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DOE OSTI2025

Neutrinoless double beta decay sensitivity of the XLZD rare event observatory

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60–80 t capable of probing the remaining weakly interacting massive particle-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in 136 Xe using a natural-abundance xenon target. XLZD can reach a 3σ discovery potential half-life of 5.7 × 10 27 years (and a 90% CL exclusion of 1.3 × 10 28 years) with 10 years of data taking, corresponding to a Majorana mass range of 7.3–31.3 meV (4.8–20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community.

2-phase xenon TPCs↗

DOE OSTI2023

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

Szołdra, Tomasz (ORCID:0000000228970506)↗

DOE OSTI2023

Valuation of Distributed Wind Turbines Providing Multiple Market Services

The role of wind turbines has traditionally been limited to providing energy capacity to the grid, but the availability of smart inverters and recent regulatory changes provide the technical and policy capability for wind turbines to also provide ancillary services. However, in contrast to the technical and policy aspects, the valuation of distributed wind turbines providing such services has not been thoroughly studied. This paper presents an optimal market-participation method for distributed wind turbines and valuates different strategies in California Independent System Operator’s balancing area. The services include energy capacity, regulation up and down, and reserves. An optimization problem is formulated to determine optimal power output for each service and demonstrated using historical data for one complete year. The revenues from multiple services are quantified, and a sensitivity analysis is performed to relate market prices with revenues. It is found that the optimal strategy generates 6% more revenue compared to the revenue from participating in the energy market only. Also, the reduced energy prices in future scenarios increase the relative importance of market participation in ancillary services.

Bhatti, Bilal Ahmad↗

DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗

DOE OSTI2021

Bayesian analysis of a future β decay experiment's sensitivity to neutrino mass scale and ordering

Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. In this work, we present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the β-decay spectrum, we assess a high-precision β-decay experiment's sensitivity to the neutrino mass scale and ordering for one assumed design scenario. We find that such an experiment could measure the electron-weighted neutrino mass within ~40 meV after 1 year (90% credibility). Neutrino masses > 500 meV could be measured within ≈5 meV. Using only β decay and external reactor neutrino data, we find that next-generation β-decay experiments could potentially constrain the mass ordering using a two-neutrino spectral model analysis. By calibrating mass ordering results, we identify reporting criteria that can be tuned to suppress false ordering claims. In some cases, a two-neutrino analysis can reveal that the mass ordering is inverted, an unobtainable result for the traditional one-neutrino analysis approach.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Oscillation Risks of Grid-Following and Grid-Forming Inverter-Based Resources in Series-Compensated Networks

Here, this paper investigates the dynamic behavior of a grid-connected inverter-based resource (IBR) when connected radially to a series compensated line. Potential interactions between the series compensation and the IBR have been identified for both types: grid-following (GFL) or grid-forming (GFM). The study begins with electromagnetic transient (EMT) simulations to demonstrate stability issues. Subsequently, nonlinear analytical models are formulated in the dq frame, validated against the EMT simulation, and leveraged to assess eigenvalues and participation factors. Influencing factors of the dominant oscillation modes have been identified. The analysis results show that series compensation may make a mode associated with the synchronization unit unstable. Furthermore, customized feedback systems are built for the synchronizing loop. Series compensation can increase the sensitivity of the voltage phase angle towards the synchronizing angle, and introduce phase lag in the real power response towards the synchronizing angle. These factors may cause interactions with the phase-locked loop in GFL-IBR systems and with power-based synchronization in GFM-IBR systems, potentially leading to instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Analysis of a Disturbance Event with Inverter-Based Resources Using EMT Simulations

Increasing penetration of inverter-based resources (IBRs) necessitates newer methods of planning and analysis of disturbances. The existing phasor-domain transient stability (TS) analysis may not capture the dynamics of IBRs during fault events. Here, in this paper, electromagnetic transient (EMT) simulations using high-fidelity detailed model of power grid and one of the affected photovoltaic (PV) plants during the Angeles Forest disturbance in 2018 are performed. In these simulations, the processes to develop EMT models of power grid from traditional phasor-domain TS data and PV plant from collected data are described. Thereafter, using these simulations, the response of the PV plant during the fault event in 2018 is replicated and a sensitivity analysis is performed. The sensitivity analysis consists of making changes to the components within the PV plant and in the power grid to evaluate the impact they have on the response observed by the PV plant during the fault event. This analysis provides an understanding of the components that impact the operation of a PV plant during fault events and provide guidance to system planners on the studies that need to be performed to maintain a reliable power grid as new IBR plants are integrated.

