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PV Fleet Performance Data Initiative Final Technical Report (FTR)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. This project will leverage data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Please see our list of public reports at https://www.nrel.gov/pv/fleet-performance-data-initiative.html. Objective 1: Support the global PV industry with scalable, robust data analysis tools that reduce the uncertainty of PV system performance and loss calculation. Objective 2: Reduce perceived risk arising from degradation rate, soiling loss, and system availability by publishing detailed statistics on U.S. fleet performance. Objective 3: Highlight factors leading to system underperformance including module type, climate, mounting configuration, etc. Objective 4: Enable continued high system performance in modern PV systems, as turnover and advances in technology bring new suppliers and high-efficiency modules into the market.

14 SOLAR ENERGY↗

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

Operations, maintenance, and cost considerations for PV+Storage in the United States

Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.

14 SOLAR ENERGY↗

Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States (2023 Edition)

Estimates of the potential of renewable energy are essential for understanding how we can decarbonize our electric grid and economy. They provide key data for policymakers, land managers, and energy modelers by defining the quantity, quality, and cost of renewable resources. However, estimating renewable energy potential is challenging and requires frequent updates because of rapid advances in technology, cost reductions, and uncertainty about developable land that are due to social, regulatory, and environmental factors. Additionally, the complex processes involved in renewable energy development require regular reviews of methods and assumptions, which can also impact our understanding of renewable potential. In this, the 2023 edition of this annual report, we present new estimates of the technical potential for land-based wind and solar photovoltaics (PV) for the contiguous United States (CONUS). We also provide cost estimates for the available resources, presenting representative supply curves that can be used in downstream modeling and analysis. Additionally, we introduce the new methodologies used to estimate wind capacity, wind energy losses, transmission cost and representation, updated technology cost and design, and scenarios of siting constraints designed to help bound the uncertainty of renewable potential.

14 SOLAR ENERGY↗

Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Finally, scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances.

14 SOLAR ENERGY↗

Challenges and Solutions for Real-Time Phasor Modeling of Large-scale Distribution Network with High PV Penetration

The conversion process of a practical large-scale feeder data from a quasi-static time series (OpenDSS) model into a real-time phasor model (ePHASORSIM in Opal-RT) is discussed in the paper. The process is implemented using an open source Python software. Previous reported implementations for the conversion process lead to several errors when applied to a larger-scale system such as the one considered here. Hence in this work, we describe the common issues in this conversion and propose a customized solution to enhance the efficiency of the conversion and reduce the complexity in the process. A quantitative validation of the enhanced conversion process is presented in this work using an actual high PV penetration feeder model that consists of 2230 buses, and using actual load and PV profile data. After a detailed analysis, this customized conversion software will be made available as an open source tool and is expected to be helpful for researchers who want to pursue a similar conversion. Solutions to various observed issues such as identifying the lines due to islanded network, representation of full impedance model of transformer/lines as sequential models, complexity in the representation of single phase buses/lines as three phase buses/lines to make it compatible with the simulator platform are discussed. Comparison of power flow and time series simulation results obtained from both OpenDSS and ePHASORsim models show very low errors, validating the accuracy of the proposed conversion process.

14 SOLAR ENERGY↗

Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.

climate data↗

Distributed Energy Resource (DER) Reliability for Backup Electric Power Systems

Hospitals, emergency services, military bases, ports, airports, industries, commercial facilities, and others rely on backup power systems to provide electricity for their critical loads during grid outages. The purpose of this report it to provide accurate reliability information on commonly deployed distributed energy resources (DERs) to improve quantitative estimates for the reliability of these backup power systems during a grid outage. A backup power system consists of DERs, an electric distribution system with its associated switches and other devices, and mechanisms to control and manage the flow of electricity. Too often, facilities and campuses fail to properly quantify the reliability of their backup power systems. DERs are assumed to be 100% reliable, with the only concern being the availability of fuel. Such assumptions can lead to gross errors in the backup system's reliability estimates, particularly for long-duration outages. This report provides a set of estimates for reliability of emergency diesel generators (EDGs), natural gas prime generators and combined heat and power (CHP) prime movers, solar photovoltaics (PV), wind turbines, and Li-ion battery energy storage systems (BESS). The estimates are derived from empirical data when available and supplemented by modeling results when needed. These reliability estimates are for the DERs ability to provide power during a grid outage, ranging from an hour to 2 weeks.

