Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Solar PV”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Techno-Economic Assessments of Second-Life Batteries for Electric Vehicle Charging Stations

When electric vehicle (EV) batteries degrade below a certain capacity, they may no longer be suitable for automotive use but can be repurposed as second-life batteries (SLBs) for other applications, such as EV charging stations. When integrated with photovoltaic (PV) systems, SLB can store surplus solar energy, reducing reliance on the grid and lowering operational costs. This paper presents a novel techno-economic assessment framework for deploying SLBs in combination with PV in grid-connected EV charging stations. The proposed framework integrates the value proposition, charging station operation, optimal dispatch strategies, battery degradation modeling, input data requirements, and detailed procedures for generating key economic performance metrics. Insightful analyses are performed to assess the performance of SLBs in comparison to new batteries across various cost scenarios. The results indicate that SLBs become financially attractive when their cost is 40% or lower than new batteries.

energy storage↗
DOE OSTI2023

Estimating the Value of Worker Training: A System Reliability & LCOE Perspective

This workshop presentation briefly describes the labor standards required for large photovoltaic (PV) systems (>1MWac) to receive the full investment tax credit from the Inflation Reduction Act. The potential for labor standards to affect aspects other than upfront installation costs (such as energy generation or maintenance expenses) is analyzed using levelized cost of energy (LCOE) calculations. This considers benefits which may come from better training for workers, more productive workers, or improved installation quality, using NREL's simplified PV-specific LCOE calculator at pvlcoe.nrel.gov.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2023

High-Performance Passivating Contacts for Si PV Based on Engineered, Doped Nanopinholes through Dielectric Layers

We present a novel, industrially relevant method to fabricate high-performance poly-Si passivating contacts for Si PV. Passivating contacts based on SiOx/poly-Si layer stacks have been implemented in record-efficiency homojunction Si solar cells. In this technology, the carrier transport through a surface-passivating SiOx is enabled either by quantum-tunneling or nanopinholes. The doped poly-Si layer provides charge-carrier selectivity. Previously, the ISFH research group demonstrated a record 26.1% efficient Si homojunction cell, where transport pinholes in ~2 nm SiOx were produced by thermal breakdown at > 1000 degrees C, which is hard to control and is surface morphology-dependent. At room temperature, our new process uses electroless plating of Ag nanoparticles, followed by metal-assisted chemical etching. Nanogalvanic corrosion yields < 20 nm-wide nanopinholes in an insulating > 2 nm SiOx layer. The nanopinholes are filled by a heavily doped a-Si:H overlayer. We drive in the dopants into the Si wafer with subsequent high-temperature annealing. Preferential incorporation of dopants at pinhole locations results in nanoscale p+/n or n+/n junctions near the wafer interface. Each heavily-doped nanoscale pinhole junction collects and transports photogenerated carriers to the cell metal contacts. The density of the engineered nanopinholes can be tuned over a wide range which is critical for optimization of device performance. The same nanogalvanic corrosion principles can be applied to produce doped transport pinholes in well-passivating thick dielectric SiOx/SiNy stacks. Importantly, our process does not rely on thermal breakdown of the dielectric layers and can be applied to textured wafers resulting in Si solar cells with > 20% conversion efficiency.

dielectric layer↗
DOE OSTI2026

Interconnect: Cooperative Research and Development Final Report, CRADA Number CRD-13-00507 (Project 4)

This CRADA modification involves analyses on a variety of CdTe-PV related materials, test structures, solar cells, and modules produced at FSLR and/or NLR and adds analysis related to module degradation and reliability. Materials will be provided by FSLR, NLR, and/or by interleaving FSLR and NLR layers and processes. Module reliability activities will include technical risk assessment, materials characterization, module and test structure characterization, modeling, accelerated test development, and outdoor testing.

