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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Artificial Soiling Replication of Field Losses on Commercial Photovoltaic Modules

Here, this study demonstrates the capabilities of an indoor artificial soiling approach developed to closely replicate the natural, cyclic soil accumulation processes in the field-dust suspension, deposition, and sedimentation/cementation-for a subtropical climate. In this work, a near-field environment is replicated in an artificial soiling cubic chamber through controlled regulation of humidity, temperature, dust type, and dust concentration, based on site-specific historical climate data. Two different models (MA and MB) of full-size commercial photovoltaic modules from a single manufacturer, installed side by side in the mid-Atlantic United States, were retrieved and subjected to artificial soiling experiments and various characterization measurements, including short-circuit current, colorimetry, reflectance, X-ray fluorescence, laser diffraction, and optical microscopy. Both in the field and in our improved field-representative artificial soiling tests, the MA model experienced roughly twice the soiling loss as the MB model. To closely replicate the field soiling losses for a site-specific climate, it is critical to include: 1) The use of field-collected dust with identical dust chemistry and particle distribution instead of standardized ISO 12103 Arizona Road dusts, 2) the use of only a small amount of field-collected dust inside the chamber during the deposition process (e.g., 0.15 g), and 3) the preconditioning of the surface coating for the partial/full dose of UV stress as experienced in the field during sunlight exposure and the abrasion as experienced in the field during regular module cleaning activities, if/as needed. The field-representative artificial soiling method developed here could potentially be adopted for rank ordering of various antisoiling coatings developed by researchers and industry stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2023

Improved Primary Reference Cell Calibrations for Higher Accuracy Photovoltaic Cell and Module Performance Measurements

The adoption of photovoltaic (PV) modules for clean electricity relies on accurate measurements of their performance, which are essential for estimating their energy production potential. Herein, the calibration chain of PV cells and modules, with particular emphasis on primary reference cell calibrations, is discussed. Also, herein, the direct sunlight method the group has developed for these calibrations is presented and critical improvements and upgrades that lead to calibration uncertainty as low as 0.45% are discussed. The ultimate motivation behind this work is to provide low‐uncertainty performance measurements of PV modules, and lowering the calibration uncertainty of primary reference cells is a key first step toward achieving this goal. As the use of solar electricity continues to grow, the demand for primary reference cell calibrations inevitably increases beyond what the small handful of primary calibration laboratories can provide today. Therefore, this work can serve as a useful guide for implementing primary PV reference cell calibrations using the outdoor method, as well as outlining the critical elements required to make these calibrations highly accurate.

Osterwald, Carl R.↗
DOE OSTI2022

Photovoltaic Module R&D Considerations for Soiling Mitigation

Photovoltaic (PV) modules work best in the sunniest environments. Unfortunately, often the sunniest places also have substantial amounts of airborne "dust" that deposits on the front surface of the modules and blocks the sunlight; reducing energy output. In fact, natural soiling has reduced the energy output of PV systems since the technology was first used, and viable mitigation strategies have remained elusive ever since. With the ever-increasing deployments around the world, especially in dusty environments, soiling is becoming a billion-dollar problem, worldwide. While substantial work has been done to examine and resolve some of the issues with PV soiling, often mitigation comes down to physically cleaning the modules. However, a more systematic evaluation of the different module properties correlations to soiling mitigation needs to be done. In many instances, the causal connections between module properties and soiling are simply not known. This lack of knowledge results in a substantial increase in time and effort to evaluate and qualify appropriate soiling mitigation protocols based on site specific issues and the intrinsic module properties that are typically not optimized for mitigating soiling in a given environment. Thus, module property protocols and/or standards are needed to more quickly help identify appropriate module and site-specific mitigation.