42 ENGINEERING↗

DOE OSTI2020

Detectability of collective neutrino oscillation signatures in the supernova explosion of a 8.8 M ⊙ star

In order to investigate the impact of collective neutrino oscillations (CNOs) on the neutrino signal from a nearby supernova, we perform three-flavor neutrino oscillation simulations employing the multiangle effect. The background hydrodynamic model is based on the neutrino hydrodynamic simulation of a 8.8 M ⊙ progenitor star. In this work, we find that CNO commences after some 100 ms post bounce. Before this, CNO is suppressed by matter-induced decoherence. In the inverted mass hierarchy, the spectrum of $\bar{ν}_e$ becomes softer after the onset of CNO. To evaluate the detectability of this modification, we define a hardness ratio between the number of high energy neutrino events and low energy neutrino events adopting a fixed critical energy. We show that Hyper-Kamiokande (HK) can distinguish the effect of CNO for supernova distances out to ~ 10 kpc. On the other hand, for the normal mass hierarchy, the spectrum of ν e becomes softer after the onset of CNO, and we show that DUNE can distinguish this feature for supernova distances out to ~ 10 kpc . More work is necessary to optimize the best value of critical energy for maximum sensitivity. We also show that if the spectrum of $\bar{ν}_e$ in HK becomes softer due to CNO, the spectrum of $ν_e$ in DUNE becomes harder, and vice versa. These synergistic observations in $\bar{ν}_e$ and $ν_e$, by HK and DUNE, respectively, will be an intriguing opportunity to test the occurrence of CNO.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Strong Upper-Plate Heterogeneity at the Hikurangi Subduction Margin (North Island, New Zealand) Imaged by Adjoint Tomography

We use earthquake-based adjoint tomography to invert for three-dimensional structure of the North Island, New Zealand, and the adjacent Hikurangi subduction zone. The study area, having a shallow depth to the plate interface below the North Island, offers a rare opportunity for imaging material properties at an active subduction zone using land-based measurements. Starting from an initial model derived using ray tomography, we perform iterative model updates using spectral element and adjoint simulations to fit waveforms with periods ranging from 4–30 s. We perform 28 model updates using an L-BFGS optimization algorithm, improving data fit and introducing P- and S-wave velocity changes of up to ±30%. Resolution analysis using point spread functions show that our measurements are most sensitive to heterogeneities in the upper 30 km. The most striking velocity changes coincide with areas related to the active Hikurangi subduction zone. Lateral velocity structures in the upper 5 km correlate well with New Zealand geology. Here, the inversion reveals increased along-strike heterogeneity on the margin. In Cook Strait we observe a low-velocity zone interpreted as deep sedimentary basins. In the central North Island, low-velocity anomalies are linked to surface geology, and we relate velocity structures at depth to crustal magmatic activity below the Taupō Volcanic Zone.

58 GEOSCIENCES↗

DOE OSTI2020

Many-Body Signatures of Collective Decay in Atomic Chains

Fully inverted atoms placed at exactly the same location synchronize as they deexcite, and light is emitted in a burst (known as “Dicke’s superradiance”). We investigate the role of finite interatomic separation on correlated decay in mesoscopic chains and provide an understanding in terms of collective jump operators. We show that the superradiant burst survives at small distances, despite Hamiltonian dipole-dipole interactions. However, for larger separations, competition between different jump operators leads to dephasing, suppressing superradiance. Collective effects are still significant for arrays with lattice constants of the order of a wavelength, and lead to a photon emission rate that decays nonexponentially in time. We calculate the two-photon correlation function and demonstrate that emission is correlated and directional, as well as sensitive to small changes in the interatomic distance. Furthermore, these features can be measured in current experimental setups, and are robust to realistic imperfections.

