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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 OSTI2022

Physics-Informed Sparse Gaussian Process for Probabilistic Stability Analysis of Large-Scale Power System with Dynamic PVs and Loads

This work proposes a physics-informed sparse Gaussian process (SGP) for probabilistic stability assessment of large-scale power systems in the presence of uncertain dynamic PVs and loads. The differential and algebraic equations considering uncertainties from dynamic PVs and loads are reformulated to a nonlinear mapping relationship that allows the application of SGP. Thanks to the nonparametric characteristic of Gaussian process, the proposed framework does not require distributions of uncertain inputs and this distinguishes it from existing approaches. As the original Gaussian process is not scalable to large-scale systems with high dimensional uncertain inputs, this paper develops the SGP with a stochastic variational inference technique. It leads to approximately two orders of complex reduction. A data pre-processing step is also introduced to tackle the coexistence of stable and unstable cases by sample clustering and constructing separate SGPs. The probabilistic transient stability index is analyzed to assess system stability under different uncertain dynamics loads and PVs. Comparisons are performed with the sampling-based, the polynomial chaos expansion-based, and traditional Gaussian process-based methods on the modified IEEE 118-bus and Texas 2000-bus systems under various scenarios, including different levels of uncertainties and the existence of nonlinear correlations among dynamic PVs. The impacts of data quality and quantity issues are also investigated. It is shown that the proposed SGP achieves significantly improved computational efficiency while maintaining high accuracy with a limited number of data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Analysis of AC-DC Converters for Grid-tied High Temperature Steam Electrolysis Systems

Grid-tied HTSE systems have the prospects to produce clean hydrogen enabling power and broad energy systems decarbonization. Most commercially available power electronic converter systems (PECS) are designed for batteries, solar PVs, wind, and other well-established renewable energy resources. Standards (such as IEEE 1547, UL 1741, CA Rule-21, HI Rule-14) exist for PECS used for renewable energy systems such as battery storage and solar PVs. However, those that consider the dynamic behavior of HTSEs and that can be used for large-scale H2 systems are yet to be developed. This paper investigates the performance of these PECS for the HTSE application that are set up at the Idaho National Laboratory for hydrogen production testing, research and development. In particular, the performance analysis of two grid-tied PECS (A and B) is conducted for a 100 kW solid oxide HTSE system. System A consists of 6 units of 30kW MOSFET-switched bidirectional AC-DC rectifier while system B has a single unit of 150kW thyristor-switched ACDC rectifier. Both systems are connected to the HTSE stacks via a DC-DC converter. Different operational conditions of the HTSE system are tested to analyze the dynamic response of the HTSE’s PECS. The experimental results show the need to develop advanced control strategies for PECS that incorporates the dynamics of HTSE systems for improved performance.

08 - HYDROGEN↗
DOE OSTI2025

Analysis of AC-DC Converters for Grid-tied High Temperature Steam Electrolysis Systems

Grid-tied HTSE systems have the prospects to produce clean hydrogen enabling power and broad energy systems decarbonization. Most commercially available power electronic converter systems (PECS) are designed for batteries, solar PVs, wind, and other well-established renewable energy resources. Standards (such as IEEE 1547, UL 1741, CA Rule-21, HI Rule14) exist for PECS used for renewable energy systems such as battery storage and solar PVs. However, those that consider the dynamic behavior of HTSEs and that can be used for large-scale H2 systems are yet to be developed. This paper investigates the performance of these PECS for the HTSE application that are set up at the Idaho National Laboratory for hydrogen production testing, research and development. In particular, the performance analysis of two grid-tied PECS (A and B) is conducted for a 100 kW solid oxide HTSE system. System A consists of 6 units of 30kW MOSFET-switched bidirectional AC-DC rectifier while system B has a single unit of 150kW thyristor-switched AC-DC rectifier. Both systems are connected to the HTSE stacks via a DC-DC converter. Different operational conditions of the HTSE system are tested to analyze the dynamic response of the HTSE’s PECS. The experimental results show the need to develop advanced control strategies for PECS that incorporates the dynamics of HTSE systems for improved performance.

High temperature steam electrolysis↗
DOE OSTI2023

Modeling and Control of Solar PVs for Large Grid Disturbances and Weak Grids

The purpose of this project is to understand dynamic phenomena by designing dynamic models of utility-sale solar photovoltaic (PV) power plants and their interactions with grids; and construct effective coordination strategies for stability enhancement for solar PVs to respond to rapidly changing grid conditions.