14 SOLAR ENERGY↗
DOE OSTI2025

U.S. Solar Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Solar Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NLR's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5734: see the "U.S. Solar Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.11.3 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano

14 SOLAR ENERGY↗
DOE OSTI2023

An Open-Source Python Library for Modeling LETID and LID in Silicon Solar Cells and Wafers

This poster demonstrates an (in development) open-source software library, written in python, to aid in modeling and understanding light- and elevated temperature-induced degradation (LETID) and boron-oxygen light-induced degradation (B-O LID) in silicon solar cells and wafers. We discuss the underlying equations and necessary input parameters for constructing realistic models. We demonstrate several use cases for the library, including modeling LETID progression in scenarios like indoor, accelerated tests and outdoor field deployment. We also demonstrate using the library to model B-O LID, and we demonstrate using the library to model degradation in passivated wafers, rather than solar cells.

LETID↗
DOE OSTI2021

Floating Photovoltaic System Cost Benchmark: Q1 2021 Installations on Artificial Water Bodies

In this report, we conduct a bottom-up analysis of the installed costs for FPV systems deployed on artificial water bodies under average site conditions (wind load of about 40 m/s, snow load of 20 psf, water depth of 50 m, water level variation of 10 m, and swell height of 1 m). We estimate an installed system cost premium of $\$0.26$/WDC (25%) for 10-MWDC fixed-tilt FPV systems, compared with ground-mounted, fixed-tilt PV installed over bare ground. Higher structural costs related to the floats and anchoring system are the largest contributors to this premium. Currently, site investigation costs are also higher for FPV because of the additional effort needed to plan and design these more complex installations. Our preliminary sensitivity analysis shows that the installed cost of FPV systems is most sensitive to float costs, wind and snow loading, and module efficiency. FPV deployment is in an early stage, and additional experience, best practice development, and new configurations and technologies could help reduce the costs of FPV systems over time.

14 SOLAR ENERGY↗
DOE OSTI2022

Environmental and Circular Economy Implications of Solar Energy in a Decarbonized U.S. Grid

This report addresses environmental and circular economy (CE) considerations related to solar technologies via novel analysis of the three Solar Futures core scenarios as well as synthesis of published research. We organize these issues into the three basic life cycle phases of a solar technology: manufacturing, operation (including site selection and construction), and EOL. Related environmental justice issues are also explored. Finally, we recommend research and development (R&D) activities that could help clarify challenges and identify solutions. Because PV deployment is projected to be much larger than CSP deployment, we offer a more detailed analysis of PV-related issues.

14 SOLAR ENERGY↗
DOE OSTI2022

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks, With Minimum Sustainable Price Analysis: Q1 2022

NREL's bottom-up cost models can be used to assess the minimum sustainable price (MSP) and modeled market price (MMP) of PV and storage systems having various configurations. MSP can be used to estimate future potential cost-reduction opportunities for PV and PV-plus-storage systems, thus helping guide research and development aimed at advancing cost-effective system configurations. MMP can be used to understand the cost of systems under recent market conditions. The MSP data in this annual benchmarking report will be used to inform the formulation of, and track progress toward, the Solar Energy Technologies Office's Government Performance and Reporting Act cost targets.

14 SOLAR ENERGY↗
DOE OSTI2023

PV Stormwater Management Research and Testing (PV-SMaRT) (Final Technical Report)

The objective of the Photovoltaic Stormwater Management Research and Testing (PV-SMaRT) project was to develop and disseminate research-based, solar-specific resources for estimating stormwater runoff at ground-mounted PV facilities and detail stormwater management and water quality best practices. The intended use of stormwater management and water quality best practices and stormwater runoff estimation resources is to reduce balance of system soft costs associated with stormwater infrastructure requirements and improve water quality through research-tested best practices. Currently, stormwater regulations and guidelines vary by jurisdiction and can lead to regulatory uncertainty and increased compliance costs for managing stormwater runoff at solar sites. To address these concerns, the NREL team and its partners (University of Minnesota, Great Plains Institute, and Fresh Energy) established and engaged an advisory Water Quality Task Force (WQTF); conducted field research on stormwater infiltration and runoff at five ground-mounted PV sites; validated a 3-D hydrologic model to predict water runoff and generate stormwater runoff coefficients for a range of site conditions and PV designs; developed a stormwater management and water quality best practices document; and engaged with local jurisdictions and other stakeholders to disseminate best practices, stormwater runoff coefficients, and other tools. Key outputs of this project were a PV-SMaRT Runoff Calculator developed by University of Minnesota, a webinar detailing project outcomes and how to use the PV-SMaRT runoff calculator, and a document on Best Practices for regulators and developers regarding stormwater runoff at PV sites.