74 ATOMIC AND MOLECULAR PHYSICS↗

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↗

DOE OSTI2025

Entanglement asymmetry and symmetry defects in boundary conformal field theory

A state in a quantum system with a given global symmetry, G, can be sensitive to the presence of boundaries, which may either preserve or break this symmetry. In this work, we investigate how conformal invariant boundary conditions influence the G-symmetry breaking through the lens of the entanglement asymmetry, a quantifier of the “distance” between a symmetry-broken state and its symmetrized counterpart. By leveraging 2D boundary conformal field theory (BCFT), we investigate the symmetry breaking for both finite and compact Lie groups. Beyond the leading order term, we also compute the subleading corrections in the subsystem size, highlighting their dependence on the symmetry group G and the BCFT operator content. We further explore the entanglement asymmetry following a global quantum quench, where a symmetry-broken state evolves under a symmetry-restoring Hamiltonian. In this dynamical setting, we compute the entanglement asymmetry by extending the method of images to a BCFT with non-local objects such as invertible symmetry defects.

Field Theories in Lower Dimensions↗

DOE OSTI2025

Collective Modes in Multilayer Graphene/𝛼−RuCl 3 Heterostructures

Collective modes in multilayer graphene, such as plasmons and phonons, exhibit sensitivity to displacement fields and interlayer coupling, distinguishing them from their counterparts in single-layer graphene. Here, we engineer collective modes in charge-transfer heterostructures composed of multilayer graphene and 𝛼−RuCl 3 . In heterostructures with a single 𝛼−RuCl 3 interface, the charge transfer generates displacement fields up to 7 V/nm at the interface between 𝛼−RuCl 3 and the adjacent graphene layer—the highest value achieved through charge-transfer methods. As a result of the broken inversion symmetry, we discover enhanced nonlinear optical response and modified phonon selection rules. Conversely, we find that multilayer graphene sandwiched between two 𝛼−RuCl 3 flakes causes displacement fields to cancel. There, we achieve carrier densities as high as 8 ×10 13 cm −2 in multilayer graphene and restore the phonon selection rules to their unperturbed state. Meanwhile, we demonstrate that plasmonic properties derive from the depletion of multiple valence bands. As a result of the quasilinear band dispersion, these “Dirac multiband plasmons” are relatively unaffected by displacement fields. On the other hand, the inverted heterostructure sequence—two multilayer graphene sheets encapsulating 𝛼−RuCl 3 —activates significant alteration of the plasmons via interlayer plasmon-plasmon coupling. Hence, multilayer graphene and 𝛼−RuCl 3 heterostructures offer a gate-free platform for engineering collective modes derived from inversion symmetry and interlayer coupling.

Moore, Samuel L. [Columbia University, New York, N↗

DOE OSTI2022

Hybrid Hydraulic-Electric Architecture (HHEA) for Mobile Machines (Final Report)

