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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Building a framework to genetically characterize “feather spots” and understand demographic impacts of solar energy sites on migratory bird populations

The lack of data on the impact of utility-scale solar facilities on avian species and populations adds to the cost of siting and operation. As much as 32 percent of the avian biological material (feathers and carcasses) recovered from solar facilities remain unidentified, because they often take the form of “feather spots”. Feather spots are remains of impacted animals that can be separated into two broad categories: 1) those remains that may be visually identified to a species, or 2) those that cannot be visually identified to a species due to degradation from the environment and/or scavenger activity (listed as “unknown”). Even when feather spots can be identified to species, they cannot be visually assigned to particular breeding populations. In some cases, it is unknown whether multiple feather spots represent single or multiple individuals. This project’s objectives were to: 1. Use a developed, genetic-based technique to identify and determine the species, population of origin, and number of individuals found in feather spots recovered from solar facilities. 2. Implement collected data and resulting analyses to develop a publicly accessible web-based decision-making tool that can be used by the solar industry, regulators and other stakeholders to inform siting, mitigation, and conservation management efforts. 3. Establish a not-for-profit fee-for-service center at UCLA to ensure collection and identification of feather spots continue after the project period of performance. During the Project Period, we proposed to establish a pipeline for collecting, transporting, and storing of avian biological material collected at solar facilities and the collection and identification of feather spots to species and individual. We proposed the development of a genetic-based framework that would recover viable DNA from feather spots, amplify this DNA (i.e., make millions of copies of the original DNA), and use it to match the resulting sequences to a national database of known species of birds. The result would be the identification of feathers spots that were previously unidentified, and the incorporation of these samples into a larger database that included all samples recovered from solar facilities. The resulting report (below) details the result of this work and its alignment with proposed activities. We proposed the use of the data collected to assess the comparative risk to specific species or populations of species from solar facilities. For some species, we have already identified genomic markers of specific breeding populations and developed “genoscapes,” maps of unique genetic variation across the full breeding range of a species. We used these (previously and newly developed) genoscapes to probabilistically link a feather spot to the specific breeding populations from which it originated (assignment probabilities range from 75%-100% depending on species and population groups). For those species without genoscapes, we developed a vulnerability and susceptibility estimate that determines the relative local and regional risk to populations that are in geographic proximity to solar facilities, using citizen science data (Breeding Bird Survey (BBS) and eBird). These two feather spot processing pipelines (see Figure 1 below) provide quantitative estimates as to the numbers of individuals from a given population of origin that are affected by solar facilities, and ultimately can reduce costs to the consumer by reducing the industry costs associated with mitigation and siting strategies for future solar energy development.

14 SOLAR ENERGY↗
DOE OSTI2022

Evaluation of Use Cases and Types of Databases for Hosting Wind Power Data

The goal of the National Wind Power Production Data Dashboard project is to develop a publicly available platform to model, process, and share wind power with uncertainty quantification for the current and future onshore and offshore wind plants across the continental United States. As of 2021, more than 70,000 utility-scale wind turbines have been installed across the United States and this number is expected to grow in the next few years. A large-scale wind power production database is needed for stakeholders (policy makers, operators, and researchers) to access easily for their decision-making. Currently, meeting that need is a challenge. Most wind power operators and system operators focus on regions of their own interest, and the data are usually inaccessible to the public.

17 WIND ENERGY↗
DOE OSTI2024

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2024 Edition [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.7 million systems installed through year-end 2023, representing close to 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, roof-coverage ratios, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and customer segmentation -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive analysis and a multi-variate regression to estimate the effects of key pricing drivers for residential systems installed in 2023.

14 SOLAR ENERGY↗
DOE OSTI2024

Lab Collaboration Project (LCP) for Marine Energy: Quantifying Collision Risk for Fish and Turbines Final Technical Report (Task 10)

A persistent environmental concern for the widespread deployment of tidal turbines is the potential for fish and marine mammals to collide with rotating blades (Copping et al. 2016, Copping and Hemery 2020). This is a consequence of well-documented bird and bat mortalities around wind turbines (Smallwood 2007, Thompson et al. 2017), as well as fish mortality at conventional hydropower dams (Pracheil et al. 2016) and tidal barrages (Dadswell and Rulifson 1994). However, unlike hydropower dams or barrages, tidal turbines do not involve structures that channel all flow through the turbines. Similarly, while functionally similar to wind turbines, tidal turbines often operate at lower relative velocities and, depending on the end-use application, may be significantly smaller than utility-scale wind turbines. Both of these factors reduce the likelihood and severity of collision, but the knowledge base on this topic remains limited.

