Engineering topics

Peterson, Josh

Publications and source records attributed to Peterson, Josh.

12 records

DOE OSTI2024

Equating Reference Cell and Broadband Pyranometer Data

An adjustment algorithm has been developed for broadband Class-A pyranometers, to modify the pyranometer data such that it more closely matches that of silicon-based reference cells. The adjustment algorithm uses modeled clear-sky spectral data as one of its inputs. The adjustment also uses a reference cell angle of incidence modifier. A comparison between the pyranometer and the reference cells is performed with and without the adjustment applied. The adjustment aligns the pyranometer and reference cell data to within +-2 % under clear skies when the zenith angle is less than 70 degrees .

incident angle modifier↗

DOE OSTI2023

Modeling Reference Cell Performance Using Measured and Modeled Spectral Data

The performance of several silicon-based reference cells is examined under clear skies on a horizontal and two-axis tracking surface during the winter of 2022. The ratio of the calculated reference cell output to the measured reference cell output is examined. For each reference cell, when using the measured spectral data, the ratio of the estimated to measured output varies by less than +/-0.6% at the P95 level. The analysis was also done using modeled spectral values obtained from the Bird spectrl2 model. The ratio between the estimated reference cell output using the modeled spectral values to the measured reference cell output varies by +/-1.1% at the P95 level.

angle of incidence↗

DOE OSTI2022

Reference Cell Performance and Modeling on a One-Axis Tracking Surface: Preprint

Performance of five silicon-based reference cells is examined on a single-axis tracking surface. The reference cells' output are modeled using one-minute sampled spectral irradiance and reference cell temperature measurements. The model also incorporates spectral responsivity data for the reference cell. The transmission of light through the glazing multiplies the sum over all appropriate wavelengths of temperature adjusted reference cell responsivity times the measured spectral irradiance. Modeled reference cell output is compared with measured reference cell output under clear sky and totally cloudy sky conditions. For each reference cell the ratio of modeled to measured output varies by less than 2% over the year.

modeling↗

DOE OSTI2022

Evaluation of Solar Reference Cells on a Two-Axis Tracker Using Spectral Measurements

A simple model calculating the performance of an IMT solar reference cell is proposed and tested under clear sky periods. One-minute data from EKO spectroradiometers collocated with an IMT reference cell are used for the analysis. Data are obtained at the NREL Solar Radiation Research Laboratory in Golden, Colorado and the UO Solar Radiation Monitoring Laboratory in Eugene, Oregon. The model is also applied and evaluated under cloudy conditions. A match of better than 1% is found between calculated clear sky values and IMT measurements for July, 2020. One- minute cloudy sky comparisons show a much larger variation, but when averaged over one hour, a standard deviation of 4% between the calculated and measured values is found.

atmospheric radiation↗

DOE OSTI2021

Influence of Diffuse and Ground-Reflected Irradiance on the Spectral Modeling of Solar Reference Cells

Thermal Energy Storage (TES) is a key component for solar thermal applications to bridge the gap between the demand for thermal energy and the supply of solar energy, whose availability depends on the time of day and season. Thus, cost-effective packed-bed thermal containers filled with a solid storage medium have been proposed for high-temperature sensible heat storage as materials are abundant and relatively cheap. Thus, it is necessary to investigate their performance and temperature profiles during the charge-discharge cycle. Several models are available for this purpose. Typically, the more detailed a model, the greater the computational effort required to solve it, and hence a time-efficient model is needed to prevent excessively long computation times for long-term analysis. At the more basic level, the common Hughes E-NTU model and the less realistic simplified Infinite-NTU model are very important for their less time and computational effort. In this paper, the appropriateness of employing the Infinite-NTU model was evaluated to investigate the performance of a typical and scalable rock-bed TES as a case study. The results presented provide a methodology to quickly test the validity of the model and predict the temperature profile for the case under study. Accordingly, such simple charge-discharge cycle thermal performance predictions are important to plan, design, and rapidly deploy a reliable and economical solar thermal system for the supply of valuable heat to high-temperature demanding applications of power generation and industrial processes as part of a rapid shift towards non-polluting renewable energy. Keywords: Solar Thermal, TES, Packed-bed, NTU model, Temperature profile

