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DOE OSTI2024

Introducing the Baseline Performance Reference (BPR) for Irradiance in PV System Applications

Photovoltaic (PV) reference cells, modules, and arrays respond in a complex manner to the many variables that define their operating environment. PV reference cells for irradiance measurement have similarities but also differences to operational PV modules. For this reason, a more neutral and a well-defined generic PV reference cell is needed, whose characteristics are close enough to most operational PV devices to make stable performance indicators possible but whose characteristics are not necessarily identical to any of them. This poster describes a new well-defined reference quantity for outdoor PV measurements, called the baseline performance reference (BPR).

baseline performance reference↗

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 OSTI2022

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

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

14 SOLAR ENERGY↗

DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗

DOE OSTI2018

PV System Component Fault and Failure Compilation and Analysis.

This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.

14 SOLAR ENERGY↗

DOE OSTI2014

PV System Energy Evaluation Method (Presentation)

This presentation describes a comparison of the "predicted" energy (based on historical weather data) with the "expected" energy (based on the measured weather data) to determine whether a PV system is performing as modeled in order to verify the accuracy of a model. A key factor in defining this energy test is determining the test boundary so that weather variations are not inadvertently included in what is considered to be PV system performance.

14 SOLAR ENERGY↗

DOE OSTI2021

Methods for Evaluating DC Arc Incident Energy in PV Systems: Preprint

Renewable energy systems continue to be one of the fastest growing segments of the energy industry. This paper focuses on the understanding of how photovoltaic (PV) technology behaves under dc arc conditions. Emphasis is placed on the electrical safety aspect of DC arc flash incident energy evaluation. Because of the fast proliferation of PV systems and the lack of formal equivalent calculation guidelines such as IEEE 1584 for AC systems, it has been necessary to rely on different equations and models presented by various researchers over the last few years. This paper discusses the behavior of PV systems under arc conditions and presents the results of available methods to estimate the dc arc flash incident energy. This paper provides a comparative analysis of a proposed arc-flash incident energy calculation method against different laboratory tests including those performed by NREL. Detailed explanations are provided regarding the effect of PV module I-V and P-V curves under arcing conditions. Examples of the application of the proposed calculation method to the test measurements are included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

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

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

14 SOLAR ENERGY↗

DOE OSTI2015

Performance Modeling and Testing of Distributed Electronics in PV Systems; NREL (National Renewable Energy Laboratory)

Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order to give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses with and without distributed power electronics, along with experimental validation results. Computer modeling is able to predict the performance of distributed power electronics (microinverters, power optimizers) in PV systems. However, details about partial shade and other mismatch must be known in order to give the model accurate information to go on. This talk will describe recent updates in NREL’s System Advisor Model program to model partial shading losses.

14 SOLAR ENERGY↗

DOE OSTI2024

PV Modules Temperature Variation and Patterns in Medium and Utility-Scale Floating PV Systems

This paper presents the preliminary results and findings of the four operational Floating PV systems across the USA. At each site, temperature of five PV modules located at North-West, North-East, Middle, South-West, and, South-East have been monitored through the Resistant Temperature Detector (RTD) sensors. Three RTDs were attached to each PV module on the rear-side along the diagonal at top, middle and bottom cells. The preliminary results reveal wide temperature differences among the inter and intra PV modules. Besides this, wave pattern temperatures were observed in a few PV modules. The final results, findings, and, factors responsible will be investigated during the next few months.

array↗

DOE OSTI2020

Observations of PV Systems Post-Hurricane

NREL's observations of post-hurricane photovoltaic (PV) systems were shared with PV reliability researchers during the Photovoltaic Reliability Workshop held in Lakewood, Colorado the week of February 26, 2018. NREL hosts an annual Photovoltaic Reliability Workshop (PVRW) so that solar technology experts can share information leading to the improvement of PV module reliability. Such improvement reduces the cost of solar electricity and promotes investor confidence in the technology - both critical goals for moving PV technologies deeper into the electricity marketplace. This presentation is intended to share real world examples of PV survivability during and after Hurricanes Irma and Maria in 2017.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Techno-economic assessment of residential PV system tariff policies in Jordan

This study assesses the economic and technical performance of four energy policy scenarios for Jordan's residential photovoltaic (PV) systems: net metering, net billing, zero-export with battery storage, and sell-all-buy-all. With the recent introduction of time-of-use (TOU) tariffs and policies addressing the “duck curve” effect, the research focuses on optimizing PV system sizing across different regulatory frameworks. A detailed techno-economic analysis evaluates these scenarios based on energy production, cost savings, payback periods, and energy self-sufficiency. The findings indicate that net metering and net billing offer the highest cost savings and the shortest payback periods (∼3 years). While the zero-export strategy with battery storage enhances energy self-sufficiency by up to 70%, it requires a higher upfront investment. The sell-all-buy-all scenario supports larger system sizes, achieving a low levelized cost of electricity (0.0696 USD/kWh) and a net present value of 619 USD. Additionally, the study identifies a critical feed-in tariff threshold of 0.055 USD/kWh, at which net billing becomes as financially attractive as net metering. Here, these insights offer valuable recommendations for policymakers to optimize net billing rates and TOU tariffs, promoting the expansion of Jordan's renewable energy sector.

