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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
DOE OSTI2013

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches

Highlights: • The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes. • The model using KED demonstrated the best results (R{sup 2} = 0.92; RMSE = 3.14 ppb). • The model using OK demonstrated a R{sup 2} = 0.85 and RMSE = 4 ppb. • Our results showed that errors appear to be substantially reduced with the KED model. • When measurements at numerous monitoring stations in a region are available, it may be better to use KED. • The BME may be more useful for prediction when data is not available. Ground-level ozone (O{sub 3}) is a powerful oxidizing agent and a harmful pollutant affecting human health, forests and crops. Estimating O{sub 3} exposure is a challenge because it exhibits complex spatiotemporal patterns. The aim in this study was to provide high-resolution maps (100 × 100 m) of O{sub 3} for the metropolitan area of Montreal, Canada. We assessed the kriging with external drift (KED) model to estimate O{sub 3} concentration by synoptic weather classes for 2010. We compared these results with ordinary kriging (OK), and a simple average of 12 monitoring stations. We also compared the estimates obtained for the 2010 summer with those from a Bayesian maximum entropy (BME) model reported in the literature (Adam-Poupart et al., 2014). The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes (daily R{sup 2} estimates ranging from 0.77 to 0.92 and RMSE from 2.79 to 3.37 ppb). For the summer of 2010, the model using KED demonstrated the best results (R{sup 2} = 0.92; RMSE = 3.14 ppb), followed by the OK model (R{sup 2} = 0.85, RMSE = 4 ppb). Our results showed that errors appear to be substantially reduced with the KED model. This may increase our capacity of linking O{sub 3} levels to health problems by means of improved assessments of ambient exposures. However, future work integrating the temporal dependency in the data is needed to not overstate the performance of the KED model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Argonne’s global critical materials agent-based model (GCMat)

Several studies have identified rare earths as critical materials. Although reasonably abundant in the Earth’s crust, rare earths typically occur in low concentrations of mined ores. Processes for recovering rare earth concentrates from these ores are complex and capital intensive. Further, lead times for deposit development, licensing, and construction are long, with reports of 10- 15 years. China is a major player in the rare earths supply chain, both in production capacity and technology innovation. In 2017, China supplied more than 80% of global rare earth oxide demand. Rare earth elements (REEs) have unique magnetic, catalytic, and phosphorescent properties that significantly improve performance of a wide range of technologies. These technologies span aerospace, energy, telecommunications, electronics, transportation, defense, and other diverse applications. Consequently, disruptions in rare earth supply can have a significant societal impact. Estimating that impact requires understanding of the dynamics across the supply chain, from rare earth oxide extraction to end use application. This report documents Argonne’s Global Critical Materials model (GCMat), first described by Riddle et al. 2015. GCMat provides capabilities to explore supply chain dynamics and uncertainty under scenarios of demand growth or shrinkage, technology adoption, supply disruptions, and trade policies and mitigation strategies of new supply sources, product substitution, consumer thrifting, and stockpiling. Supply chain participants from rare earth mining through final demand are modeled as interacting agents who make market decisions independently as time progresses. Since the version documented in Riddle et al. 2015, GCMat has been expanded to cover additional REEs, derived products and supply chains that use these REEs, and includes new agent behaviors and modeling capabilities. Section 2 provides a summary of the GCMat model design, including the structure of the model and key assumptions, section 3 summarizes methods used for model calibration and sensitivity analysis, and section 4 provides examples of model results.

36 MATERIALS SCIENCE↗
NASA NTRS1995

The Atmospheric Data Acquisition And Interpolation Process For Center-TRACON Automation System

The Center-TRACON Automation System (CTAS), an advanced new air traffic automation program, requires knowledge of spatial and temporal atmospheric conditions such as the wind speed and direction, the temperature and the pressure in order to accurately predict aircraft trajectories. Real-time atmospheric data is available in a grid format so that CTAS must interpolate between the grid points to estimate the atmospheric parameter values. The atmospheric data grid is generally not in the same coordinate system as that used by CTAS so that coordinate conversions are required. Both the interpolation and coordinate conversion processes can introduce errors into the atmospheric data and reduce interpolation accuracy. More accurate algorithms may be computationally expensive or may require a prohibitively large amount of data storage capacity so that trade-offs must be made between accuracy and the available computational and data storage resources. The atmospheric data acquisition and processing employed by CTAS will be outlined in this report. The effects of atmospheric data processing on CTAS trajectory prediction will also be analyzed, and several examples of the trajectory prediction process will be given.

