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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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DOE OSTI2018

Proceedings of the 2018 PV Reliability Workshop, 27 February - 1 March 2018, Lakewood, Colorado

NREL hosts an annual Photovoltaic Reliability Workshop (PVRW) so solar technology experts can share information leading to the improvement of PV module reliability. Such improvement reduces the cost of solar electricity and promotes investor confidence in the technology - both critical goals for moving PV technologies deeper into the electricity marketplace. This document collects the presentations and posters from the 2018 PV Reliability Workshop, which was hosted by NREL from Tuesday, February 27, to Thursday, March 1, 2018.

14 SOLAR ENERGY↗
DOE OSTI2018

Soiling Related Abrasion and the Development of a PV Abrasion Standard

The natural soiling and consequent cleaning of photovoltaic (PV) modules result in abrasion damage to the cover glass. The durability of the front glass has important economic consequences, including the use of antireflective and/or antisoiling coatings as well as the method and frequency of cleaning-maintenance. The abrasion of glass and coated glass has been explored in a field study, including the soiling-prone locations of: Dubai (United Arab Emirates), Kuwait city (Kuwait), Mesa (Arizona), Mumbai (India), and Sacramento (California). Dry brush cleaned specimens will be compared to those subject to artificial brush testing or falling sand abrasion. The characteristics of material integrity, optical transmittance, surface energy, surface roughness, and scratch size were examined using an optical microscope, spectrophotometer, contact goniometer (for water), interferometer, and atomic force microscope, respectively. The findings of this study will be used to provide feedback regarding the cleaning equipment, cleaning methods, and coatings used in the PV industry. The study here will also be used to aid the development of an abrasion standard for the PV industry.

14 SOLAR ENERGY↗
DOE OSTI2019

Improving Solar PV Degradation Prediction Certainty: PREDICTS2 (Final Technical Report)

The rate and type of in-service PV performance degradation vary for different module designs, vintages, and operating climates. The current IEC 61215 module qualification testing standard can be used to identify design and manufacturing flaws that may lead to early life failures, but it was not intended to accurately predict degradation rates in the first 5 to 10 years of a PV plant’s lifetime, nor long-term performance, under varied operating conditions. Correlations between accelerated aging data and real-world degradation data are needed to better predict wear-out degradation in response to environmental stressors, such as elevated temperature, temperature cycling, moisture, wind load, and solar radiation. The PREDICTS2 project aged 36 pristine-condition ‘spare’ modules from a commercial PV power plant in the U.S. Southwest using the IEC 61215 and Qualification Plus (Qual Plus) testing standards. The study is unique in its ability to compare performance degradation data for fielded modules operating outdoors for 6 years in a commercial plant environmental with degradation data for modules of the same make, model and vintage that have been aged artificially in an indoor laboratory. Changes in individual module current-voltage (I-V) curve data were measured before and after the artificial aging process and compared to I-V curve data for the fielded modules. This project advanced the industry’s understanding of how environmental stressors affect performance degradation and established relationships between degradation mechanisms and changes to module electrical parameters and power loss. Improved certainty in degradation rates is expected to be the greatest source of LCOE reduction resulting from this project. Reducing the spread in the degradation rate probability distribution lowers project risk, which translates to lower project financing costs.

14 SOLAR ENERGY↗
DOE OSTI2018

Using Federal Energy Assistance Funds for PV to Reduce Energy Burden for Low-Income Households

Though the rapid decline in the cost of solar has resulted in unprecedented levels of solar deployment across the country, the majority of residential solar installations have been in middle-to-affluent households. Also, federal energy assistance programs have traditionally focused on weatherization with energy efficiency measures or bill assistance. Coupled with innovative financing mechanisms, solar photovoltaics (PV) now present another attractive option for helping low-income households reduce their energy burden. Seizing this opportunity, several states have undertaken efforts to include solar investments in Department of Health and Human Services' Low-Income Heating and Energy Assistance Program (LIHEAP) and the Department of Energy's Weatherization Assistance Program (WAP) funded projects. To support these state initiatives, DOE's WAP and the Solar Energy Technologies Office (SETO) have been collaborating with the National Renewable Energy Laboratory (NREL) to provide states with additional guidance and technical support to gain approval to use WAP funds for PV. Early examples of states demonstrating cost effectiveness of PV within Colorado and New York state SETO and NREL have also begun exploring how established solar business models could align with the LIHEAP utility assistance model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