14 SOLAR ENERGY↗
DOE OSTI2021

A data-driven network optimisation approach to coordinated control of distributed photovoltaic systems and smart buildings in distribution systems

The increasing integration of distributed energy resources, including demand-side resources and distributed photovoltaics (PVs), into distribution systems has resulted in more complicated power system operation. A data-driven network optimisation approach is proposed to coordinate the control of distributed PVs and smart buildings in distribution networks considering the uncertainties of solar power, outdoor temperature and heat gain associated with building thermal dynamics. These uncertain parameters have a significant impact on the operation and control of distributed PVs and smart buildings, bringing challenges to the distribution system operation. In the proposed data-driven distributionally robust optimisation (DRO) approach, the Wasserstein ball is used to construct an ambiguity set for the uncertain parameters, which does not require the probability distributions to be known. Furthermore, a conditional value-at-risk is incorporated into the Wasserstein-based DRO model and converted into a computationally tractable mixed-integer convex optimisation problem. Benchmarked with robust optimisation and chance-constrained programming, the proposed data-driven model can give a less conservative robust solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Investigating Local Carrier Dynamics in PERC Patterned CdTe Solar Cells

Remarkable progress has been achieved in CdTe photovoltaics (PVs) to further improve cell performance while reducing manufacturing costs. Researchers optimized the front contact that leads the short-circuit current density (J sc ) over 31mA/cm 2 (e.g., (Zn, Mg)O buffer layer and/or alloying CdTe with Se). Reese et al. reported an open-circuit voltage (V oc ) over 1 V with group-V doped single crystal, showing the feasibility of increasing V oc in CdTe PV that is fixed to less than 900 mV in most cases. Recent studies suggested that the V oc improvement in polycrystalline CdTe PVs requires well-passivated back contact. One possible strategy is to use CdMgTe alloy (E g > 1.8 eV), where the band-gap offset (ΔE CB ≈ 0.2 eV) reflects minority carrier electrons, thereby decreasing surface recombination. Another strategy is to utilize a stable Al 2 O 3 layer as an electron reflector; experimental works confirmed the improved performance with a conformal Al 2 O 3 layer. In this configuration, the precise control of Al 2 O 3 (≈1 nm) over the entire CdTe layer is essential because the J sc greatly depends on the tunneling current. While promising, both CdMgTe and Al 2 O 3 passivation on CdTe introduce unfavorable valence band offset that blocks the hole transport. Kephart et al. proposed a patterned passixc vation layer (≈ 20 nm Al 2 O 3 ) with point contacts (≈ 3 μm in diameter) that extract hole carriers. This configuration is similar to the passive emitter and rear contact (PERC) design that has been extensively studied in Si PVs. While remarkably high carrier lifetime and photoluminescence (> 10 X) were measured, consistent improvement in V oc and efficiency in this CdTe PERC were not yet observed. At this time, it is unclear how the surface potential is distributed in the presence of patterned Al 2 O 3 reflectors and how this additional field impacts the PV performance for Cu-doped and group-V doped CdTe PERC devices. To tackle this challenge, we develop robust nanofabrication and characterization platform to study CdTe PERC devices consisting of a patterned Al 2 O 3 layer on CdSe( 1-x )Te x (Cu-doped, GrV-doped; x = 0 to 1; CST). First Solar supplies high-quality CST materials. The dark and light I-Vs under 1-sun illumination are extracted for a series of each set of devices. We perform quantitative and qualitative PV analysis for a series of Cu-doped and Gr-V doped PERC devices, showing notably different V oc changes for GrV-doped compared to Cu-doped PERC devices. This project attempts to produce individual contacts on single grains and grain boundaries to measure lateral transport. As a model system, we use a CdSe( 1-x )Te x film on glass prepared by a colossal grain growth (CGG) technique at National Renewable Research Laboratories (NREL). Our preliminary results confirm that intergranular transport is hindered by the electrical barrier formed near grain boundaries. The PERC fabrication and the lateral transport measurement platform developed in this project can easily be applied to other types of advanced CdSe( 1-x )Te x architectures to better understand local photocarrier transport, in turn, providing the fundamental knowledge to improve the performance of CdTe PVs.

14 SOLAR ENERGY↗
DOE OSTI2024

Benchmark High-Fidelity EMT Models for Power Grid with PV Plants

In recent times electromagnetic transient (EMT) modeling tools have been identified as one of the most important requirements in replicating, analyzing, and investigating the dynamics of the power grid with photovoltaic (PV) plants. However, there are no benchmark models for power grid with PVs to investigate emerging challenges with higher penetration of PVs (like trips and momentary cessations during faults from a region far away). To this end, in this paper, synthetic benchmark high-fidelity EMT dynamic models of power grid with large-scale PV plants are presented. The models are developed in PSCAD and PSCAD/Fortran. Simulation results for different use cases (events) and scenarios are presented.