13 HYDRO ENERGY↗
DOE OSTI2024

Hydrogen and Power Co-Production Using Direct sCO 2 Power Cycles

This report presents the techno-economic analysis (TEA) results of integrating a modified autothermal reforming (ATR) hydrogen (H 2 ) production plant with a natural gas-fired, utility-scale power plant based on the direct supercritical carbon dioxide (sCO 2 ) power cycle. In this study, the H 2 production and the power plant are fully integrated in terms of heat, fuel, and carbon capture and storage (CCS). The ATR process has significant waste heat available for heat integration with a direct-fired sCO 2 power plant that benefits the power plant efficiency. The off-gas stream from the modified ATR process is primarily carbon dioxide (CO 2 ), carbon monoxide (CO), and residual H 2 . As supplemental fuel, it has beneficial heating value in the CO and H 2 that can be used in the direct sCO 2 power cycle. Finally, the direct sCO 2 power plant can isolate the CO 2 produced at the facility for CCS.

08 HYDROGEN↗
DOE OSTI2024

Project No. 5: Evaluating Dredged Materials for Energy Storage Applications with Economic and Carbon Benefits (CRADA Final Report)

The New York Power Authority (NYPA) is committed to supporting the Climate Leadership and Community Protection Act (CLCPA) through its VISION2030 strategic plan. As a clean energy provider, NYPA is seeking to demonstrate leadership in every aspect of its business by taking a comprehensive approach to sustainability management and integrating sustainability principles into day-to-day decision-making. This effort includes planning for climate resilience through projects that mitigate climate risk in our operations and prioritize climate opportunities in our investments. Canal Corporation, a subsidiary of NYPA, is charged with maintaining minimum water depths for navigation in the Cayuga-Seneca, Champlain, Erie and Oswego Canals. In order to do so, an average volume of 280,000 cubic yards of sediment is dredged annually and held in Upland Disposal Sites (UDS) permitted by the New York Department of Environmental Conservation (NYSDEC). The required on-land storage at UDSes are nearing capacity, and disposal opportunities are costly, both economically and environmentally. Novel energy storage technology developed by NREL provides an opportunity for meeting NYPA's need to find reuse options for dredged materials and commitment to providing clean reliable energy. This would also support NYPA's goal of developing 300 MW of utility scale storage and enabling 150 MW of distributed storage by 2030. NREL will consult NYPA on the environmental and economic impact of reusing dredged materials as useful commodities such as energy storage media, construction sand or industrial uses. Test and material characterization methods will be based on current NREL storage material characterization approaches. NREL worked with NYPA on sample preparation, material testing, test results analysis. Test and material characterization methods were based on current NREL storage material characterization approaches. The team analyzed the environmental and economic impact of reusing dredged materials as useful commodities such as energy storage media, construction sand or industrial uses. The test and analysis works have achieved the project goal in characterizing NYPA dredging materials and verifying their various uses including construction sand and thermal energy storage media. Uses of dredging materials as useful materials will bring economic and environmental benefits and avoid disposal costs.

25 ENERGY STORAGE↗
DOE OSTI2024

Distributed Wind Monitoring Best Practices

Accessible performance and operational data have been identified as a key enabler for distributed wind energy industry advancement. While utility-scale wind turbines benefit from reliable and continuous supervisory control and data acquisition (SCADA)-based monitoring platforms, monitoring of the U.S. fleet of distributed wind (DW) turbines has been more inconsistent, unreliable, and sometime difficult to access. Without fleet monitoring data, the industry will never understand and thus work to improve turbine under-performance and reliability issues. For the DW industry to scale up, attract investors, and boost credibility, fleetwide monitoring must be robust and reliable, select data must be made accessible to stakeholders, and the data must be in a format useful to users. To help move the industry toward a more standardized, accessible stream of monitoring data, this distributed wind monitoring best practices report attempts to cover topics including key monitoring channels, hardware, communication strategies, and accessibility. Strategic engagement with DW original equipment manufacturers (OEMs), service providers, lab and university researchers, testing organization, certification bodies, end users and solar photovoltaic (PV) monitoring experts has enabled a better understanding of the current state-of-the-art of monitoring and aided in articulating this set of best practices that will guide OEMs toward harmonized monitoring strategies, aimed at a future goal of achieving accessible performance and operational data for the entire fleet of U.S. distributed wind turbines.