mitagation↗
DOE OSTI2025

Reducing module soiling with scalable and robust photocatalytic coatings

The air-glass interface at the front of a photovoltaic (PV) module reflects approximately 4% of incident light, decreasing the potential power output of the module by the same amount. Today’s modules reduce this loss by adding a low-refractive-index (1.25-1.30) SiO2 coating to the sunward side of the module glass; this antireflection coating recovers approximately 3% of the 4% light that would otherwise be lost. While such antireflection coatings work very well on clean, new modules, they do not inhibit soiling—the accumulation of soilants such as dust, pollen, soot, or other foreign material—on the module glass, and soilants reflect and scatter incident light. An improved coating would serve provide not only an antireflection effect, but also an anti-soiling effect. The goal of this project was to develop such a coating and provide a path for it to be manufactured in the U.S. The project successfully designed and fabricated coatings that provided >3% transmittance gain compared to bare glass (matching the performance of commercial antireflection coatings) and displayed anti-soiling behavior in standard laboratory soiling effects. This was achieved by using a Swift Coat proprietary coating deposition technique, aerosol impact-driven assembly (AIDA), to control the porosity and thus refractive index of coatings of photocatalytic materials—such as TiO2—that would otherwise increase (instead of decrease) reflection. These combined antireflection/anti-soiling coatings passed PV industry standard module reliability tests as well as coating-specific abrasion tests, showing that they have the durability needed for decades in the field. Swift Coat scaled the AIDA hardware and deposition process to make mini-modules that were monitored for nearly two years during field tests administered by a third party, as well as demonstrated scaling to the widths of full-sized modules. The fielded mini-modules outperformed reference modules (with commercial antireflection coatings) in two locations, providing a 1% absolute average performance boost and larger increases during periods of heavier soiling. Swift Coat’s cost analysis indicated a coating manufacturing cost below the sales price of today’s antireflection coatings. More than five module manufacturers sampled and assessed the coatings, and three provided letters of support. The coating developed in this project increases the energy output of PV modules, thereby decreasing the cost per kilowatt-hour of solar energy generated. Cheaper solar electricity benefits the public by accelerating the transition to a stable, affordable, carbon-free energy economy. In addition, for select applications in which PV modules are highly visible—such as on residential rooftops—the coating provides an aesthetic benefit because it stays cleaner than today’s modules. Finally, Swift Coat and its prospective customers are U.S. companies, and successful commercialization of this technology will provide U.S. jobs and a secure solar supply chain.

14 SOLAR ENERGY↗
DOE OSTI2023

Development of a Novel Soiling Chamber for Testing Antisoiling Coatings: Preprint

This study presents the development and validation of a novel soiling chamber. The chamber is novel in that it includes wind induced soiling, feedback from a low-cost particulate monitor, and in-situ Isc measurements. Validation with side-by-side identical modules within the chamber produced soiling losses of 7% over 19 hours while the soiling ratio was always within 0.5% between the two modules. Initial side-by-side testing of an anti-soiling coated module versus and uncoated module demonstrated significant wind induced cleaning of the coated module. Specifically, the coated module showed only 0.8% soiling loss while the uncoated module reached as much as 10.5% soiling loss.

photovoltaic↗
DOE OSTI2021

Impact of soiling on Si and CdTe PV modules: Case study in different Brazil climate zones

Soiling, particulate accumulation on photovoltaic (PV) module surfaces, reduces the available solar resource and the resulting generated device power. This case-study summarizes initial results of 5-year research on the contrasting soiling conditions in the tropical, subtropical, and semi-arid climates in Brazil. A major objective is to present a case study of the effects of soiling on PV module performance in different Brazil climate zones that represent the primary areas for the current and expanding Brazil solar installations. For this, the paper presents methodologies to quantify the soiling ratio (SRatio) and soiling rate (SRate) for two representative commercial technologies, polycrystalline or multicrystalline silicon (mc-Si) and thin-film cadmium telluride (CdTe) modules, through soiling monitoring stations deployed in the selected climate regions. An aim is to add to the growing soiling-research knowledge base through addressing these key factors and their relationships to critical electrical, solar resource, thermal, and local meteorological and environmental parameters. This paper presents, evaluates, and compares soiling rates and losses in Belo Horizonte, Minas Gerais (Equatorial Tropical: 19.92° S, 43.99° W), Porto Alegre, Rio Grande do Sul (Humid-Subtropical: 30.05° S, 51.17° W), and Brotas de Macaúbas, Bahia (Semi-Arid: 12.00° S, 42.63° W). The results show that soiling is moderate in all 3-regions, for example with 0.1%/day < SRate < 0.2%/day for Belo Horizonte. Precipitation dominates the cleaning of the modules in the summertime in this climate zone, while it is the major factor year-round in Rio Grande do Sul. Wind is the major issue mitigating the soiling accumulation for the Bahia installation. The methodology incorporates several key refinements, including the normalization and adjustment for the meteorological parameters (temperature, irradiance, wind, precipitation). The evaluations include the region-specific differing effects of non-uniform soiling, natural cleaning, and ambient temperatures.

