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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

2022 Component Innovation Awardee: Windurance

Combining battery energy storage with distributed wind energy systems can increase production, ability to meet local electricity demands, interconnection capacity, and potential sales of surplus energy back to the grid, while reducing demand charges and the overall levelized cost of energy (LCOE). Energy storage options for distributed wind energy systems can vary widely in terms of power level and energy storage capacity, and their potential benefits depend on factors including wind resource, turbine design, connection requirements, use patterns, utility rates, and regulations. Windurance received a 2022 Competitiveness Improvement Project (CIP) funding award to add battery energy storage capabilities to the company's bidirectional DC converter. The energy storage component will complete a comprehensive portfolio of power conversion and control electronics that can be seamlessly integrated with distributed wind systems. The company received earlier CIP awards to fund prototype design and construction of wind turbine pitch actuators, inverters, and controllers.

CIP↗
DOE OSTI2026

Asynchronous Grid Connections Providing Fast-Frequency Response: System Integration Study

This paper presents an integration study for the recent power electronic-based fast-frequency response technology, "asynchronous grid connection" which operates as an aggregator for behind-the-meter resources and distributed generators. Both technical feasibility and techno-economic viability studies are presented. The fast-frequency response characteristics, validated against Power Hardware-in-the-Loop experiments, are integrated into an IEEE 9- bus system in DigSilent PowerFactory for system-level dynamic analysis. It demonstrates that droop-based control enhancements to local distributed generators allow their aggregation to provide grid-supporting functionalities and participate in the ancillary service markets. To this end, a long-term simulation embedding the system within the ancillary service market framework of PJM has been performed. The fast-frequency response regulation is subsequently used to calculate the potential revenue and project the results on a 15-year investment horizon. Finally, the techno-economic analysis provides recommendations for enhancements to access the full potential of distributed generators on a technical and regulatory level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗
DOE OSTI2023

Using the Gerchberg-Saxton algorithm to reconstruct nonmodulated pyramid wavefront sensor measurements

Adaptive optics (AO) is a technique to improve the resolution of ground-based telescopes by correcting, in real-time, optical aberrations due to atmospheric turbulence and the telescope itself. With the rise of Giant Segmented Mirror Telescopes (GSMT), AO is needed more than ever to reach the full potential of these future observatories. One of the main performance drivers of an AO system is the wavefront sensing operation, consisting of measuring the shape of the above mentioned optical aberrations. Aims. The non-modulated pyramid wavefront sensor (nPWFS) is a wavefront sensor with high sensitivity, allowing the limits of AO systems to be pushed. The high sensitivity comes at the expense of its dynamic range, which makes it a highly non-linear sensor. We propose here a novel way to invert nPWFS signals by using the principle of reciprocity of light propagation and the Gerchberg-Saxton (GS) algorithm. We test the performance of this reconstructor in two steps: the technique is first implemented in simulations, where some of its basic properties are studied. Then, the GS reconstructor is tested on the Santa Cruz Extreme Adaptive optics Laboratory (SEAL) testbed located at the University of California Santa Cruz. This new way to invert the nPWFS measurements allows us to drastically increase the dynamic range of the reconstruction for the nPWFS, pushing the dynamics close to a modulated PWFS. The reconstructor is an iterative algorithm requiring heavy computational burden, which could be an issue for real-time purposes in its current implementation. However, this new reconstructor could still be helpful in the case of many wavefront control operations. In conclusion, this reconstruction technique has also been successfully tested on the Santa Cruz Extreme AO Laboratory (SEAL) bench where it is now used as the standard way to invert nPWFS signal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗
NASA NTRS1988

Simulation of GaAs cluster formation on GaAs(00-1), AlAs(00-1), Si(001), and As1/Si(001) surfaces

Recently developed semiempirical potential energy functions for the Ga-As-Si and Ga-As-Al systems have been applied here to determine the excess formation energy for GaAs clusters on GaAs(00-1), AlAs(00-1), Si(001), and one atomic layer As-covered Si(001) substrates as a function of cluster size and cluster shape by the Monte Carlo technique. Pyramidal type ledges on the GaAs clusters are found to be the favored ledge for the first three layers while an inverted-pyramidal type ledge is also favored in certain cases for the As1/Si(001) substrate. Cluster formation at ledges is compared with cluster formation on a flat terrace for the Si(001) and the As1/Si(001) substrates.