Jardin, M. R.↗
NASA NTRS2016

Characterization of Aircraft Structural Damage Using Guided Wave Based Finite Element Analysis for In-Flight Structural Health Management

The development of multidisciplinary Integrated Vehicle Health Management (IVHM) tools will enable accurate detection, diagnosis and prognosis of damage under normal and adverse conditions during flight. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and structural damage conditions. A major concern is the growth of undetected damage/cracks due to fatigue and low velocity foreign object impact that can reach a critical size during flight, resulting in loss of control of the aircraft. To avoid unstable catastrophic propagation of damage during a flight, load levels must be maintained that are below the load-carrying capacity for damaged aircraft structures. Hence, a capability is needed for accurate real-time predictions of safe load carrying capacity for aircraft structures with complex damage configurations. In the present work, a procedure is developed that uses guided wave responses to interrogate damage. As the guided wave interacts with damage, the signal attenuates in some directions and reflects in others. This results in a difference in signal magnitude as well as phase shifts between signal responses for damaged and undamaged structures. Accurate estimation of damage size and location is made by evaluating the cumulative signal responses at various pre-selected sensor locations using a genetic algorithm (GA) based optimization procedure. The damage size and location is obtained by minimizing the difference between the reference responses and the responses obtained by wave propagation finite element analysis of different representative cracks, geometries and sizes.

Seshadri, Banavara R.↗
DOE OSTI2021

Big Adaptive Rotor Phase I (Final Report)

The Big Adaptive Rotor (BAR) project was initiate by DOE in 2018 with the goal of identifying novel technologies that can enable large (>100m) blades for low specific power (SP) turbines. Five distinct tasks were completed to achieve this goal: 1. Assess trends, impacts, and value of low-SP turbines, 2. Wind turbine blade cost reduction roadmap study, 3. Research and Development (R&D) opportunity screening, 4. Detailed design and analysis, and 5. Low-cost carbon fiber. These tasks were completed by the national lab team consisting of Sandia National Laboratories (SNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). The objective of Task 1 was to assess the historical trends of low-SP of onshore deployments, and to assess the impact and value of low-SP turbines. Analysis under this task showed that there is significant value for low-SP turbines, especially in markets where there is a higher saturation of wind energy on the grid. This has to do with the fact that low-SP turbines have increased capacity factors, and can contribute more reliable energy to the grid, even in lower wind conditions. This bodes well as higher renewable scenarios are likely in the coming years. Task 2 was a detailed analysis on the logistical challenges of deploying very large (>100m) onshore blade. This work was completed by experts at DNV-GL. The report looked at various ways to get around the current transportation constraints which are estimated to be around 75m in length. The report concluded that there are viable solutions to this issue including: segmented blades (which the industry is already pursuing), lighter than air (LTA) transportation, on-site manufacturing, and controlled bending of blades on rail. The final option was recommended for further analysis and study by DOE and the national labs because keeping a single piece blade reduces manufacturing and operations and maintenance (O&M) costs. Task 3 focused on identifying novel concepts that are capable of enabling a cost effective 5MW 206m rotor for onshore deployment. The findings from the first two tasks were considered in the analysis, in that the concepts identified must be able to overcome the transportation logistics challenges. Around 20 concepts were identified and evaluated by experts within the industry. Additionally, science and engineering challenges were identified for each concept. Based on these evaluations six concepts were deemed the most impactful and were selected for further analysis in Task 4. The concepts were: highly flexible rail transportable blades, downwind rotors, distributed aerodynamic control (DAC) devices, inflatable blade, bi-wing blade, and 4/5 bladed rotors. Task 4 conducted detailed design, optimization, and analysis on the selected BAR concepts. A modeling gaps analysis was conducted, and modeling improvements were implemented that allowed for the study and design of the novel concepts. The BAR team established a set of baseline designs by which to compare the selected designs through a technoeconomic analysis. It was found that the highly flexible rail transportable blade, the downwind rotor, and the DAC devices have the most promise to deliver the BAR targets. A Phase II for BAR has been proposed to further mature these concepts and address the open science and engineering challenges identified in Task 3. Task 5 conducted research on optimized carbon fiber materials that were used throughout the BAR Phase I project. Overall, the BAR project has identified low-SP turbines as important to continued LCOE reductions for onshore turbines. Furthermore, the project has identified viable solutions to the technical and logistical challenges to realizing these goals. The most promising technologies that were identified in Phase I of the project will be further matured and de-risked in Phase II of the BAR project.