14 SOLAR ENERGY↗
DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗
DOE OSTI2021

PV Module Design for Recycling Guidelines

The global growth of clean energy technology deployment will be inexorably followed by a parallel growth of end-of-life (EOL) products that bring both challenges and opportunities. Cumulatively, by 2050, estimates project 78 million tonnes of raw materials embodied in the mass of EOL photovoltaic (PV) modules. Owing partly to concern that the projected growth of clean energy technologies could become constrained by availability of raw materials, despite ongoing dematerialization efforts, significant attention under the umbrella of circular economy has been brought to recycling these technologies at EOL. Yet PV has not been designed with recycling at EOL in mind, and it presents challenges to returning embodied raw materials back to use in new products through recycling. This study aims to inform future designs to improve recyclability through synthesis of prior published works augmented by novel recommendations that result in a set of general design for recycling (DfR) guidelines, with a subset specific to PV modules. We further discuss how established trends in design of PV modules could affect recyclability. If adopted today, application of these DfR guidelines could help to mitigate tomorrow's resource scarcity, lower the barriers and cost for PV recycling, and enable a circular economy during the energy transition.

14 SOLAR ENERGY↗
DOE OSTI2022

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗
DOE OSTI2022

Photovoltaic module antireflection coating degradation survey using color microscopy and spectral reflectance

Abstract Commercial antireflective coatings (ARCs) on photovoltaic (PV) module glass can improve module power by 2.5%–3.0%, but their long‐term field performance requires additional study. In this paper, we investigate ARC performance on fielded modules using two nondestructive techniques: reflectance spectroscopy and RGB microscopy, finding a large variation in coating durability and performance. For new coatings, the fleet average nominal power enhancement is 2.8%. This power enhancement is observed to degrade at approximately −0.05%/year absolute over the first 8 years of fielding in arrays that are not regularly cleaned. Interferometry and imaging results imply that coating loss for these modules is due to slow chemical thinning of the initial 125 nm thick coating by 1.4 to 5.0 nm/year. Due to the physics of interference coatings, the performance loss is projected to accelerate as the coating is further thinned, resulting in a coating lifetime (time to 80% of initial performance) of 7.5 to 25 years. At the higher 5.0 nm/year coating loss rates, we estimate that −0.14%/year power degradation of the module can be attributed solely to ARC degradation over the first 20 years. Extreme coating loss is observed on some modules where after 8 years fielding, the coating can be completely removed with a single wet wipe with a lens tissue. A case study is also presented comparing ARC and noncoated modules installed at a single site in 2013. We find that the ARC modules have a 2.6% higher soiling power loss than the noncoated modules; this exceeds the ARC power enhancement of 2.4% and leads to the surprising conclusion that the ARC lowers production for modules in this location due to increased soiling. These results demonstrate that RGB microscopy is a powerful, field‐capable, and quantitative characterization technique for assessing degradation of PV module ARCs.

Karin, Todd↗
DOE OSTI2021

GEDet: Detecting Erroneous Nodes with A Few Examples

Detecting nodes with erroneous values in real-world graphs re- mains challenging due to the lack of examples and various error scenarios. We demonstrate GEDet, an error detection engine that can detect erroneous nodes in graphs with a few examples. The GEDet framework tackles error detection as a few-shot node classification problem. We invite the attendees to experience the following unique features. (1) Few-shot detection. Users only need to provide a few examples of erroneous nodes to perform error detection with GEDet. GEDet achieves desirable accuracy with (a) a graph augmentation module, which automatically generates synthetic examples to learn the classifier, and (b) an adversarial detection module, which improves classifiers to better distinguish erroneous nodes from both cleaned nodes and synthetic examples. We show that GEDet significantly improves the state-of-the-art error detection methods. (2) Diverse error scenarios. GEDet profiles data errors with a built-in library of transformation functions from correct values to errors. Users can also easily “plug in” new error types or examples. (3) User-centric detection. GEDet supports (a) an active learning mode to engage users to verify detected results, and adapts the error detection process accordingly; and (b) visual interfaces to interpret and track detected errors.