PV High Wind User Test Facility

The creation of a PV high wind test facility at the NREL Flatirons Campus that will enable private and public research efforts aimed at storm hardening PV systems. The facility will be instrumented to monitor effects of high wind conditions on modules and other array components. These in-field tests will coordinate with flow models, wind tunnel testing, validation of PV aeroelastic design codes, and post-testing module and system component analysis.

14 SOLAR ENERGY↗
DOE OSTI2020

Impact of Aggregated PV on Subsynchronous Torsional Interaction

This paper investigates induced oscillation (specifically subsynchronous torsional interactions) in power systems arising from photovoltaic (PV) power modulation. Time domain simulations of a modified IEEE first-benchmark system are presented and analyzed. In the IEEE benchmark system, a PV generator was added at the same bus where the synchronous generator is connected. The impact of different parameters of the PV inverters’ volt-volt-ampere reactive (volt-var) curve on SSTI is examined. The most severe impact found arises from the time response of the inverter’s reactive power change. A second-order time response with natural frequency matching the rotor speed deviation oscillation frequency and low-damping ratio quickly drives the system to an unstable region. Although it is highly unlikely that conditions necessary for distributed energy resource-induced oscillations would occur in the field, with knowledge of this vulnerability in mind, inverters' control parameters can be designed to avoid it.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems: Preprint

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗
DOE OSTI2022

Metal Oxide Varistor (MOV) Lifetime Estimation with Impulse-Based Testing in PV Inverter Systems: Preprint

Surges caused by lightning strikes could damage electrical components in photovoltaic (PV) systems. Metal oxide varistors (MOVs) are commonly used to protect PV systems from lightning strikes. In this paper, a holistic impulse-based MOV lifetime estimation framework is proposed. The impacts of peak current and fault duration induced by lightning events are considered in the MOV lifetime estimation framework. Moreover, the impact of different parameter combinations on MOV lifetime estimation is analyzed. The effectiveness of the proposed work is validated in a PV inverter test system developed in MATLAB/Simulink.

lifetime estimation↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2025

Solar Photovoltaic (PV) Module Facts and Trends

Unprecedented growth of solar PV has led to growing concerns about PV module toxicity and potential environmental and human health impacts. This factsheet provides objective, science-based data to help address these concerns and empower communities with the resources they need to make solar PV decisions.

14 SOLAR ENERGY↗
DOE OSTI2023

United States Utility-Scale PV Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for utility-scale PV across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE), levelized cost of transmission (LCOT), and more for each reV site (~60,000 sites). Hourly generation profiles are available for each reV site and can be matched to the available capacity in the supply curve (refer to the Jupyter Notebook). The composite exclusion TIFF is a single file that delineates areas where PV installations are permissible based on various siting assumptions. This data packet contains information for the Reference and Limited siting scenarios. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

2023↗
DOE OSTI2018

NREL Suite of Tools for PV and Storage Analysis

Many different factors such as the solar resource, technology costs and incentives, utility cost and consumption, space available, and financial parameters impact the technical and economic potential of a PV project. NREL has developed techno-economic modeling tools that can be used to evaluate PV projects at a site.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Considerations for Implementing PV Plus Storage Systems at Federal Buildings and Campuses

Federal agencies have a long history of using solar photovoltaics and battery storage (PV plus storage) systems at remote sites where the technologies can offset costly diesel fuel. However, recent declines in lithium-ion battery costs, along with changes in net metering policies and utility rate structures, are opening up opportunities for PV plus storage to be deployed cost-effectively at grid-connected sites.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Impact of distributed power electronics on the lifetime and reliability of PV systems: Impact of distributed power electronics

