder) varied in wrack from negligible (12 g AFDM /m 2 ) on some beaches to the primary source of detritus on others (256 g AFDM /m 2 ). Long‐term feeding experiments (months) showed that consumption rates of A. rubra in the spring (19.7% of the initial pack biomass) and in the fall (52% of the initial pack biomass) were intermediate between those of N. luetkeana (fully consumed) and Phyllospadix spp. (never >10% consumed of the initial pack biomass). Long‐term experiments also showed that conditioned fall‐shed leaves of A. rubra were consumed at a faster rate (52.3% of initial pack biomass) than spring‐shed leaves of A. rubra (16.8% of initial pack biomass). Short‐term feeding experiments again showed that consumption of A. rubra in the spring (18.6% of initial pack biomass over 3 d) and fall (16.7% over 7 d) was intermediate between N. luetkeana (57.3% consumed over 3 d in the spring and 60.7% over 7 d in the fall) and Phyllospadix spp. (<1% consumed in the spring). Except for Phyllospadix spp., consumption rates followed polyphenolic concentrations in that, N. luetkeana (418 mg/mL) > A. rubra (3415 mg/mL) > F. gardneri (8098 mg/mL). Phyllospadix spp. was rarely consumed despite a fairly low concentration of phenolics (800 mg/mL). In the temperate zone, leaves of A . rubra may constitute an important source of energy during the fall and winter when more nutritious marine resources dieback, such as single‐celled algae and kelp (e.g., N. luetkeana ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Developing a Control Strategy for Minimum Airflow Setting Considering CO2 Level and Energy Consumption in a Variable Air Volume System

In an office building equipped with a Variable Air Volume (VAV) system, this paper introduces a novel method for controlling the minimum supply airflow fraction in each zone’s VAV box, having a capability to consider indoor CO2 level and energy consumption. The EnergyPlus simulation using the medium office prototype model was employed, which evaluated the performance of the energy and CO2 concentration for five VAV box airflow control strategies. The paper focuses on CO2 concentration-based airflow control method and compares it with other four methods including conventional single-max, reduced minimum single-max, demand-controlled ventilation(DCV), and dualmax control methods according to guidelines and common practices. The newly proposed control strategy directly correlates the minimum airflow fraction to CO2 concentration. A general trend emerged when comparing CO2 concentrations—lower minimum airflow fractions were associated with higher concentrations. The proposed control method effectively maintained low CO2 concentrations and enabled a lower airflow fraction contributing to energy consumption reduction. It was confirmed that heating energy consumption in climate zone 4A, 5B, and 6A showed a maximum saving of approximately 30% compared to the conventional single-max and dual max control strategies. It was found that cooling energy consumption in climate zone 4A and 6A can achieve a maximum saving of approximately 10% compared to the conventional control strategies. The proposed CO2 concentration-based control logic is promising as it not only improves the indoor air quality lowering the CO2 concentration in the occupied spaces, but also contributes to HVAC energy savings.

Lee, Jong Man↗
DOE OSTI2019

Comments on “Comparison of energy consumption in desalination by capacitive deionization and reverse osmosis”

Capacitive deionization (CDI) is an emerging brackish water desalination technology in which ions are removed from water by electrostatically adsorbing them onto porous electrodes. Recently, Qin et al. presented an estimate of energy consumption for CDI schemes, and compared the energy consumption of CDI to the energy consumption of a particular reverse osmosis operation scheme which they propose. Qin et al. estimate very high values of energy consumption in CDI for brackish water desalination (e.g. ~1 to 2 g/L salt solution), and these values and trends do not agree with published experiments for CDI or with experimentally validated models for CDI. The current comment identifies important scaling errors and incorrect values in their model resistance parameters, and then discusses unphysical trends predicted by their model. We do not attempt provide a comprehensive review of their model, operation, estimates, and figures, but rather concentrate on several key issues. We present our comments in two sections dealing with resistances and energy metrics, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

China's transportation energy consumption and CO2 emissions from a global perspective

ABSTRACT Rapidly growing energy demand from China's transportation sector in the last two decades have raised concerns over national energy security, local air pollution, and carbon dioxide (CO2) emissions, and there is broad consensus that China's transportation sector will continue to grow in the coming decades. This paper explores the future development of China's transportation sector in terms of service demands, final energy consumption, and CO2 emissions, and their interactions with global climate policy. This study develops a detailed China transportation energy model that is nested in an integrated assessment model—Global Change Assessment Model (GCAM)—to evaluate the long-term energy consumption and CO2 emissions of China's transportation sector from a global perspective. The analysis suggests that, without major policy intervention, future transportation energy consumption and CO2 emissions will continue to rapidly increase and the transportation sector will remain heavily reliant on fossil fuels. Although carbon price policies may significantly reduce the sector's energy consumption and CO2 emissions, the associated changes in service demands and modal split will be modest, particularly in the passenger transport sector. The analysis also suggests that it is more difficult to decarbonize the transportation sector than other sectors of the economy, primarily owing to its heavy reliance on petroleum products.

Yin, Xiang↗
DOE OSTI2016

Mapping water consumption for energy production around the Pacific Rim

World energy demand is projected to increase by more than a third by 2035 and with it the use of water to extract and process fuels and generate electricity. Management of this energy-water nexus requires a clear understanding of the inter-related demands of these resources as well as their regional distribution. Toward this need the fresh water consumed for energy production was mapped for almost 12 000 watersheds distributed across the 21-economies comprising the Asia-Pacific Economic Cooperation. Fresh water consumption was estimated for ten different sectors including thermoelectric and hydroelectric power; energy extraction including coal, oil, natural gas, uranium and unconventional oil/gas; energy processing including oil and biofuels; and biofuel feedstock irrigation. These measures of water consumption were put in context by drawing comparison with published measures of water risk. In total 791 watersheds (32%) of the 2511 watersheds where energy related water consumption occurred were also characterized by high to extreme water risk, these watersheds were designated as being at energy-water risk. Furthermore, for six economies watersheds at energy-water risk represented half or more of all basins where energy related water consumption occurred, while four additional economies exceeded 30%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Energy consumption and charging load profiles from long-haul truck electrification in the United States

Abstract The urgent need to decarbonize the transportation sector combined with falling battery prices has spurred industry and policy interest in long-haul truck electrification. The charging behavior and resulting loads from electrified long-haul freight trucks are crucial for the smooth operation of the electric grid and have far-reaching environmental impacts (e.g., greenhouse gas and other air pollutant emissions). However, the aggregate energy impact of a fleetwide shift to electrified long-haul freight trucking has not been explored. This study combines electric truck design scenarios, bottom-up truck weight modeling, vehicle energy modeling, large-scale truck traffic data, and simulation of likely operation and charging behaviors to estimate end-use energy consumption and location-specific hourly charging loads for a national fleet of long-haul electric trucks. Relative to a fleet of future diesel trucks, electrification would reduce direct end-use energy consumption by 0.9 × 10 18 J (0.9 quadrillion BTU), but electrification might increase life cycle energy consumption depending on the electricity source. The electricity required to charge long-haul electric trucks is equivalent to five percent of annual electricity consumption in the United States (US). The simulated truck charging loads peak during the day across the US grid regions, but the charging peaks’ exact timing is sensitive to when trucks are dispatched for operation. The load shapes suggest that electric trucks’ charging loads can coincide with peaks in solar power generation, and planning could enable on- or off-site integration between truck charging stations and renewable electricity generation.

Tong, Fan (ORCID:0000000346613956)↗