Guan, Sheng↗
DOE OSTI2025

Spatial and temporal evaluations of the liquid argon purity in ProtoDUNE-SP

Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by the cathode plane assembly, which is biased to create an almost uniform electric field in both volumes. The DUNE Far Detector modules must have robust cryogenic systems capable of filtering argon and supplying the TPC with clean liquid. This paper will explore comparisons of the argon purity measured by the purity monitors with those measured using muons in the TPC from October 2018 to November 2018. A new method is introduced to measure the liquid argon purity in the TPC using muons crossing both drift volumes of ProtoDUNE-SP. For extended periods on the timescale of weeks, the drift electron lifetime was measured to be above 30 ms using both systems. A particular focus will be placed on the measured purity of argon as a function of position in the detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Robust Distribution State Estimation for Reliable Locational Marginal Pricing under Cyber-Attacks

Here this paper examines the impact of false data injection (FDI) cyber-attacks on distribution system state estimation (DSSE) and the resulting distribution locational marginal price (DLMP) in power markets. Two robust high-breakdown regression estimators, namely S- and MM- estimators, are implemented to provide resistance against FDI attacks targeting measurements and grid topology, creating leverage points. The introduced estimators are compared to the weighted least squares (WLS) with a bad data detection and rejection module (BDD) and the robust Huber M-estimator. The proposed estimators are shown to be effective and compare favorably to both existing Huber M- and the WLS with BDD in the presence of topology FDI attacks. Both the S- and MM-estimators provide good performance in the case of clean and corrupted measurements. Their performance is comparable in this case to the Huber M- and the WLS, followed by a BDD module. The simulation considered a modified distribution IEEE 13 and 34-bus systems where the impact of FDI attack scenarios is shown on the state and the DLMP pricing in the presence of distributed Generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Resource Recovery and Environmental Protection in Wyoming’s Greater Green River Basin Using Selective Nanostructured Membranes (Final Report)

Produced water (PW) represents a sizable waste stream that is co-generated with oil and natural gas production. In 2021 Wyoming ranked 8th and 9th, respectively in domestic oil and natural gas production. In 2017 Wyoming ranked as the 4th highest generator of PW in the U.S, accounting for 7% of the total volume generated. In the context of being the 3rd most arid state in the U.S., the value of water reuse becomes obvious. PW reuse, and resource recovery, in any form requires some level of treatment to remove particulates, residual (free, dispersed) hydrocarbons, organics, and salts. The level of treatment depends on the requirements of the reuse, or resource recovery, application. PW management systems in Wyoming employ in order of volume of PW managed the following management strategies: reinjection for enhanced oil recovery, surface discharge, deep well injection, evaporation ponds (impoundments), and commercial management/treatment. Complicating treatment efforts are the relatively high concentrations of organics (natural and synthetic), dispersed/free hydrocarbons, benzene-toluene-ethylbenzene, and xylenes (BTEX) compounds, biologicals, salts, and minerals. Hydrocarbons (dispersed/dissolved crude oils) and BTEX compounds, as well as synthetic organics, present economic and environmental concerns. The former represents lost revenue, while the latter results in negative environmental impacts like emissions from surface impoundments. The overall objective of this proposal was to synthesize superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes for selectively concentrating and then separating BTEX compounds and oil and grease (O&G) from PW originating from the Greater Green River Basin (GGRB) in Wyoming. Three specific research aims were pursued to accomplish this overall objective. This final report details the development of the superhydrophobic and superhydrophilic membranes, as well as the design of the membrane module prototypes specifically. The technoeconomic assessment is separately reported in another document. 1. Aim #1 – Material optimization and performance evaluation of superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes made by electrospinning/spraying. 2. Aim #2 – Design and construction of cross-flow membrane modules for selectively concentrating and then separating BTEX/oil from GGRB produced water. 3. Aim #3 – Techno-economic assessment of BTEX/oil recovery, and clean water production, using superhydrophilic/oleophobic and superhydrophobic/oleophilic membrane separation for GGRB PW. Superhydrophobic membranes were synthesized by electrospinning poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers onto polyester (PET) substrates and electrospraying nano-carbon black/PVDF-HFP onto the nanofibrous layer. These membranes were characterized by high (>8000 liters per square meter per hour per bar (LMH/bar)) permeance values for pure hydrocarbon phases and a high hydrocarbon selectivity (>96%) when treating GGRB PW. All results were obtained when operating the membrane in a crossflow configuration representative of actual field operating conditions. Solvent/oil properties, specifically viscosity and total surface energy/tension, affected permeance across the membrane, which resulted in light mineral oil (394 LMH/bar) and o-xylene (1834 LMH/bar) being characterized by lower permeance values in the pure phase tests. Mixed phase fluxes between 40 to 80 LMH were obtained for the PW when operating the membrane at a feed pressure of 0.3 bar. Flux decreased as the mixed phase concentration in the feed decreased pointing to the importance of maximizing the collision efficiency between the emulsion and the membrane surface and maximizing the emulsion concentration in the feed and the turbulence within the feed channel. These tests demonstrated that the superhydrophobic membranes developed here are a viable hydrocarbon recovery method for GGRB PWs and should be pursued for testing in pilot-scale trials. Superhydrophilic membranes were successfully synthesized via electrospinning/spraying using polyacrylonitrile (PAN) nanofibers as a base nanofibrous matrix. Integration of polyaniline (PANI) into the nanofibrous matrix produced a superior membrane, for water filtration applications, relative to PAN alone and reduced graphene oxide (RGO) when integrated into the nanofibrous matrix. This conclusion was based on the PANI-PAN resistance to flux loss (fouling) when treating model solvent/oil solutions representative of GGRB PWs and field collected PW from the GGRB. The synthesized PAN membranes outperformed a commercially available PAN membrane designed for oil/water separation. This finding indicates that the surface chemical and physical characteristics of the electrospun membranes presents improved properties for filtration of challenging waters like GGRB PWs. The electrospun membranes therefore show promise overall as a substitute for conventionally polymerized membranes in PW treatment applications. The PANI-PAN membrane specifically presents superior performance characteristics for concentration O&G prior to treatment by the hydrocarbon recovery membrane and producing high-quality filtrate for reuse and/or additional treatment (desalination).