14 SOLAR ENERGY↗

Automating Detection and Diagnosis of Faults, Failures, and Underperformance in PV Plants

The project developed hybrid physics-based and machine-learning methods for near-real-time detection of balance-of-system faults (e.g., string, combiner, and tracker outages) in utility-scale Photovoltaic plants, achieving over 50% true positive rates with under 10% false positives and significantly reducing engineering setup time. In the extended phase, the scope expanded to plant-level underperformance analysis and industry benchmarking through the SUPER.epri.com platform. SUPER standardizes data processing and performance metrics across more than 9 GWac and 120+ plants, enabling robust comparisons and insights into loss rates, inverter downtime, and capacity degradation.

14 SOLAR ENERGY↗

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↗

NREL's Tools for AgriPV Modeling

As part of the Tools and Apps for Agrivoltaics session, NREL presents their tools that have capabilities for modeling PV and agricultural dual use sites. These include the System Advisor Model (SAM), bifacial_radiance open-source raytracing tool, and a simplified agriPV calculator available in the InSPIRE website.

agriculture↗

Identifying Barriers to Solar and Storage Hybrids: Modeled vs. empirical wholesale market value and net-value for co-located solar + storage projects [Slides]

Large-scale (1MW+) co-located solar and battery storage projects are expanding rapidly in the United States, but their realized contribution to the bulk power system remains poorly understood because public project-level operating data are limited. The Lawrence Berkeley National Laboratory estimates the wholesale market value of 280 operational photovoltaic-plus-storage (PV+S) projects across the seven ISOs/RTOs and 19 additional balancing authorities, representing roughly 95% of the U.S. PV+S fleet in 2024. We model optimized hourly dispatch under energy, capacity, and ancillary-service market opportunities and compare the resulting value with standalone PV value, project-specific levelized cost estimates, and empirical operating or revenue data where available.

14 SOLAR ENERGY↗

A Circular Economy for Solar Photovoltaic System Materials: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As PV capacity increases, owners are also decommissioning older system assets. Estimates based on a 30-year lifetime assumption found that cumulative U.S. end-of-life (EoL) PV modules could total one million metric tons (Mt) by 2030 and up to 10 million Mt by 2050 (Weckend, Wade, and Heath 2016). Beyond maintenance replacements, early retirements that are due to efficiency upgrades and extreme weather, as well as PV deployment beyond earlier expectations, would increase these projections. PV system owners must evaluate equipment management options for used modules and system components retired during maintenance activities, refurbishment, repowering and system decommissioning. PV manufacturers must also evaluate material management options from customer returns, defects, and scrap. Management options for early retired and EoL PV system material include reuse, repair for reuse, recycling-based resource recovery, storage, and disposal. Disposal of PV system material increases the burden on landfill capacity, while reuse, repair for reuse, and recycling-based resource recovery (reuse/repair/recovery) options salvage valuable materials and provide secondary market opportunities and ancillary benefits (Weckend, Wade, and Heath 2016; EPA 2019c; SWEEP 2019). PV system owners may also decide store used modules and components as spares, or in the interim before a reuse or EoL management decision is made. Despite potential secondary market opportunities and the potential benefits associated with the repair/reuse/recovery of PV system material, anecdotal evidence suggests that in the United States decommissioned PV modules are stored, landfilled or otherwise disposed of (Salim et al. 2019; CPUC 2019b; DTSC 2019b; NREL 2019a). Some modules are being disposed of in municipal nonhazardous landfills and federally regulated hazardous treatment, storage, and disposal facilities, and others are being stored in warehouses until economically viable repair/reuse/recycling becomes available (CPUC 2019b; DTSC 2019b; NREL 2019a; Libby and Shaw 2018). As awareness of current practices grows, and the demand for critical PV module material increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for PV system materials. Circular economy principles attempt to transition from a "take-make-consume-dispose" linear economic system to a circular system that allows for the long life, and the reuse/repair/recovery of products and materials (Ellen MacArthur Foundation 2020). We begin this report by summarizing the drivers, barriers, and enablers to a circular economy for PV system materials in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the repair/reuse/recovery of PV materials, and potential civil and criminal liabilities associated with noncompliance. We then discuss state policies and initiatives in the United States that expressly address PV system decommissioning and repair/reuse/recovery of PV materials. We conclude by providing case studies of U.S. business models for the repair/reuse/recovery of PV system materials. Our results are based on legal and literature-based research and interviews with solar industry stakeholders, regulators, and policymakers.