17 WIND ENERGY↗
DOE OSTI2023

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

Deep decarbonization of power system operations requires the maximal utilization of available renewable resources. At distribution-level operations, however, grid operators can face numerous challenges in integrating renewables at scale owing to the inherent intermittence of renewable energy resources. These include phenomena such as voltage fluctuations, which are typically mitigated through control actuators such as on-load tap changers (OLTC) as well as energy storage devices, such as battery energy storage systems (BESS). On the one hand, high intermittence of the available renewable portfolio may require increasingly aggressive control of actuators, thereby accelerating the probability of equipment failure. On the other hand, integrating BESS operations and having a diverse renewable generation portfolio can typically help stagger power/energy flow to mitigate the aforementioned adverse impacts. In this paper, we employ a Bayesian framework for equipment lifetime estimation to understand the impact of including tidal energy resources and BESS in distribution system operations for feeders having substantial distribution photovoltaic generation. Our results indicate that while tidal energy alone may slightly decrease equipment reliability, the adverse impact on reliability is significantly magnified by a generation portfolio consisting of tidal generation and photovoltaic generation. Here, we also study the tidal and photovoltaic hosting capacity problem with and without energy storage systems using equipment reliability as an added constraint. We conclude that energy storage increases the reliability-constrained hosting capacity of the distribution system.

14 SOLAR ENERGY↗
DOE OSTI2014

The Costs and Benefits of Compliance with Renewable Portfolio Standards: Reviewing Experience to Date

More than half of U.S. states have renewable portfolio standards (RPS) in place and have collectively deployed approximately 46,000 MW of new renewable energy capacity through year-end 2012. Most of these policies have five or more years of implementation experience, enabling an assessment of their costs and benefits. Understanding RPS benefits and costs is essential for policymakers evaluating existing RPS policies, assessing the need for modifications, and considering new policies. A key aspect of this study is the comprehensive review of existing RPS cost and benefit estimates, in addition to an examination of the variety of methods used to calculate such estimates. Based on available data and estimates reported by utilities and regulators, this study summarizes RPS costs to date. The study considers how those costs may evolve going forward, given scheduled increases in RPS targets and cost containment mechanisms incorporated into existing policies. The report also summarizes RPS benefits estimates, based on published studies for individual states, and discusses key methodological considerations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A Hydropower Biological Evaluation Toolset (HBET) for Characterizing Hydraulic Conditions and Impacts of Hydro-Structures on Fish

Currently, approximately 16% of the world’s electricity and over 80% of the world’s renewable electricity is generated from hydropower resources, and there is potential for development of a significant amount of new hydropower capacity. However, in practice, realizing all the potential hydropower resource is limited by various factors, including environmental effects and related mitigation requirements. That is why hydropower regulatory requirements frequently call for targets to be met regarding fish injury and mortality rates. Hydropower Biological Evaluation Toolset (HBET), an integrated suite of software tools, is designed to characterize hydraulic conditions of hydropower structures and provide quantitative estimates of fish injury and mortality rates due to various physical stressors including strike, pressure, and shear. HBET enables users to design new studies, analyze data, perform statistical analyses, and evaluate biological responses. In this paper, we discuss the features of the HBET software and describe a case study that illustrates its functionalities. Here, HBET can be used by turbine manufacturers, hydropower operators, and regulators to design and operate hydropower systems that minimize ecological impacts in a cost-effective manner.

13 HYDRO ENERGY↗
NASA NTRS1998

Impact of Radiation Hardness and Operating Temperatures of Silicon Carbide Electronics on Space Power System Mass

The effect of silicon carbide (SiC) electronics operating temperatures on Power Management and Distribution (PMAD), or Power Conditioning (PC), subsystem radiator size and mass requirements was evaluated for three power output levels (100 kW(e) , 1 MW(e), and 10 MW(e)) for near term technology ( i.e. 1500 K turbine inlet temperature) Closed Cycle Gas Turbine (CCGT) power systems with a High Temperature Gas Reactor (HTGR) heat source. The study was conducted for assumed PC radiator temperatures ranging from 370 to 845 K and for three scenarios of electrical energy to heat conversion levels which needed to be rejected to space by means of the PC radiator. In addition, during part of the study the radiation hardness of the PC electronics was varied at a fixed separation distance to estimate its effect on the mass of the instrument rated reactor shadow shield. With both the PC radiator and the conical shadow shield representing major components of the overall power system the influence of the above on total power system mass was also determined. As expected, results show that the greatest actual mass savings achieved by the use of SiC electronics occur with high capacity power systems. Moreover, raising the PC radiator temperature above 600 K yields only small additional system mass savings. The effect of increased radiation hardness on total system mass is to reduce system mass by virtue of lowering the shield mass.