Choi, D. K.↗
NASA NTRS2010

Two-Dimensional Synthetic-Aperture Radiometer

A two-dimensional synthetic-aperture radiometer, now undergoing development, serves as a test bed for demonstrating the potential of aperture synthesis for remote sensing of the Earth, particularly for measuring spatial distributions of soil moisture and ocean-surface salinity. The goal is to use the technology for remote sensing aboard a spacecraft in orbit, but the basic principles of design and operation are applicable to remote sensing from aboard an aircraft, and the prototype of the system under development is designed for operation aboard an aircraft. In aperture synthesis, one utilizes several small antennas in combination with a signal processing in order to obtain resolution that otherwise would require the use of an antenna with a larger aperture (and, hence, potentially more difficult to deploy in space). The principle upon which this system is based is similar to that of Earth-rotation aperture synthesis employed in radio astronomy. In this technology the coherent products (correlations) of signals from pairs of antennas are obtained at different antenna-pair spacings (baselines). The correlation for each baseline yields a sample point in a Fourier transform of the brightness-temperature map of the scene. An image of the scene itself is then reconstructed by inverting the sampled transform. The predecessor of the present two-dimensional synthetic-aperture radiometer is a one-dimensional one, named the Electrically Scanned Thinned Array Radiometer (ESTAR). Operating in the L band, the ESTAR employs aperture synthesis in the cross-track dimension only, while using a conventional antenna for resolution in the along-track dimension. The two-dimensional instrument also operates in the L band to be precise, at a frequency of 1.413 GHz in the frequency band restricted for passive use (no transmission) only. The L band was chosen because (1) the L band represents the long-wavelength end of the remote- sensing spectrum, where the problem of achieving adequate spatial resolution is most critical and (2) imaging airborne instruments that operate in this wavelength range and have adequate spatial resolution are difficult to build and will be needed in future experiments to validate approaches for remote sensing of soil moisture and ocean salinity. The two-dimensional instrument includes a rectangular array of patch antennas arranged in the form of a cross. The ESTAR uses analog correlation for one dimension, whereas the two-dimensional instrument uses digital correlation. In two dimensions, many more correlation pairs are needed and low-power digital correlators suitable for application in spaceborne remote sensing will help enable this technology. The two-dimensional instrument is dual-polarized and, with modification, capable of operating in a polarimetric mode. A flight test of the instrument took place in June 2003 and it participated in soil moisture experiments during the summers of 2003 and 2004.

LeVine, David M.↗
DOE OSTI2020

Runaway electron beam dynamics at low plasma density in DIII-D: energy distribution, current profile, and internal instability

Parameters of the post-disruption runaway electron (RE) beam in the collisionless background plasma achieved after deuterium injection are investigated in DIII-D. The spatially resolved RE energy distribution function is measured for the first time during the RE plateau stage by inverting hard X-ray bremsstrahlung spectra. It has maximum energy up to 20 MeV and a non-monotonous feature at 5{6 MeV observed only in the core of the beam supporting the possibility of kinetic instabilities. The RE current profile is reconstructed for the first time using the spatially resolved RE energy distribution. It is found to be more peaked than the pre-disruption plasma current, with higher internal inductance, suggesting preferential formation of REs in the core plasma or potentially a radially inward motion of the REs. The accessed relatively low-current (180 kA) RE beam is found stable, likely due to its elevated q profile. From this base stable equilibrium, instability is accessed by ramping the solenoid current. Under a large applied accelerating loop voltage an internal kink mode is observed. The kink mode leads to sawtooth-like relaxation of the RE current profile, but drives no RE loss. Under conditions of a large decelerating voltage, chirping Alfvénic instabilities driven by REs during the RE plateau stage are observed for the first time. The low-frequency (0.1{7 MHz) Alfvénic instabilities, supposedly compressional Alfvén eigenmodes, are found to be correlated with a RE loss signal. Finally, this provides novel plasma conditions to study these instabilities and investigate opportunities to utilize them for RE control. Bifurcated electron cyclotron emission (ECE) spectrum is measured during the collisionless RE plateau, with a break point at ≈100 GHz suggesting resonant absorption of the ECE at low frequencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