PV modeling↗

DOE OSTI2021

Improved field evaluation of reference cells using spectral measurements

Output from an IMT reference solar cell mounted on a one-axis tracking surface is investigated using spectral measurements covering the 350–1650 nm range for selected days throughout the year. Comparisons are made to a Class-A pyranometer also mounted on the one-axis tracking surface. Systematic biases over the day and year are observed in the ratio of the reference cell’s measurements to reference pyranometer measurements. This systematic bias is associated with the spectral, temperature, and angle-of-incident effects that differ between the reference cell and the reference pyranometer. The comparison is done for selected clear and totally cloudy days to determine the magnitude of the effects and to characterize the influence of these effects on the reference cell measurements. A model to calculate the reference cell output based on spectral irradiance and reference cell temperature is introduced.

14 SOLAR ENERGY↗

DOE OSTI2021

Using Spectral Measurements to Characterize Solar Reference Cells on a Two-Axis Tracker

A study is commencing relating the spectral responsivity of reference cells in the field to changing spectral distribution during the day. Initial results indicate that measurements of the incident spectral distribution can be used to match results of reference cell measurements on a two-axis tracker with a standard deviation of ±0.25% under clear-sky conditions. Initial results are provided. As more data are obtained covering a variety of field conditions and locations, the robustness of these results will be tested. The website https://midcdmz.nrel.gov/apps/sitehome.pl?site=PVRES contains the data generated by this project.

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

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 OSTI2019

Removing Biases from Rotating Shadowband Radiometers

Three types of biases are examined for a Rotating Shadowband Radiometer (RSR): temperature bias, spectral bias, and deviation from a Lambertian cosine response. A step by step method is presented to illustrate how to use this information to develop a model for adjustment algorithms for a RSR. Comparisons are made with a RSR adjusted using the model and measure direct normal, diffuse, and global irradiance.

14 SOLAR ENERGY↗

DOE OSTI2019

Improved Field Evaluation of Reference Cell Using Spectral Measurements: Preprint

Spectral irradiance measurements as opposed to modeled spectral values are used to evaluate the effects of changing spectral distributions on the output of reference solar cells. Comparisons are made on a one-axis tracking surface to a Class A pyranometer. The ratio of the reference cells to reference pyranometers exhibit a bias over the day. Spectral and temperature modeling reproduce most but not all changes in the ratio over the day. Sources for this difference in modeling and performance of the reference cells are examined.

14 SOLAR ENERGY↗

DOE OSTI2019

Removing Biases from Rotating Shadowband Radiometers: Preprint

Three types of biases are examined for a rotating shadowband radiometer (RSR): temperature bias, spectral bias, and deviation from a Lambertian cosine response. A step-by-step method is presented to illustrate how to use this information to develop a model for adjustment algorithms for a RSR. Comparisons are made with a RSR adjusted using the model and measure direct normal, diffuse, and global irradiance.

14 SOLAR ENERGY↗

DOE OSTI2018

Evaluation of Photodiode-Based Pyranometers and Reference Solar Cells on a Two-Axis Tracking System

The performance of photodiode-based pyranometers and reference solar cells are examined on a two-axis tracker surface. This is the third in a series of papers examining the performance of photodiode-based pyranometers and reference solar cells on fixed and tracking surfaces. Because the instruments are oriented normally to the incident radiation, angle-of-incidence effects are minimized. By removing the angle-of-incidence effects inherent in earlier studies, the change in the sensor's clear sky responsivity can be more clearly identified. It was found that the photodiode-based pyranometers demonstrate a larger change in responsivity than the reference solar cells. Spectral measurements are recommended to verify the cause of this difference.

14 SOLAR ENERGY↗