14 SOLAR ENERGY↗
DOE OSTI2023

Energy in the Balance: PV Reliability to Power the Energy Transition

We present an analysis of the effects of reliability on our ability to achieve the energy transition deployment targets. We examine three end of life modes as captured in the PV ICE tool; degradation, failures, and project lifetime. Recommendations are made for improving PV reliability for achieving energy energy transition.

circularity↗
DOE OSTI2026

Resilience of High-Efficiency CdSeTe:As and CdSeTe:Cu Solar Cells to Proton Irradiation

Power generation in space is currently dominated by expensive III-V multi-junction photovoltaic (PV) devices and cheap crystalline silicon (c-Si) PV devices. Both of these technologies degrade rapidly in proton-radiation-rich space environments, such as the Van Allen belt. The present study of cadmium selenide telluride- (CdSeTe-) based PV devices exposed to 150-to-1500 keV proton irradiation with fluences up to 9 x 1013 cm-2 reveal a more radiation-hard alternative to III-V and c-Si PV technologies. We report on measurement and analysis of current density vs voltage (JV), external quantum efficiency (EQE), external radiative efficiency, and capacitance vs voltage (CV) characteristics. JV characteristics of As-doped CdSeTe devices show 80% remaining power conversion efficiency (PCE) relative to unexposed controls when exposed to 650 keV protons at a fluence of 1012 cm-2. Under these same irradiation conditions, Cu-doped CdSeTe devices demonstrate an even better 95% PCE retention compared with unirradiated control devices. Evidence of radiation-induced absorber p-type doping compensation is observed in the glass-side EQE at 0 V and CV characteristics of most of the irradiated CdSeTe:As devices, but clear compensation is evident only for the most heavily irradiated CdSeTe:Cu devices. Elevated blue-green photocurrent in the film-side 0 V EQE suggests a buried junction in the most heavily irradiated CdSeTe:As devices. Although CdSeTe:Cu devices are the more resilient of the CdSeTe structures, both CdSeTe-based technologies are radiation-hard when compared to c-Si and III-V multi-junction PV.

14 SOLAR ENERGY↗
DOE OSTI2022

A Sparse and Low Rank Penalized Signal Decomposition Model with Constraints: Anomaly Detection in PV Systems

Recently, robust PCA has seen its wide application in various industries for its ability to perform the task of anomaly detection. The essence of robust PCA approach is to break down the signal into a low rank component and sparse component. In many applications, a simple breakdown of the signal without accounting for the signs of low rank components and sparse components would violate the physical constraints of the decomposed signal. In addition, often times, the signals in the real world collected for a long duration has smooth changes within a day and between days. As an example, the power signals collected in a photovoltaic (PV) system are cyclostationary, exhibiting these characteristics. Neglecting the smoothness of signals would result in miss detection of anomalous signals which are smooth within a day but non-smooth between days and vice versa. In this paper, we developed a signal decomposition approach for the purpose of anomaly detection based on the idea of low rank and sparse decomposition taking into consideration the signs of the decomposed low rank and sparse components and the within-day and between-day smooth changes in the original signals. The proposed unsupervised approach for fault detection eliminates the need for faulty samples required by other machine learning methods. It does not require the full I-V characteristics to work. Furthermore, there is no need for complex modelling of PV systems as in the case of power loss analysis. Using Monte Carlo simulations, we demonstrate the ability of our proposed approach for detecting anomalies of different duration and severity in PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2024

2024 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2024 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.

Array↗
DOE OSTI2024

Benefits of the SolarAPP+ Online Permitting Software

The Solar Automated Permit Processing Plus (SolarAPP+) software is an online platform that provides plan review and instantly issues permits for code-compliant residential photovoltaic (PV) systems.

automated permitting↗