Here, this paper quantifies the impact of distributed power electronics in photovoltaic (PV) systems in terms of end-of-life energy-capture performance and reliability. The analysis is based on simulations of PV installations over system lifetime at various degradation rates. It is shown how module-level or submodule-level power converters can mitigate variations in cell degradation over time, effectively increasing the system lifespan by 5-10 years compared with the nominal 25-year lifetime. An important aspect typically overlooked when characterizing such improvements is the reliability of distributed power electronics, as power converter failures may not only diminish energy yield improvements but also adversely affect the overall system operation. Failure models are developed, and power electronics reliability is taken into account in this work, in order to provide a more comprehensive view of the opportunities and limitations offered by distributed power electronics in PV systems. Lastly, it is shown how a differential power-processing approach achieves the best mismatch mitigation performance and the least susceptibility to converter faults.

14 SOLAR ENERGY↗
DOE OSTI2025

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗
DOE OSTI2025

Techno-economic implications and cost of forecasting errors in solar PV power production using optimized deep learning models

Accurate solar Photovoltaic (PV) power forecasting is important for enhancing both the performance and economic feasibility of PV systems. This study evaluates several deep learning models, including Dense Neural Networks (DNN), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and a hybrid LSTMCNN model, for predicting PV power production one day in advance. Prior to optimization, the models exhibited relatively high errors, with the best model (DNN) achieving a Root Mean Square Error (RMSE) of 31.13 kW and a coefficient of determination (R 2 ) of 62.15 %. After employing Bayesian optimization, the LSTM-CNN model demonstrated the best performance, with the RMSE reduced to 9.79 kW and R 2 improved to 97.62 %, showcasing significant enhancement in predictive accuracy. Here, the economic evaluation considered three cases: rewards for underestimation (0.08 USD/kWh), no rewards, and penalties for both over-and underestimation (120 % of the utility tariff). In the rewards scenario, the LSTM-CNN model reduced the Levelized Cost of Electricity (LCOE) by 4 %, while in the penalty scenario, a backup diesel generator would have increased the LCOE by 49 %. Additionally, the LSTM-CNN model minimized financial losses, achieving the lowest penalties and maximizing net cash flow compared to other models, demonstrating its overall technical and economic superiority.

Deep learning↗
DOE OSTI2014

Denitrification versus respiratory ammonification: environmental controls of two competing dissimilatory NO 3 – /NO 2 – reduction pathways in Shewanella loihica strain PV-4

Denitrification and respiratory ammonification are two competing, energy-conserving NO 3 – /NO 2 – reduction pathways that have major biogeochemical consequences for N retention, plant growth and climate. Batch and continuous culture experiments using Shewanella loihica strain PV-4, a bacterium possessing both the denitrification and respiratory ammonification pathways, revealed factors that determine NO 3 – /NO 2 – fate. Denitrification dominated at low carbon-to-nitrogen (C/N) ratios (that is, electron donor-limiting growth conditions), whereas ammonium was the predominant product at high C/N ratios (that is, electron acceptor-limiting growth conditions). pH and temperature also affected NO 3 – /NO 2 – fate, and incubation above pH 7.0 and temperatures of 30 °C favored ammonium formation. Reverse-transcriptase real-time quantitative PCR analyses correlated the phenotypic observations with nir K and nos Z transcript abundances that decreased up to 1600-fold and 27-fold, respectively, under conditions favoring respiratory ammonification. Of the two nrfA genes encoded on the strain PV-4 genome, nrfA 0844 transcription decreased only when the chemostat reactor received medium with the lowest C/N ratio of 1.5, whereas nrfA 0505 transcription occurred at low levels (≤3.4 × 10 –2 transcripts per cell) under all growth conditions. At intermediate C/N ratios, denitrification and respiratory ammonification occurred concomitantly, and both nrfA 0844 (5.5 transcripts per cell) and nir K (0.88 transcripts per cell) were transcribed. Furthermore recent findings suggest that organisms with both the denitrification and respiratory ammonification pathways are not uncommon in soil and sediment ecosystems, and strain PV-4 offers a tractable experimental system to explore regulation of dissimilatory NO 3 – /NO 2 – reduction pathways.

54 ENVIRONMENTAL SCIENCES↗