02 PETROLEUM↗
DOE OSTI2025

Lessons Learned on Prize Design in the Perovskite Startup Prize

In 2018, the U.S. Department of Energy's Solar Energy Technologies Office and the National Renewable Energy Laboratory set out to develop a repeatable, predictable prize model with the American-Made Challenges. A new model launched by the Solar Energy Technologies Office in March 2021 was the American-Made Perovskite Startup Prize. This new prize aimed to accelerate the growth of the domestic perovskite industry and support the rapid development of solar cells and modules that use perovskite materials. By sharing the outputs of the prize, we hope that our lessons learned will help continue to build the clean tech entrepreneurship support ecosystem and influence how a successful prize design can be achieved.

14 SOLAR ENERGY↗
DOE OSTI2021

Nanoparticle-Induced Disorder at Complex Liquid–Liquid Interfaces: Effects of Curvature and Compositional Synergy on Functional Surfaces

The self-assembly of surfactant monolayers at interfaces plays a sweeping role in tasks ranging from household cleaning to the regulation of the respiratory system. The synergy between different nanoscale species at an interface can yield assemblies with exceptional properties, which enhance or modulate their function. However, understanding the mechanisms underlying coassembly, as well as the effects of intermolecular interactions at an interface, remains an emerging and challenging field of study. Herein, we study the interactions of gold nanoparticles striped with hydrophobic and hydrophilic ligands with phospholipids at a liquid–liquid interface and the resulting surface-bound complexes. We show that these nanoparticles, which are themselves minimally surface active, have a direct concentration-dependent effect on the rapid reduction of tension for assembling phospholipids at the interface, implying molecular coassembly. Through the use of sum frequency generation vibrational spectroscopy, we reveal that nanoparticles impart structural disorder to the lipid molecular layers, which is related to the increased volumes that amphiphiles can sample at the curved surface of a particle. The results strongly suggest that hydrophobic and electrostatic attractions imparted by nanoparticle functionalization drive lipid–nanoparticle complex assembly at the interface, which synergistically aids lipid adsorption even when lipids and nanoparticles approach the interface from opposite phases. The use of tensiometric and spectroscopic analyses reveals a physical picture of the system at the nanoscale, allowing for a quantitative analysis of the intermolecular behavior that can be extended to other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Benchmarks of Global Clean Energy Manufacturing, 2014-2016

Benchmarks of Global Clean Energy Manufacturing provides an assessment of the global state of clean energy manufacturing over 3 years from 2014 to 2016. Four technologies were examined - wind turbine components (blade, tower, nacelle), crystalline silicon (c-Si) solar photovoltaic (PV) modules, light-duty vehicle (LDV) lithium-ion battery (LIB) cells, and light-emitting diode (LED) packages for lighting and other consumer products. The analysis looked along each technology's manufacturing supply chain, including processing raw materials, producing required subcomponents, and assembling final products. Manufacturing supply chains were evaluated across 13 economies that are the primary manufacturing hubs for these technologies. This Highlights summary report features key findings across the manufacturing supply chains.

42 ENGINEERING↗