Marthi, Phani Ratna Vanamali↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2024

Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The impact of policies and business models on income equity in rooftop solar adoption

Low- and moderate-income (LMI) households are less likely to adopt rooftop solar photovoltaics (PVs) than higher-income households in the United States. As the existing literature has shown, this dynamic can decelerate rooftop PV deployment and has potential energy justice implications, in light of the cost-shifting between PV and non-PV households that can occur under typical rate structures and incentive programmes. Here we show that some state policy interventions and business models have expanded PV adoption among LMI households. Additionally, we find evidence that LMI-specific financial incentives, PV leasing and property-assessed financing have increased the diffusion of PV adoption among LMI households in existing markets and have driven more installations into previously underserved low-income communities. By shifting deployment patterns, we posit that these interventions could catalyse peer effects to increase PV adoption in low-income communities even among households that do not directly benefit from the interventions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Real-World 20-Hz IBR Subsynchronous Oscillations: Signatures and Mechanism Analysis

This article provides analyses of subsynchronous oscillations associated with solar photovoltaics (PVs) observed in real world. All have oscillation frequencies at approximately 20 Hz in voltage and current magnitudes. On the other hand, in phase voltage and current, the oscillations show very different signatures. Through constructing simplified linear models and conducting sensitivity analysis, we are able to associate dynamic phenomena with the underlying mechanism and speculate the possible causes of the 20-Hz oscillations. The analysis results have all been validated via simulation results from electromagnetic transient (EMT) test beds constructed in MATLAB/Simscape.

inverter-based resources↗
DOE OSTI2020

Se diffusion in CdTe thin films for photovoltaics

Manipulating CdSeTe bandgrading to enhance photocurrent and carrier lifetime is an essential part of high-performance CdTe photovoltaics (PVs). Here, we examine Se diffusion kinetics in single-crystal and polycrystalline CdTe during deposition, thermal annealing, and CdCl 2 treatments. Se distributions are determined by dynamic secondary-ion-mass spectroscopy and Auger electron spectroscopy depth profiling and coupled with electron backscatter diffraction images of the crystalline structure. Effective bulk and grain boundary diffusion coefficients are determined by analytical models and discussed in the context of processing and film morphology. Se is found to diffuse in CdTe at much higher rates during CdCl 2 treatments than with thermal processing alone. GB diffusion also occurs at a significantly faster rate than bulk diffusion. As a result of these two effects, the near interface bulk and GB Se diffusion during CdCl 2 treatments dominates the bandgrading profiles in CdTe PVs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗
DOE OSTI2021

Electromagnetic Transient (EMT) Simulation Algorithm for Evaluation of Photovoltaic (PV) Generation Systems

Use of inverter-based resources facilitating renewable energy resources such as photovoltaic (PV) generation is increasing rapidly with decreasing costs and reduced emissions associated. To accommodate such rapid growth of inverter-based resources like PV systems, electromagnetic transient (EMT) simulation models of both PV systems and grids are required to analyze the interaction of PVs in the grid (like the post-event analysis). In addition, the EMT simulation would help with the planning of future power grid with a large number of PVs as well as other inverter-based distributed generation systems. In this paper, the EMT simulation models of PV systems and grids are developed based on the differential algebraic equations (DAEs) representing their EMT dynamics. Furthermore, advanced simulation algorithms including numerical stiffness-based hybrid discretization, DAE clustering and aggregation, multi-order integration, and matrix splitting approaches are applied to accelerate the EMT simulation. The proposed algorithm was applied to 125 PV inverters within 52-bus medium-voltage (MV) distribution grid.

Choi, Jongchan↗
DOE OSTI2024

Metal Oxide vs Organic Semiconductor Charge Extraction Layers for Halide Perovskite Indoor Photovoltaics

Halide perovskite indoor photovoltaics (PVs) are highly promising to autonomously power the billions of microelectronic sensors in the emerging and disruptive technology of the Internet of Things (IoT). However, how the wide range of different types of hole extraction layers (HELs) impacts the indoor light harvesting of perovskite solar cells is still elusive, which hinders the material selection and industrial–scale fabrication of indoor perovskite photovoltaics. In the present study, new insights are provided regarding the judicial selection of HELs at the buried interface of halide perovskite indoor photovoltaics. This study unravels the detrimental and severe light–soaking effect of metal oxide transport layer–based PV devices under the indoor lighting effect for the first time, which then necessitates the interface passivation/engineering for their reliant performance. This is not a stringent criterion under 1 sun illumination. By systematically investigating the charge carrier dynamics and sequence of measurements from dark, light–soaked, interlayer–passivated device, the bulk and interface defects are decoupled and reveal the gradual defect passivation from shallow to deep level traps. Thus, the present study puts forward a useful design strategy to overcome the deleterious effect of metal oxide HELs and employ them in halide perovskite indoor PVs.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