Calibration of selected pyranometers and satellite derived solar radiation in Puerto Rico

Harmsen, Eric W.; Cruz, Pedro Tosado; Mecikalski, John R.

doi:10.1504/ijret.2014.059660

Cited by 13 publications

(12 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other methods have been proposed in the literature (Bender et al 2011;Harmsen, Tosado-Cruz, and Mecikalski 2014;and Thuman, Schnitzer, and Johnson 2012), and they are typically used by commercial data providers. This is because the short-term measured data set must first be subjected to a stringent quality-control procedure and then to more or less complex statistical methods.…”

Section: Extrapolating Short-term Measured Data Setsmentioning

confidence: 99%

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

Sengupta¹,

Kurtz²,

Dobos³

et al. 2015

151

121

View full text Add to dashboard Cite

ForewordThe first version of this handbook was developed in response to a growing need by the solar energy industry for a single document addressing the key aspects of solar resource characterization. The solar energy industry has developed rapidly throughout the last few years, and there have been significant enhancements in the body of knowledge in the areas of solar resource assessment and forecasting. Thus, this second version of the handbook was developed from the need to update and enhance the initial version and present the state of the art in a condensed form for all of its users.Although the first version of this handbook was developed by only researchers from the National Renewable Energy Laboratory, this version has additional contributions from an international group of experts primarily from the knowledge that has been gained through participation in the International Energy Agency's Solar Heating and Cooling Programme Task 36 and Task 46.As in the first version, this material was assembled by scientists and engineers who have many decades of combined experience in atmospheric science, radiometry, meteorological data processing, and renewable energy technology development.Readers are encouraged to provide feedback to the authors for future revisions and an expansion of the handbook's scope and content. iv This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. PrefaceAs the world looks for low-carbon sources of energy, solar power stands out as the single most abundant energy resource on Earth. Harnessing this energy is the challenge for this century. Photovoltaics, solar heating and cooling, and concentrating solar power (CSP) are primary forms of energy applications using sunlight. These solar energy systems use different technologies, collect different fractions of the solar resource, and have different siting requirements and production capabilities. Reliable information about the solar resource is required for every solar energy application. This holds true for small installations on a rooftop as well as for large solar power plants. However, solar resource information is of particular interest for large installations, because they require a substantial investment, sometimes exceeding $1 billion in construction costs. Before such a project is undertaken, the best possible information about the quality and reliability of the fuel source must be made available. That is, project developers need to have reliable data about the solar resource available at specific locations, including historic trends with seasonal, daily, hourly, and (preferably) subhourly variability to predict the daily and annual performance of a proposed power plant. Without this data, an accurate financial analysis is not possible.In September 2008, the U.S. Department of Energy (DOE) hosted a meeting of prominent CSP developers and stakeholders. One purpose was to identify areas in which the DOE's CSP program should focus its efforts to help the industry develop an...

show abstract

Section: Extrapolating Short-term Measured Data Setsmentioning

confidence: 99%

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

Sengupta¹,

Kurtz²,

Dobos³

et al. 2015

151

121

View full text Add to dashboard Cite

show abstract

“…Solar radiation is a critically important variable in the estimation of ET. Figures 2 and 3 show comparisons of the daily integrated solar radiation at the University of Puerto Rico (UPR) Fortuna Agricultural Experimental near Juana Diaz, PR, and the UPR-Mayaguez Campus (UPRM) in Mayaguez, PR, respectively [39]. The figures show a high degree of correlation between the remote sensing solar radiation and the measured solar radiation.…”

Section: Goesweb Model Accuracy and Validationmentioning

confidence: 98%

“…The coefficients of determination (r 2 ) for the UPRM and experimental station data were 0.88 and 0.83, respectively. (From [39]). Figure 4 shows a comparison of the ET o computed by the GOESWEB algorithm and from weather station data from the UPR Fortuna Agricultural Experiment Station, near Juana Diaz, PR.…”

Section: Goesweb Model Accuracy and Validationmentioning

confidence: 99%

See 1 more Smart Citation

The Use of Visible Geostationary Operational Meteorological Satellite Imagery in Mapping the Water Balance over Puerto Rico for Water Resource Management

Mecikalski¹,

Harmsen²

2019

Satellite Information Classification and Interpretation

View full text Add to dashboard Cite

A solar insolation satellite remote sensing product for Puerto Rico, the US Virgin Islands (USVI), Dominican Republic, Haiti, Jamaica, and Cuba became available in 2009 through a collaboration between the University of Puerto Rico-Mayagüez Campus and the University of Alabama in Huntsville. Solar insolation data are available at 1 km resolution for Puerto Rico and the USVI and 2 km resolution for the other islands, as derived from 500 m resolution GOES-16 visible imagery. The insolation data demonstrate the powerful utility of satellite-derived fields for water resource applications, specifically the routine production of potential and reference evapotranspiration. This chapter describes the theoretical background and technical approach for estimating components of the daily water and energy balance in Puerto Rico. Useful information can be obtained from the model, which benefits disaster and emergency management, agriculture, human health, ecology, coastal water management, and renewable energy development at the island scale.

show abstract

“…Thus, bias removal can be achieved by finding a correction factor between ground and satellite data [13]. For daily values of global irradiation calibration of satellite-derived data using recalibrated pyranometers are proposed in Puerto Rico [17]. A more sophisticated method is also proposed for correcting HelioClim-3 by representing the error of clearness index by sinusoid functions [18].…”

Section: Introductionmentioning

confidence: 99%

Correcting satellite derived DNI with systematic and seasonal deviations: Application to India

Polo

Martín²,

Vindel

2015

Renewable Energy

View full text Add to dashboard Cite

a b s t r a c tA simple method for correcting satellite-derived direct normal irradiance, with important deviations to the experimental data, is presented in this work and illustrated for the particular case of Rajasthan (India). Northwest India is expected to have a high level of solar radiation and it is an interesting area for solar concentrating power systems. However uncertainty in direct normal irradiance estimations from satellite may affect negatively to the bankability of solar plants. Direct normal irradiance have been estimated for a site in Rajasthan from satellite information for the period 2003 to 2011, and ground measurements during 2011 have been used to analyze the uncertainties and to develop a simple correction method. The original satellite estimations showed important deviations from the experimental values and high bias. A systematic underestimation of direct irradiance has been observed during the dryer seasons that could be attributed to an overestimation of the aerosol optical depth input to the model. These observations have allowed the design of a correction methodology. Unbiased new estimations of direct normal irradiance have been generated with this methodology with important reduction in the deviations and with an agreement in the distribution functions compared to the distribution function of the ground data.

show abstract

Calibration of selected pyranometers and satellite derived solar radiation in Puerto Rico

Cited by 13 publications

References 11 publications

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

The Use of Visible Geostationary Operational Meteorological Satellite Imagery in Mapping the Water Balance over Puerto Rico for Water Resource Management

Correcting satellite derived DNI with systematic and seasonal deviations: Application to India

Contact Info

Product

Resources

About