Traditionally, off-road mobile machines such as excavators and wheel loaders are primarily powered by hydraulics, and throttling valves are used to control their work circuits. In recent years, two general trends are towards more energy efficient systems and electrification. With electrification, both efficiency and control performance can be improved by the elimination of throttling losses and the use of high-bandwidth inverter control. Electrification is generally accomplished with Electro-hydraulic actuators (EHA) but they are limited to lower powered systems due to the high cost of electric machines capable of high power or high torque. This project proposes a new system architecture for off-road vehicles - Hybrid Hydraulic Electric Architecture (HHEA) to improve efficiency and control performance without requiring large electric machines. The widely applicable architecture combines hydraulic power and electric power in such a way that the majority of power is provided hydraulically while electric drives are used to modulate this power. In particular, HHEA utilizes multiple common pressure rails to transmit the majority of power and small electric machines to modulate the power. The energy-saving potential of the the HHEA has been validated for the work circuits of a variety of mobile machines, from small 5-ton excavators to medium sized 20-ton excavators and wheel loaders, and representative duty cycles to reduce energy input by 50-80% compared to the commercial state-of-art load-sensing systems. In addition, the corner power requirements of the electrical machines can be downsized by 85% compared to the EHA approach. Various tradeoff studies have also been conducted, including sensitivities to individual components performances, controllers, accumulator sizes, and variations of the system architecture etc. A control strategy has been developed to maintain or exceed the motion control precision compared to current systems. The motion control strategy consists of a nominal controller, based on a passivity-based backstepping design, and a transition controller, based on least-norn feedforward design. The nominal controller is used in between common pressure rail switches whereas the transition controller compensates for any disturbance that common pressure rail switchings inflict on the system. The control strategy has been experimentally validated on both a medium pressure (200bar) hardware-in-the-loop (HIL) testbed and a high pressure (300+bar) HIL testbed. An efficient and power-dense integrated electric-hydraulic machine consisting of an axial flux electric machine and a radial hydrostatic piston hydraulic machine has been designed, constructed and tested. The machine has an active material power density of 6.1kW/kg, a rated speed of 12500 RPM, and a design efficiency of 85%. This is among the highest power density electric machines using conventional materials. While the integrated machine was designed for modulating the hydraulic power within the HHEA, it can also be used in other applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Resonant inelastic x-ray scattering investigation of Hund's and spin-orbit coupling in 5 d 2 double perovskites

𝐵 site ordered 5⁢𝑑 2 double perovskites (𝐴 2 ⁢𝐵⁢𝐵′⁢O 6 , 𝐵′ = 5⁢𝑑 2 ) display a remarkable range of physical properties upon variation of the chosen 𝐵 and 𝐵′ site ions. This sensitivity to chemical substitution reflects the delicate balance and profound impact of strong electronic correlation and spin-orbit coupling in such systems. Here, we present rhenium 𝐿 2 and 𝐿 3 resonant inelastic x-ray scattering (RIXS) measurements of two such physically dissimilar materials, Mott-insultating Ba 2⁢ Y⁢Re⁢O 6 and semiconducting Sr 2⁢ Cr⁢Re⁢O 6 . Despite these differences, our RIXS results reveal similar energy scales of Hund's (𝐽 𝐻 ) and spin-orbit coupling (𝜁) in the two materials, with both systems firmly in the intermediate Hund's coupling regime where 𝐽 𝐻 /𝜁∼1. However, there are clear differences in their RIXS spectra. The conductive character of Sr 2⁢ Cr⁢Re⁢O 6 broadens and obfuscates the atomic transitions within an electron-hole continuum, while the insulating character of Ba 2 ⁢Y⁢Re⁢O 6 results in sharp atomic excitations. This contrast in their RIXS spectra despite their similar energy scales reflects a difference in the itinerancy-promoting hopping integral and illustrates the impact of the local crystal environment in double perovskites. Finally, 𝐿 2 and 𝐿 3 edge analyses of the atomic excitations in Ba 2 ⁢Y⁢Re⁢O 6 reveal that the ordering of the low lying excited states is inverted compared to previous reports, such that the appropriate energy scales of Hund's and spin-orbit coupling are significantly modified. We present exact diagonalization calculations of the RIXS spectra at both edges which show good agreement with our results for new energy scales of 𝜁 = 0.290⁢(5)⁢eV and 𝐽 𝐻 = 0.38⁢(2)⁢eV [𝐽 𝐻 /𝜁 = 1.30⁢(5)].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Measurement of 2D density profiles using a second-harmonic, dispersion interferometer