OASIS: Offsetting Active Reconstruction Attacks in Federated Learning

Federated Learning (FL) has garnered significant attention for its potential to protect user privacy while enhancing model training efficiency. For that reason, FL has found its use in various domains, from health care to industrial engineering, especially where data cannot be easily exchanged due to sensitive information or privacy laws. However, recent research has demonstrated that FL protocols can be easily compromised by active reconstruction attacks executed by dishonest servers. These attacks involve the malicious modification of global model parameters, allowing the server to obtain a verbatim copy of users' private data by inverting their gradient updates. Tackling this class of attack remains a crucial challenge due to the strong threat model. In this paper, we propose a defense mechanism, namely OASIS, based on image augmentation that effectively counteracts active reconstruction attacks while preserving model performance. We first uncover the core principle of gradient inversion that enables these attacks and theoretically identify the main conditions by which the defense can be robust regardless of the attack strategies. We then construct our defense with image augmentation showing that it can undermine the attack principle. Comprehensive evaluations demonstrate the efficacy of the defense mechanism highlighting its feasibility as a solution.

deep neural networks↗
DOE OSTI2021

Adapting confocal Raman microscopy for in situ studies of redox transformations at electrode-electrolyte interfaces

Confocal Raman microscopy was applied to quantify redox species present within the diffusion layer adjacent to an electrode surface under potentiostatic control. A glass microscope coverslip with a thin indium tin oxide (ITO) coating served as both the working electrode and optical window for a microscope-stage mountable spectroelectrochemical cell. A high numerical aperture objective mounted in an inverted microscope frame just below the stage brought excitation radiation through the coverslip window and to a tight focus a few micrometers above the ITO film surface. Species diffusing into the confocal probe volume defined by the excitation beam focus and the collected light region were detected, identified and quantified based on their Raman scattering frequencies and intensities. Here, in measurements that interrogated the interconversion of ferrocyanide and ferricyanide ions as a function of applied voltage, least-squares regression analysis of spectral datasets predicted the formal potential and relative surface concentrations of the ions in good agreement with the expected Nernstian response. Preliminary studies of methyl viologen reduction at an ITO film/Nafion membrane interface were conducted and show the possibility for estimation of mass transport coefficients of redox species within ionic polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Vigilance and task load - In search of the inverted U

The 'Inverted-U Hypothesis' states that for a given task, there is an optimal level of workload or demand that yields the highest level of performance. A departure in either direction will result in a monotonically lower performance level, hence an inverted-U-shaped relationship between task demand and quality of performance. Most studies to date have failed to demonstrate the left-hand branch of the curve, that is, the regime in which performance presumably rises as load increases. The purpose of this study was to explore whether low-level additional demand on the monitor would result in improved performance. Four groups of subjects performed a visual monitoring task for 48 min, then two of the four groups were given additional tasks, and a third had potentially distracting information on its display. Results indicated that the two groups with additional demand detected more signals than did the control group or the control-plus-distraction group. There were no significant differences in false alarms.

Wiener, E. L.↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

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

Effects of temperature inversion on densification in chemical vapor infiltration

In a classical chemical vapor infiltration (CVI) process, the competing effects of chemical kinetics and reagent gas transport lead to non–uniform depositions such that outer layers of a preform densify faster leaving the core highly porous. Currently, CVI must be performed at a sufficiently low temperature to achieve good densification quality which leads to high processing time and cost. Volumetric heating of the preform, especially through microwaves, can create temperature inversion such that the core is hotter than the outer surface and potentially, overcome the challenges associated with isothermal CVI. Direct numerical simulations (DNS) of densification under various such temperature distributions indicate that microwave heating in CVI processing can lead to better (uniform) densification of porous preforms. Here the role of key parameters describing the temperature distributions on the densification behavior is investigated. Strategic temporal control of the temperature distribution shows that processing times can be reduced by almost half while maintaining a good densification quality similar to that of low–temperature isothermal processing. Inside–out densification due to the inverted temperature profile is a key distinguishing characteristic of microwave assisted CVI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
DOE OSTI2020

