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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measuring Irradiance for Bifacial PV Systems

The advent of bifacial PV systems drives new requirements for irradiance measurement at PV projects for monitoring and assessment purposes. While there are several approaches, there is still no uniform guidance for what irradiance parameters to measure and for the optimal selection and placement of irradiance sensors at bifacial arrays. Standards are emerging to address these topics but are not yet available. In this paper we review approaches to bifacial irradiance monitoring which are being discussed in the research literature and pursued in early systems, to provide a preliminary guide and framework for developers planning bifacial projects.

bifacial↗
DOE OSTI2019

Albedo Data for Bifacial PV Systems

At the September 2018 Bifacial PV Workshop in Lakewood, CO, a better understanding of albedo values and characteristics was identified as a key need by both the PV and financial communities to better estimate performance and to reduce risk of bifacial PV systems. To meet this need, the U.S. Department of Energy (DOE) has initiated work with the National Renewable Energy Laboratory (NREL) to provide the following: A multi-year database of measured and quality assessed albedo values with temporal resolution of one hour or less for numerous locations and types of ground surfaces. Site metadata for each location (Pictures, instruments and calibration history, soil and vegetation types, etc.) Site albedo statistics for each location (diurnal profiles, monthly and annual means, interannual variability) Analysis of the spectral mismatch for bifacial PV modules of the ground-reflected radiation for anticipated deployment surfaces (using both measured and modeled spectral albedo data). Comparisons of the measured albedos with available satellite-derived MODIS albedo products to validate the MODIS albedo products for estimating bifacial PV system performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Measuring Irradiance for Bifacial PV Systems: Preprint

The advent of bifacial PV systems drives new requirements for irradiance measurement at PV projects for monitoring and assessment purposes. While there are several approaches, there is still no uniform guidance for what irradiance parameters to measure and for the optimal selection and placement of irradiance sensors at bifacial arrays. Standards are emerging to address these topics but are not yet available. In this paper we review approaches to bifacial irradiance monitoring which are being discussed in the research literature and pursued in early systems, to provide a preliminary guide and framework for developers planning bifacial projects.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Comparative Analysis of Rear Irradiance Modeling Methods for Bifacial PV Systems on Single-Axis Trackers Under Varying Albedo Conditions

This study compares three rear-side irradiance modeling methods for bifacial PV systems on single-axis trackers: (i) the 2D View Factor (VF) model in PVsyst(R), (ii) the open-source PVFactors VF model, and (iii) the Ray Tracing (RT) technique using bifacial_radiance. Simulations were benchmarked against field measurements from a pilot PV plant with rear-side sensors at the torque tube height. Results show that all models underestimated the non-uniformity of rear irradiance along the module length and overestimated the total rear irradiance incident on the module. However, since bifacial gain represents only a fraction of the system's total energy, the resulting energy yield differences among methods remained within +- 2 % of measured values, which is typical for such simulations. While the overall energy impact is limited, this study characterizes the specific limitations of each modeling approach, supporting further improvements in bifacial PV performance assessment methods.

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 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↗
DOE OSTI2019

Bifacial PV System Mismatch Loss Estimation and Parameterization: Preprint

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 scenarios including horizontal single-axis tracking (HSAT) and 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 HSAT systems and 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↗
DOE OSTI2021

Albedo Data Sets for Bifacial PV Systems

For use by the PV and financial communities to better estimate the performance and to reduce the risk of bifacial PV systems, data sets of ground albedo and associated meteorological data were developed by using existing measurement network data and data contributed by the PV industry. The data sets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Complete information is presented in a user's guide and data are available for download from NREL's DuraMAT website.

albedo↗
DOE OSTI2020

Albedo Data for Bifacial PV Systems Update

For use by the PV and financial communities to better estimate the performance and to reduce the risk of bifacial PV systems, data sets of ground albedo and associated meteorological data were developed by using existing measurement network data and data contributed by the PV industry. The data sets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Complete information is presented in a user’s guide and data are available for download from NREL’s DuraMAT website.

albedo↗
DOE OSTI2020

Albedo Data Sets for Bifacial PV Systems: Preprint

For use by the PV and financial communities to better estimate the performance and to reduce the risk of bifacial PV systems, data sets of ground albedo and associated meteorological data were developed by using existing measurement network data and data contributed by the PV industry. The data sets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Complete information is presented in a user’s guide and data are available for download from NREL’s DuraMAT website.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Optimizing Bifacial PV Systems (Q3 FY2020 Project Report)

This project has four main technical objectives. Develop and improve bifacial performance models by adding the capability to evaluate electrical behavior and performance of bifacial modules and arrays under realistic field conditions including irradiance variability caused by racking, module frame, and position in the array. Instrument and monitor performance of fielded bifacial systems to validate performance models and to measure, analyze and publish on bifacial energy gain. These should include both research and commercial bifacial systems and cover a variety of deployment applications. Evaluate optimal bifacial system designs using simulations leveraging high performance computing, and also using full sized and miniaturized experimental field deployments. Establish and contribute to international test standards for bifacial system performance, testing, and safety, and work with the community to establish installation and siting best practices.

14 SOLAR ENERGY↗
DOE OSTI2020

bifacial_radiance: a python package for modeling bifacial solar photovoltaic systems

bifacial_radiance is a national-laboratory-developed, community-supported, open-source toolkit that provides a set of functions and classes for simulating the performance of bifacial photovoltaic (PV) systems. (Bifacial PV modules collect light on the front as well as the rear side.) bifacial_radiance automates calculations of PV system layout and performance to use along with the popular ray-tracing software tool RADIANCE (Ward, 1994). Specific algorithms include design and layout of PV modules, reflective ground surfaces, shading obstructions, and irradiance calculations throughout the system, among others. bifacial_radiance is an important component of a growing ecosystem of open-source tools for solar energy (William F Holmgren et al., 2018).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

2021 Q1 Project Report: Optimized Bifacial PV Systems (Q1 FY2021 Project Report)

This project has four main technical objectives: 1) Develop and improve bifacial performance models by adding the capability to evaluate electrical behavior and performance of bifacial modules and arrays under realistic field conditions including irradiance variability caused by racking, module frame, and position in the array. 2) Instrument and monitor performance of fielded bifacial systems to validate performance models and to measure, analyze and publish on bifacial energy gain. These should include both research and commercial bifacial systems and cover a variety of deployment applications. 3) Evaluate optimal bifacial system designs using simulations leveraging high-performance computing, and also using full sized and miniaturized experimental field deployments. 4) Establish and contribute to international test standards for bifacial system performance, testing, and safety, and work with the community to establish installation and siting best practices.

42 ENGINEERING↗
DOE OSTI2021

Albedo Data Sets for Bifacial PV Systems

Solar radiation data for seven SURFRAD stations for the period 1996-2018 show an increase in irradiance under clear skies over the period, but the increase was not constant and shorter periods may have even experienced decreases in irradiance. A popular implementation of a clear sky model provided modeled irradiances for comparison with the SURFRAD data under conditions screened for clear skies. The use of the clear sky model, which did not consider year-to-year variances in atmospheric turbidity, was found problematic for resolving small changes in irradiance important for determining PV system degradation over three or five years, but less problematic for a period of ten years.

41 EE - Solar Energy Technologies Office (EE-4S)↗