14 SOLAR ENERGY↗

Modeling the PV System Level Economic Impact of PV Connector Failure Modes

Photovoltaic (PV) connectors must maintain mechanical integrity for over 25 years while operating under UV exposure, elevated temperature, and mechanical loading. Connector degradation increases with electrical resistance, leading to energy losses, unplanned downtime, and higher operation and maintenance (O&M) costs and in severe cases, safety risks from overhearing or arcing. Connector related failures remain among the most frequent causes of disruption in utility-scale PV (UPV) systems, yet their lifetime economic impacts are poorly quantified. This work presents a techno-economic analysis (TEA) framework that links identified connector failure modes to system level energy losses and lifetime cost impacts using identified resistance measurements and failure rates from 6,2761 PV connectors inspected. Connector failures increase system level O&M costs, raising LCOE by roughly 5%. Downtime driven availability losses dominate economic impact. Resistance-driven I2R and IV-curve losses are secondary, but remain non-negligible. Thermal damage, bend-radius violations, and loose connections drive the majority of LCOE uplift Improving connector reliability through better installation quality, inspection, and design can meaningfully reduce lost energy, O&M costs, and LCOE.

14 SOLAR ENERGY↗

bifiPV2020 Bifacial Workshop: A Technology Overview

The virtual bifiPV Workshop was held in July 2020 to provide the solar industry with a forum for sharing and discussing research into bifacial photovoltaic (PV) technology. This report outlines major insights from the workshop to give the reader an overview of the latest developments in bifacial PV technology worldwide, from the lab to the field. Citations are drawn from this workshop unless otherwise noted, with all proceedings available online at bifipvworkshop. com. Presentations for the bifiPV2020 Workshop focused on the following areas: bifacial power plant modeling and simulation, albedo improvements, the development of encapsulants, the durability and reliability of current bifacial technologies, performance comparisons between glass-glass and glass-transparent backsheet configurations, the future of passivated emitter and rear contact (PERC) solar cells, and the growing adoption of n-type solar cells. With 650 GW total PV installed worldwide and 1 TW to come very soon, PERC is now the standard PV cell type produced en masse. However, it is already reaching 23% efficiency, the upper limit for this type of technology. PV modules breaking the 0.5-kW barrier are starting to appear, and the costs of standard PERC technology are already below 0.2 USD/Wp. In 2019, five GW of bifacial PV were installed worldwide. In 2020, the majority of bifacial installations are expected to be located in the United States, China, and Middle East and North Africa (MENA) states. N-type bifacial technologies are becoming increasingly viable and have huge potential to dominate the market in the coming years. With bifacial technology mounted on horizontal single-axis trackers (HSAT), bids below 10 USD/MWh will soon be observed in the MENA region, and later in Chile and the United States. Factory audits and reliability testing can reduce field failures by helping buyers to select producers that follow rigorous quality assurance and quality control processes.

14 SOLAR ENERGY↗

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗

Temperature Coefficients of Perovskite Photovoltaics for Energy Yield Calculations

Temperature coefficients for maximum power (TPCE), open circuit voltage (VOC), and short circuit current (JSC) are standard specifications included in data sheets for any commercially available photovoltaic module. To date, there has been little work on determining the TPCE for perovskite photovoltaics (PV). We fabricate perovskite solar cells with a TPCE of -0.08 rel %/°C and then disentangle the temperature-dependent effects of the perovskite absorber, contact layers, and interfaces by comparing different device architectures and using drift-diffusion modeling. A main factor contributing to the small TPCE of perovskites is their low intrinsic carrier concentrations with respect to Si and GaAs, which can be explained by its wider band gap. In this work, we demonstrate that the unique increase in Eg with increasing temperatures seen for perovskites results in a reduction in JSC but positively influences VOC. The current limiting factors for the TPCE in perovskite PV are identified to originate from interfacial effects.

14 SOLAR ENERGY↗

Maximum Power Reference Tracking Algorithm for Power Curtailment of Photovoltaic Systems

This paper presents an algorithm for power curtailment of photovoltaic (PV) systems under fast solar irradiance intermittency. Based on the Perturb and Observe (P&O) technique, the method contains an adaptive gain that is compensated in real-time to account for moments of lower power availability. In addition, an accumulator is added to the calculation of the step size to reduce the overshoot caused by large irradiance swings. A testbed of a three-phase single-stage, 500 kVA PV system is developed on the OPAL-RT eMEGAsim real-time simulator. Field irradiance data and a regulation signal from PJM (RTO) are used to compare the performance of the proposed method with other techniques found in the literature. Results indicate an operation with smaller overshoot, less dc-link voltage oscillations, and improved power reference tracking capability.

Paduani, Victor↗