A second-harmonic, dispersion interferometer is used to image large-area (≃5 cm 2 ) plasma-jet and gas-jet density profiles. Achromatic telescopes magnify the diameters of the primary-laser beam (1064 nm) and its second-harmonic (532 nm) before probing the sample and de-magnify the beam diameters after the sample, where the primary beam transfers its phase change to a second, second-harmonic beam, allowing the sample’s dispersive-phase change to be measured between two, orthogonally polarized second harmonic beams. The telescopes produce an azimuthally symmetric, dispersive-phase shift in the sample + background phase-change image and in the background phase-change image, which is removed by digital subtraction. The interferometer’s performance was verified using standard-optical components as dispersive elements (BK7 lenses and wedge plates), resolving a minimum, phase-change sensitivity of ΔΦ min ≳ 15 mrad and spatial resolution of Δx res ≃ 100 μm. The phase change produced by unknown-density objects (a pulsed-plasma-jet and a pulsed-gas-jet) was measured, and their data were used to recover the original, 2D density profiles using an inverse Abel transform: peak-number density, N gas ≃ 6 × 10 20 cm –3 and N e ≃ 5 × 10 16 cm –3 ; line-integrated density, ∫N gas dl ~ 2 × 10 19 cm –2 and ∫N e dl ~ 1 × 10 16 cm –2 . The techniques and methods developed here are scalable to even larger probe-beam diameters and frame-capture rates, leading to a diagnostic capability that is well-suited for applications involving the real-time measurement of density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Task 12 PV Sustainability - Environmental Life Cycle Assessment of Residential PV and Battery Storage Systems

Using a life cycle assessment (LCA), the environmental impacts from generating 1 kWh of electricity for self-consumption via a photovoltaic-battery system are determined. The system includes a 10 kWp multicrystalline-silicon photovoltaic (PV) system (solar irradiation about 1350 kWh/m2/year and annual yield 1000 kWh/kWp), an iron phosphate lithium-ion (LiFePO4) battery, and other components such as the control system, battery housing, and two inverters (one for the PV system and one for the battery system). Three options for the AC-coupled system with changing battery capacities (5, 10, or 20 kWh nominal capacity) are investigated. The environmental impacts are assessed using the indicators greenhouse gas emissions and cumulative energy demand (separated into total and non-renewable cumulative energy demand). In addition, the four most important impact categories for PV electricity - respiratory inorganics (particulate matter), acidification, energy carrier resource use, and minerals and metals resource use - are assessed according to the environmental footprint (EF) method. Data are drawn from the DETEC data DQRv2:2018, recent literature, and product details provided by manufacturers. The results show larger environmental impacts of PV-battery systems with increasing battery capacity; for capacities of 5, 10, and 20 kWh, the cumulative greenhouse gas emissions from 1 kWh of electricity generation for self-consumption via a PV-battery system are 80, 84, and 88 g CO 2- eq/kWh, respectively. The cumulative greenhouse gas emissions of PV electricity consumed directly or fed into the grid are 54 g CO 2 -eq/kWh. The corresponding total cumulative energy demands are 5.27, 5.40, and 5.50 MJ oil-eq/kWh, with non-renewable energy carriers contributing 1.16, 1.22, and 1.29 MJ oil-eq/kWh. In the investigated EF impact categories, we similarly observe a larger environmental burden with increasing battery capacity, except in the use of minerals and metals. Our sensitivity analyses show that using a nickel cobalt manganese oxide (NCM) lithium-ion battery, instead of an LiFePO 4 battery, leads to a comparable environmental impact in terms of greenhouse gas emissions and cumulative energy demand. However, the NCM battery increases the impact in the EF categories of acidification and respiratory inorganics by 7 and 10%, respectively, whereas energy carrier resource use decreases by 4% and minerals and metals resource use decrease by 1%. Using a copper indium selenium (CIS) PV panel instead of a multicrystalline-silicon decreases greenhouse gas emissions by 24%, non-renewable cumulative energy demand by 13%, and particulate matter emissions by 60% (the largest decrease). Furthermore, the calculated environmental impacts are sensitive to the assumed battery lifetime. A decrease from 5000 to 3000 charge cycles increases non-renewable cumulative energy demand by 24% and greenhouse gas emissions by 16%. Increasing from 5000 to 7000 charge cycles decreases the environmental impacts by 6% and 7% in terms of non-renewable cumulative energy demand and greenhouse gas emissions, respectively. A utility-scale battery system case study shows that using batteries to store PV electricity overproduction reduces greenhouse gas emissions compared to using natural gas backup electricity generation.

14 SOLAR ENERGY↗