Battery storage↗

DOE OSTI2015

PV Systems Reliability Final Technical Report.

The continued exponential growth of photovoltaic technologies paves a path to a solar-powered world, but requires continued progress toward low-cost, high-reliability, high-performance photovoltaic (PV) systems. High reliability is an essential element in achieving low-cost solar electricity by reducing operation and maintenance (O&M) costs and extending system lifetime and availability, but these attributes are difficult to verify at the time of installation. Utilities, financiers, homeowners, and planners are demanding this information in order to evaluate their financial risk as a prerequisite to large investments. Reliability research and development (R&D) is needed to build market confidence by improving product reliability and by improving predictions of system availability, O&M cost, and lifetime. This project is focused on understanding, predicting, and improving the reliability of PV systems. The two areas being pursued include PV arc-fault and ground fault issues, and inverter reliability.

14 SOLAR ENERGY↗

DOE OSTI2023

The Baseline Performance Reference for Irradiance in PV System Applications

This report proposes the definition of a new baseline performance reference (BPR). The definition goes beyond existing standards pertaining to photovoltaic (PV) reference cells and devices to define the response under all possible operating conditions in the field. Field evaluations using BPR devices will be more sensitive to performance anomalies than pyranometers because they track PV system power output more closely. At the same time, they will be able to detect a broader range of performance anomalies than traditional matched reference devices, which might have matching defects. The BPR definition also opens the door to new practices in resource assessment and yield prediction. Solar resource data can be collected or modeled and validated directly as BPR irradiance, and PV system simulations based on BPR irradiance need fewer assumptions and less processing to obtain the effective irradiance on modules. As a result, lower uncertainty in yield assessments can be expected.

14 SOLAR ENERGY↗

DOE OSTI2019

Bifacial PV System Performance: Separating Fact from Fiction

The performance of bifacial PV systems depends greatly on the installed conditions. Previous simulations and results have shown very high bifacial gain improvement, but this may not be the case for all conditions, particularly for large-scale systems with self-shading, lower-cost PV modules (PERC) which might have lower bifaciality coefficient, and field deployments over natural ground cover. But not to worry! Financial models indicate that even with these lower performance conditions, and with bifacial gain of 4%-9%, bifacial modules can still provide improved LCOE.

14 SOLAR ENERGY↗

DOE OSTI2019

Bifacial PV System Mismatch Loss Estimation

Nonuniform rear-irradiance on bifacial PV systems can cause additional mismatch loss, which may not be appropriately captured in PV energy production estimates and software. A simplified empirical relationship is presented that links the spatial variation of irradiance (to the resulting mismatch loss factor).

14 SOLAR ENERGY↗

DOE OSTI2023

De-Risking Large-Scale PV Systems Through Data Analytics

Large-scale photovoltaic system performance analysis is being conducted within the US Department of Energy's-sponsored PV Fleet Performance Data Initiative. This collaboration with commercial PV system owners collects and evaluates PV field performance data, and provides reports on aggregated results. Drawing on over 2200 sites across the US and over 24,000 separate PV inverters we have collected in excess of 8.3 gigawatts (GW) of performance data, representing 6-7% of the entire US installed PV capacity. A mixture of utility-scale and large commercial systems are represented, averaging 4.1 megawatts (MW) in size and 5 years in age. Initial results show average system degradation rates at -0.75% / year, which is slightly higher than historically reported module-level values of -0.5%/year. We also found that the availability of systems averaged 97.7%, which is lower than the typical 99% uptime assumed by many project economic forecasts. Given these results, we compared monthly performance with expected production values, based on satellite weather data and a simple PVWatts performance model. We found that systems were performing within 10% of monthly expectation over 90% of the time, with a fleet average vs expected monthly value of 0.994. We also evaluated the impact of extreme weather events on system performance, and found a range of short-term and longer-term performance effects ranging from grid outage, system downtime, module damage and accelerated long-term degradation rate.

analysis↗

DOE OSTI2019

Bifacial PV System Mismatch Loss Estimation & Parameterization

Non-uniform irradiance on the rear-side of bifacial PV systems can cause additional mismatch loss which may not be appropriately captured in PV energy production estimates and software. We have evaluated several rooftop mounted systems over high albedo reflective roofs. Mismatch losses of up to 2% annual loss for very close-mounted (0.15 m) rooftop systems were found, but losses for high ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically the mean absolute difference of irradiance) to the resulting mismatch loss factor, with a R2 fit better than 0.985. This approximate relationship has been validated by experiments on mismatched PV modules, and provides a basis for fast estimation of bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM.

14 SOLAR ENERGY↗