Tin–Lead Alloying for Efficient and Stable All-Inorganic Perovskite Solar Cells

Cesium containing all-inorganic perovskites have received considerable interest in photovoltaics research because of their potential for improved stability compared to their organic-inorganic hybrid counterparts. However, the inorganic perovskites studied thus far still suffer from lower power conversion efficiency and long-term instability, due to an unfavorable bandgap and either phase instability or air-sensitivity. Herein, A strategy to mitigate these concerns is investigated by alloying tin and lead on the B site to form tin-lead alloyed low-bandgap (~1.34 eV) inorganic CsSn 0.3 Pb 0.7 I 3 perovskites. Solar cells made using this material in an inverted full-structured architecture with a PEDOT:PSS hole transport materials (HTM) attain power conversion efficiency (PCE) up to 9.41% (stabilized PCE 7.23%). Furthermore, a simple HTM-free device without PEDOT:PSS layer is demonstrated more stable than the full-structured device and exhibits a PCE of 7.60% (stabilized PCE 7.31%) – the highest efficiency to date for an inorganic perovskite with a bandgap below 1.40 eV. This simplified device structure shows good reproducibility and stability. Finally, this work provides a possible route for fabricating low-cost, high stability devices with competitive efficiencies.

14 SOLAR ENERGY↗
DOE OSTI2020

Harmonics and Stability Evaluation of Converter-Interfaced Combined Heat and Power Units

Grid integration of medium-sized combined heat and power (CHP) units is challenging due to strict grid codes and conventional generators lack of control flexibility to meet these grid codes. Adding a two-stage ac-dc-ac power electronics interface between the generator and the utility grid will accelerate the interconnection process of CHP units. For the dc-ac stage, a voltage source converter (VSC) has been widely used as a grid-tied inverter because of its fast control and low total harmonics distortion (THD). In this paper, several topologies of generator-side rectifiers for ac-dc power conversion are explored and analyzed. The harmonics impact of various rectifiers on the CHP generator are evaluated. The overall cost of the electrical system, when using various types of rectifiers, is assessed and the VSC back-to-back converter interface configuration is found to be optimal. The overall system stability is also examined using small-signal impedance analysis to assess potential instability issues at the system level.

CHP, Harmonics, Generator Rectifier Unit, DC Imped↗
DOE OSTI2024

An Updated Life Cycle Assessment of Utility-Scale Solar Photovoltaic Systems Installed in the United States

Given the high deployment targets for solar photovoltaics (PV) needed to meet U.S. decarbonization goals, and the limited carbon budget remaining to limit global temperature rise, accurate accounting of the energy-use and greenhouse-gas emissions over the life-cycle of PV systems is needed. In the United States, most PV systems are large utility-scale systems which use single-axis trackers and central inverters, which are not commonly examined in existing life-cycle assessment (LCA) literature. In this study, we present a cradle-to-grave LCA of a typical silicon U.S. utility PV (UPV) installation which is consistent with the utility system features documented in the annual NREL PV system cost benchmark reports. We analyze and present results for four main metrics: cumulative energy demand (CED), greenhouse gas (GHG) emissions, energy payback time (EPBT), and carbon payback time (CPBT). We consider six primary manufacturing options: three based on an imported PV module supply chain (comparing low-carbon imports, high-carbon imports, and average imports), and three based on a potential domestic PV module supply chain (comparing low-carbon U.S. regions, high-carbon U.S. regions, and average U.S. regions). These manufacturing options were then paired with installation locations to create six main cases: low-carbon options were installed in Phoenix (Arizona), high-carbon options were installed in Seattle (Washington), and average options were installed in Fredonia (Kansas). These locations were selected to represent a range of irradiance and grid mixes in the United States, in order to illustrate the likely range of EPBTs and CPBTs possible across the United States. For all six cases, a sensitivity analysis for end-of-life (EOL) handling was explored to capture current and future management options: landfilling, partial recycling, and high-quality recycling. For the purposes of this report, the benchmark system was defined to use an average imported supply chain with partial recycling, installed in Fredonia (Kansas). CED results show ratios at or below 0.1 MJ oil-eq /MJgenerated which demonstrates efficient use of primary energy resources (below a 1:1 ratio), and represents a slight improvement over previous results in literature. GHG emissions per kWh range from 10-36 g CO 2 e, which are consistent with or lower than previous results published by NREL and IEA-PVPS. We use a graphical approach for calculating EPBT and CPBT in this report, which improves upon methods typically used in literature by accounting for non-linearity and avoiding data quality issues associated with long-term projections. EPBT was determined to vary from 0.5 to 1.2 years, with a benchmark EPBT of 0.6 years; CPBT was shown to vary from 0.8 to 20 years, with benchmark CPBT of 2.1 years, which is lower than other estimates from recent literature (typically >2 years).

14 SOLAR ENERGY↗