17 WIND ENERGY↗
DOE OSTI2024

Planar Transformer Systems for Modular Power Electronics in Long-Haul, Low-Cost PV Systems

This project successfully developed and verified a new approach for medium voltage (MV) planar transformers for use in emerging, utility-scale, modular PV systems. This approach simplifies their manufacture, improves their isolation capability, lowers their cost, and reduces their volume and loss, while also creating flexibility in the materials that can be used.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar Photovoltaic (PV) Damage Assessment After Typhoon Mawar: Findings and Recommendations for Resilient PV on Guam

A team from the National Renewable Energy Laboratory (NREL) visited Guam in August 2023 to assess failure modes of solar photovoltaic (PV) systems after Typhoon Mawar and to provide recommendations to increase the resilience of PV systems on Guam. The team visited 30 systems: commercial and utility scale, and rooftop and ground-mounted. The team observed systems with no apparent damage, as well as systems that were completely lost. Systems fared very well overall. The average failure rate of rooftop systems was 18%, with a median failure rate of 2%, meaning the few systems that suffered total loss pulled up the average. Only eight 8 of the 25 rooftop systems suffered more than 5% damage. All ground-mounted systems suffered less than 0.5% damage, aside from a carport that lost 16% of its modules. PV systems at Andersen Air Force Base suffered 5% damage on average, with a median system failure of 0.6%. In almost all cases, failures were the result of: (1) Inadequate clamping of the module frame to the mount, (2) Module mounting clamps rotating out of underlying support rail (i.e., T-bolt that rotates free at less than 60 degrees of rotation), (3) An object hitting the panel resulting in a fracture, and in some cases leading to a cascading failure of several more panels, and (4) Excessive tilt angle (in Guam, greater than 5 degrees can be a risk due to wind speed, and power production trade-offs are insignificant).

14 SOLAR ENERGY↗
DOE OSTI2024

Tough Break: Many Factors Make Glass Breakage More Likely

We have seen cases of glass in PV modules breaking differently, and more often, than it did five years ago. There have been many changes to PV module design and materials in that time. But there is probably no single change that is responsible for the problem. Here we summarize the current thinking on PV glass breakage in utility-scale power plants. We share insights from multiple still-running projects at NREL.

14 SOLAR ENERGY↗
DOE OSTI2025

Vulcan Test Platform: Demonstrating the Data Center as a Flexible Grid Asset

Explosive data center demand is outpacing grid infrastructure development. AI workloads and hyperscale cloud growth are creating unprecedented power requirements, while traditional grid expansion faces multi-year development timelines, regulatory hurdles, and decarbonization challenges. Sidewalk Infrastructure Partners recognized this impending crisis years ago and founded Verrus to develop an innovative solution: data centers that function as grid assets rather than passive loads. The Verrus approach integrates proprietary grid-aware controls with battery energy storage systems (BESS) in a medium-voltage architecture that delivers three critical capabilities: Fast-responding demand flexibility that can service requests from the utility within 10 seconds, Uninterrupted transition to islanded operation during grid disturbances, Continuous uptime assurance while maintaining all customer service level commitments Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), we validated these capabilities on Vulcan, a 70 MW utility-scale test platform powered by NREL's ARIES Virtual Emulation Environment. This deployment-ready technology has successfully demonstrated that Verrus data centers can deliver meaningful grid services while maintaining mission-critical reliability. This technical report outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can play a pivotal role in enhancing grid flexibility and reliability, without sacrificing service level guarantees.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2025

Solar and Battery Storage Permitting and Siting Requirements - Solar Prize Round 7 (CRADA Final Report)

The purpose of this project is to identify local zoning ordinances, state permitting requirements, federal regulatory bottlenecks throughout the development process, and the potential to use Large Language Models (LLM) and aggregate permitting and interconnection data for commercial and industrial (C&I), community, and utility-scale solar photovoltaic (PV) and battery storage projects.

