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Sengupta, Manajit

Publications and source records attributed to Sengupta, Manajit.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Numerical Computation of Clear-Sky Transmittance and Reflectance of Solar Radiation for the Modeling of PV System Performance

Modeling of photovoltaics (PV) system performance requires numerical computation of plane-of-array (POA) irradiances that are influenced by atmospheric absorption and scattering. Clear-sky transmittance and reflectance of diffuse irradiance are essential for the understanding of solar radiation related to multiple reflection between land surface and clouds. This study analytically solves the radiative transfer equation for clear-sky conditions and numerically computes the transmittance and reflectance of diffuse irradiance as functions of the optical thickness of the atmosphere. The computation will be implemented in all-sky radiative transfer models to improve their computational efficiency.

14 SOLAR ENERGY↗
DOE OSTI2020

The Case for Custom TMY's: Examples Using the NSRDB

A typical meteorological year (TMY) data set essentially represents an hourly compilation of median months constructed using multi-year datasets. Although TMY data sets are generated from irradiance data in the horizontal plane, they are used in photovoltaic (PV) modeling for systems inclined to various angles. This paper demonstrates that a POA TMY (plane of array TMY) generated by selecting median months from a multi-year POA irradiance timeseries dataset produces significantly different results than a POA TMY generated by transposing a TMY dataset constructed from horizontal data. In some months the differences can be more than 3%. These results point to the need for generating TMY's using POA irradiance timeseries representing the orientation at which PV panels will be deployed.

14 SOLAR ENERGY↗
DOE OSTI2020

Improved Field Evaluation of Reference Cell Using Spectral Measurements

Output from a reference solar cell mounted on a one-axis tracking surface is investigated using 350 nm to 1650 nm spectral irradiance measurements on selected days throughout the year. Comparisons are made to a Class-A pyranometer also mounted on the tracking surface. The ratio of the reference cell's measurements to reference pyranometer measurements exhibit systematic biases over the day and year. Most of this bias is linked to spectral, temperature, and angle-of-incident effects that differ for the reference cell and the pyranometer. The comparison is done for selected clear and totally cloudy days to determine the magnitude of the effects and to characterize they influence the measurements made with reference cells.

14 SOLAR ENERGY↗
DOE OSTI2020

Sensitivity Study for Forecasting Variables of WRF-Solar Using a Tangent Linear Approach

Integrating solar generation in recent years has highlighted the need for improved accuracy in predicting solar power. Confidence in solar power forecasting can be achieved by designing an ensemble that provides reliable probabilistic information for solar radiation with reduced uncertainty and error. Ideally, ensemble members are created through the optimized perturbation of the initial conditions in numerical weather prediction (NWP) models. Tangent linear models are capable of efficiently investigating the sensitivity of solar radiation to model input parameters because they do not require individual perturbation of each variable. This sensitivity study using tangent linear models provide us the capability to identify the right variables to perturb in an ensemble prediction system. In this study, we developed tangent linear models for WRF-Solar modules that directly impact the computation of solar radiation and the simulation of cloud formation and dissipation including the Fast All-sky Model for Solar Applications (FARMS), the Noah land surface model (LSM), the Thompson microphysics, the Mello-Yamada-Nakanishi-Niino (MYNN) boundary layer parameterization, and the Deng scheme for a shallow-convection parameterization. A sensitivity analysis was conducted under various scenarios based on satellite observations and model simulations from the National Solar Radiation Data Base (NSRDB) and WRF-Solar, respectively. Critical forecasting variables that are highly sensitive to the forecasting of global horizontal irradiance (GHI), direct normal irradiance (DNI), cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes were determined using the relevant WRF-Solar module. This study will be used as a guidance on future research leading to high-quality probabilistic solar forecasting. In this presentation, we discuss the validation of tangent linear approach for WRF-Solar modules and illustrate how the sensitivity results are valuable in the improvement of probabilistic solar prediction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integration of Total-Sky Imager Data with a Physics-Based Smart Persistence Model for Intra-Hour Forecasting of Solar Radiation

Short-term solar forecasting models based solely on global horizontal irradiance (GHI) measurements are often unable to discriminate the forecasting of the factors affecting GHI from those that can be precisely computed by atmospheric models. Our previous study introduced a Physics-based Smart Persistence model for Intra-hour forecasting of solar radiation (PSPI) that decomposed the forecasting of GHI into the computation of extraterrestrial solar radiation and solar zenith angle and the forecasting of cloud albedo and cloud fraction. The extraterrestrial solar radiation and solar zenith angle were accurately computed by the Solar Position Algorithm (SPA) developed at the National Renewable Energy Laboratory (NREL). A cloud retrieval technique was used to estimate cloud albedo and cloud fraction from surface-based observations of GHI. With the assumption of persistent cloud structures, the cloud albedo and cloud fraction were predicted for future time steps using a two-stream approximation and a 5-minute exponential weighted moving average, respectively. The model evaluation indicated the estimation and forecast of cloud fraction mostly contributed to the uncertainty of the PSPI though it overcame the persistence and smart persistence models in all forecast time horizons between 5 and 60 minutes. This study aims to enhance the PSPI by ingesting surface-based observations of cloud fraction from a total sky imager (TSI). The estimation and forecast of cloud albedo is correspondingly improved by utilizing the cloud fraction observations and thus leads to more accurate GHI forecast. Various time-series analysis methods are also investigated on the forecasting of cloud fraction and cloud albedo for further improving the GHI forecast. These improvements are valuable for many applications, such as forecasting energy use for buildings, grid operations, and ultimately bringing down the cost of solar energy.