Juhasz, Albert J.↗
NASA NTRS2020

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO2 concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO2 was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.

climate change↗
DOE OSTI2017

Power Plant Retirements: Trends and Possible Drivers

This paper synthesizes available data on historical and planned power plant retirements. Specifically, we present data on historical generation capacity additions and retirements over time, and the types of plants recently retired and planned for retirement. We then present data on the age of plants that have recently retired or that have plans to retire. We also review the characteristics of plants that recently retired or plan to retire vs. those that continue to operate, focusing on plant size, age, heat rate, and SO 2 emissions. Finally, we show the level of recent thermal plant retirements on a regional basis and correlate those data with a subset of possible factors that may be contributing to retirement decisions. This basic data synthesis cannot be used to precisely estimate the relative magnitude of retirement drivers. Nor do we explore every possible driver for retirement decisions. Moreover, future retirement decisions may be influenced by different factors than those that have affected past decisions. Nonetheless, it is clear that recently retired plants are relatively old, and that plants with stated planned retirement dates are—on average—no younger. We observe that retired plants are smaller, older, less efficient, and more polluting than operating plants. Based on simple correlation graphics, the strongest predictors of regional retirement differences appear to include SO 2 emissions rates (for coal), planning reserve margins (for all thermal units), variations in load growth or contraction (for all thermal units), and the age of older thermal plans (for all thermal units). Additional apparent predictors of regional retirements include the ratio of coal to gas prices and delivered natural gas prices. Other factors appear to have played lesser roles, including the penetration variable renewable energy (VRE), recent non-VRE capacity additions, and whether the region hosts an ISO/RTO.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

THE HUNT FOR EXOMOONS WITH KEPLER (HEK). II. ANALYSIS OF SEVEN VIABLE SATELLITE-HOSTING PLANET CANDIDATES

From the list of 2321 transiting planet candidates announced by the Kepler Mission, we select seven targets with favorable properties for the capacity to dynamically maintain an exomoon and present a detectable signal. These seven candidates were identified through our automatic target selection (TSA) algorithm and target selection prioritization (TSP) filtering, whereby we excluded systems exhibiting significant time-correlated noise and focused on those with a single transiting planet candidate of radius less than 6 R{sub Circled-Plus }. We find no compelling evidence for an exomoon around any of the seven Kepler Objects of Interest (KOIs) but constrain the satellite-to-planet mass ratios for each. For four of the seven KOIs, we estimate a 95% upper quantile of M{sub S} /M{sub P} < 0.04, which given the radii of the candidates, likely probes down to sub-Earth masses. We also derive precise transit times and durations for each candidate and find no evidence for dynamical variations in any of the KOIs. With just a few systems analyzed thus far in the ongoing ''Hunt for Exomoons with Kepler'' (HEK) project, projections on eta-moon would be premature, but a high frequency of large moons around Super-Earths/Mini-Neptunes would be premature, but a high frequency of large moons around Super-Earths/Mini-Neptunes would appear to be incommensurable with our results so far.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Covariance Shaping Over Riemannian Manifolds for Massive MIMO Communication

Acquiring accurate instantaneous channel state information (CSI) is a challenging aspect of massive multi-input multi-output (MIMO) communication. Utilizing statistical information, such as channel covariance matrix, to design statistical beamforming vectors is robust when compared to instantaneous CSI. In this paper, we propose a novel MIMO covariance shaping scheme over Riemannian manifolds. It serves as an effective statistical beamforming solution to a number of close proximity user equipment (UE) that are undergoing substantial channel correlation. Proposed algorithm exploits the Hermitian positive definite nature of covariance matrices lying over Riemannian manifold. We introduce Wasserstein distance function as a Riemannian metric to measure distances between channel covariance matrices. Furthermore, K-means clustering technique is utilized to effectively identify the optimal shape of effective optimal covariance matrices. Our findings suggest that maximizing the geodesic distance between covariance matrices ultimately leads to a corresponding increase in the network throughput, as determined by the beamforming vector used to shape the covariance matrices. Simulation results validate that the proposed solution converges faster than Euclidean-based state-of-the-art, while maintaining the same computational complexity. Finally, the sum rate performance asymptotically achieves full capacity for two-UE case and more than 96% of the upper bound exhaustive search benchmark for multi-UE scenario.