14 SOLAR ENERGY↗
DOE OSTI2025

Market Analysis of Solar Photovoltaic Development Potential on Bureau of Land Management Land in Arizona

This report explores the magnitude of the potential buildout of new solar development on Bureau of Land Management (BLM) land in Arizona based on market conditions in 2023. The BLM currently has 18 solar energy zones (SEZs), including three in Arizona, where land has undergone preliminary reviews and is suitable for expedited environmental review and permitting for solar energy projects. The BLM also administers variance areas that are outside SEZs and may consider right-of-way (ROW) applications for utility-scale solar development on such variance lands. Within variance areas in Arizona, the BLM has further identified Renewable Energy Development Area (REDA) lands that are likely well suited to solar or wind development. The purpose of the analysis reported here is to explore the anticipated extent of new solar development on BLM land in the state by 2035.

14 SOLAR ENERGY↗
DOE OSTI2025

Techno-Economic Analysis of Compressed Air Energy Storage and Hydrogen Production from Variable Renewable Energy

This study presents the techno-economic analysis (TEA) results of integrating electrolysis hydrogen (H 2 ) production, compressed air energy storage (CAES), and H 2 -fired combustion turbines in a high variable renewable energy (VRE) market environment. The inconsistent nature of VRE creates challenges for power producers in maintaining a stable electrical grid as it is increasingly utilized. The mission of the National Energy Technology Laboratory (NETL) is driving innovation and delivering energy solutions, and a multiangle approach involving H 2 production, energy storage, and next-level H 2 -fired combustion turbine generator (CTG) technologies could provide one solution for the nation’s growing electrical grid issues with increasing VRE sources. The H 2 production and CAES concept were investigated due to its ability to provide utility-scale H 2 -fueled power generation with large-scale energy storage capabilities. Two facilities with CAES and natural gas-fired CTGs (in McIntosh, Alabama, and Huntorf, Germany) have been operating for decades. In contrast, this study investigates the potential to replace the natural gas fuel with H 2 fuel. This concept has been publicly presented by both Siemens Energy and Bechtel Global Engineering, Construction & Project Management (Bechtel) at two different power generating levels. The CAES and air expansion/combustion turbine power generation in this study are primarily based on the Siemens Energy system (Bailie, Aug. 10-11, 2021) (Scheller, Feb. 21, 2023). The inclusion of a H 2 turboexpander generator is from Bechtel (Gülen, Sep. 6, 2022). A block flow diagram of the proposed process is illustrated in Exhibit ES-1.

08 HYDROGEN↗
DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗
DOE OSTI2026

Knowledge-Based Hazardous Waste Determinations for Solar Photovoltaic (PV) Modules: A Foundational Study

This report explores using "generator knowledge" to determine whether a solar photovoltaic (PV) module must be managed as hazardous waste prior to recycling or landfilling. Generator knowledge is a legal term and existing regulatory pathway for making a hazardous waste determination that has been used by other industries but is a relatively unknown option to the PV industry. In the United States, a hazardous waste determination often acts as a pre-requisite to recycle or landfill a PV module. The results of the hazardous waste determination dictate whether the PV module must be managed as hazardous waste or nonhazardous solid waste. Managing a PV module as hazardous waste requires compliance with stringent U.S. federal and state hazardous waste law. In addition to increased management costs, which can be ten times higher, legal liability for PV modules regulated as hazardous waste is also heightened with both civil and criminal penalties for noncompliance which includes making an inaccurate or faulty hazardous waste determination. The most common reason a PV module would be regulated as hazardous is if it contains a regulated metal in an amount that equals or exceeds the toxicity characteristic limits. To determine whether a PV module exhibits a hazardous characteristic, the regulated person/entity must "apply knowledge...in light of the materials and processes used." In the absence of adequate knowledge to determine whether the PV module is hazardous, it must be tested using Test Method 1311 Toxicity Characteristic Leaching Procedure (TCLP) or an equivalent EPA-approved method. Although TCLP is the predominant method used to today to make a hazardous waste determination for PV modules, evidence from this study concludes it is not practical to TCLP test every PV module even in a single utility-scale installation, and a scalable solution is needed. This study finds that knowledge-based hazardous waste determinations may allow a regulated person/entity to make a hazardous waste determination for more than one PV module at one time - making this regulatory pathway a potential scalable solution. Through legal analysis and interviews with 44 experts, the authors explore what it means to make an accurate knowledge-based hazardous determination for PV modules considering sources and forms of information as well as potential limitations. The work aims to provide a foundation for building consensus on whether knowledge-based hazardous determinations are a viable, scalable industry approach for solar.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