14 SOLAR ENERGY↗
DOE OSTI2020

Results of Recent and Historical Comparisons Between Absolute Cavity Pyrgeometer (ACP), InfraRed Integrating Sphere (IRIS)

Results of seven comparisons between ACPs and IRISs. Difference between the longwave irradiance measured by the ACPs and IRISs versus the irradiance measured by the WISG. The longwave irradiance measured by the ACPs, IRISs, and AERI versus the irradiance measured by the WISG. Recommendations to establish the world reference for measuring the atmospheric longwave irradiance with traceability to the International System of Units (SI).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

PV Variability at the DeSoto Next Generation Solar Energy Center (Cooperative Research and Development Final Report, CRADA Number CRD-11-425)

In order to support the continued integration of utility-scale solar photovoltaic sites into the Florida transmission system and to further enhance our understanding of the effects of cloud-induced output variability on the site and transmission operations, participant elects to enter a Cooperative Research and Development Agreement (CRADA) with the National Renewable Energy Lab (NREL). Under this agreement, NREL will work with participant to instrument their PV plant in DeSoto county FL and obtain solar radiation and power output data. The Florida Power & Light's (FPL) DeSoto Next Generation Energy Center is the largest installed PV plant in the country (25 MW). Our goal is that this site be instrumented and used for research into PV variability and forecasting.

14 SOLAR ENERGY↗
DOE OSTI2019

Method and System for Accessing PV Resource Data from the NSRDB: Preprint

This study developed a capability to provide spectrally resolved solar resource data from the National Solar Radiation Database (NSRDB), effectively providing 20 years of half-hourly data for all of the United States at a 4-km by 4-km spatial resolution. These data are now available freely to users directly through a geographic information system-based web interface (https://nsrdb.nrel.gov) as well as through an application programming interface. Users of these data can conduct more accurate prefeasibility studies and assess multiple photovoltaic (PV) technologies. It is expected that widely used models such as PVSyst, the National Renewable Energy Laboratory's System Advisor Model (SAM), and First Solar-designed PlantPredict will develop the capabilities to use these spectral data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Application of the Clear-Sky Spectral Error for Radiometer Classification in ISO 9060: Preprint

A recent update of the ISO 9060 standard for the classification of solar radiometers introduces the use of the clear sky spectral error. The spectral error is the change in responsivity that may occur when the spectral distribution of the incident solar radiation differs from the spectral distribution present at the time of calibration. Spectral errors may occur if the radiometer does not have a completely uniform spectral responsivity. This use of the clear sky spectral error is a significant change compared to the previous version of the 9060 standard as now not only thermopile radiometers, but also photodiode radiometers are covered by the standard. We explain the method used to derive the spectral error and present spectral errors for several radiometers of different technologies. The results demonstrate that the new method is helpful to classify radiometers, distinguishing between different radiometer types and excluding inappropriate instruments from the classification as pyranometers and pyrheliometers. We recommend that the method is also used for WMO's radiometer classification which up to our knowledge is currently not fulfilled by any field pyrheliometer and many pyranometers on the market due to its demanding requirements for the spectral responsivity.

14 SOLAR ENERGY↗
DOE OSTI2019

The Impact of Plane-of-Array-Based TMYs on Solar Resource for PV Applications: Preprint

This study attempts to apprise stakeholders about the accurate use of a typical meteorological year (TMY) data set for decision-making that could potentially speed up the acceptance and deployment of projects and reduce risks to financiers and developers. A TMY data set represents hourly concatenation of 12 typical meteorological months constructed using multiyear data sets. Typically, TMY data sets are constructed under horizonal irradiance conditions that are then used in photovoltaic (PV) performance models for available energy calculations in a location after transposing the data to represent a desired plane-of-array (POA) orientation. In this study, we attempt to show that a POA TMY generated with corresponding POA irradiance time-series information produces significantly different results than a POA TMY generated by transposing a TMY data set. In some months, the differences can be more than 3% for irradiance and energy yield. These results point to the need for generating TMY data sets using POA irradiance time series representing the orientation at which PV panels will be deployed.

14 SOLAR ENERGY↗