42 ENGINEERING↗
DOE OSTI2018

Electrochemical and Magnetic Properties of Electrospun SrTi{sub 1−x}Fe{sub x}O{sub 3} (x = 0, 0.05 and 0.10) Nanofibers for Anodes of Li-Ion Batteries

SrTi{sub 1−x}Fe{sub x}O{sub 3} (x = 0, 0.05 and 0.1) nanofibers (NFs) were fabricated by electrospinning technique. As prepared products were calcined at 800 {sup ∘} C in argon atmosphere for 3 h to obtain a perovskite phase. The crystal structure and morphology of samples were investigated using X-ray diffraction (XRD), transmission electron microscopy (TEM) and scanning electron microscopy (SEM). Electrochemical and magnetic properties of calcined NFs were studied using a potentiostat/galvanostat electrochemical cell system and vibrating sample magnetometer (VSM), respectively. XRD results showed the cubic perovskite structure of calcined samples with the diameter estimated by TEM in the range of 137.4–141.3 nm SEM micrographs revealed the linkage of crystalline grains in NFs of porous and rough surfaces. Electrochemical properties performed on coin-cell-type Li-ion batteries (LIBs) with calcined SrTi{sub 1−x}Fe{sub x}O{sub 3} (x = 0.05 and 0.10) NF-based anodes showed a significant increase of the specific capacity from 305 to 431 mAh/g for the first cycle with the reversible values of 100 and 130 mAh/g, respectively. VSM measurements at room temperature (RT) indicated that calcined SrTiO{sub 3} NFs exhibited paramagnetic (PM) behavior, while calcined SrTi{sub 1−x}Fe{sub x}O{sub 3} NFs displayed ferromagnetic (FM) behavior at RT with the increase of unsaturated magnetization at 10 kOe from 0.46 to 0.82 emu/g for samples with x = 0.05 and 0.10, respectively. The observed FM behavior in calcined SrTi{sub 1−x}Fe{sub x}O{sub 3} (x = 0.05 and 0.1) NFs was suggested to originate from the face center exchange (FCE) mechanism owing to Fe{sup 3+} –Vo–Fe{sup 3+} couplings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Probabilistic Zonal Reserve Requirements for Improved Energy Deliverability with Wind Power

In power systems with high penetration of renewable energy resources, uncertainty and variability of these stochastic resources introduce additional challenges for the operation of power systems. To improve the power system's reliability in the face of uncertainty, reserves are required as additional generation capacity to rebalance the power system following random disturbances. However, reserve deliverability is not guaranteed, because it may encounter potential transmission line congestion. Zonal reserve requirements can address this issue, but operators lack efficient ways to allocate reserves to zones while accounting for wind power forecast uncertainty. Herein we propose a methodology for probabilistic zonal reserve requirements to address wind power forecast uncertainties. This method estimates the probability distribution of line flows based on the system generation margin and injection shift factor. This estimate is then used to construct pre-defined and post-zonal reserve requirements. Case studies demonstrate that the proposed method efficiently schedules energy and reserves to balance energy and manage deliverability with wind power forecast uncertainty.We also discuss operational implications of the proposed method.

17 WIND ENERGY↗
DOE OSTI2023

The Current State of Light-Duty Electric Vehicle Supply Equipment Costs: An Assessment of Contemporary Understanding

This study uses a hybrid meta-analysis and literature-review approach to understand the current state of knowledge regarding the costs of electric vehicle supply equipment (EVSE). We present a novel way to consider, categorize, and label measures of cost and show cost measure estimates from a sample of 13 recent studies. We find that in general, there is too much variation and too few commonly represented EVSE cost measures to reasonably provide aggregate figures for these measures. We propose a convention for presenting EVSE cost measures that includes the application (commercial or residential), the power level (Level 1, Level 2, DCFC [with further distinction based on rated power capacity]), and the type of cost measure (hardware, installation, operation, and total cost). We contend that providing researchers with standard cost measures will help to advance our knowledge of EVSE costs by ensuring that future work will use common metrics. Establishing common metrics will enable conventional meta-analyses that will make assessments of EVSE costs even more accessible. Additionally, common metrics will make tracking costs more reliable as the technology continues to evolve and become more ubiquitous.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