Internal Review Draft

Assessment of Solar Resources in thePhilippines

Task 7Bb ReportPhilippine Renewable Energy Project

Prepared and Submitted by:The National Renewable Energy Laboratory

Under Contract with the US Agency for InternationalDevelopmentOctober, 2000

Assessment of Solar Resources for the Philippines

Dave RennéPamela Gray-Hann

Ray GeorgeLiz Brady

1. Introduction

Accurate solar resource data is important for the proper sizing and life cycle cost analysisof solar photovoltaic technologies. Knowledge of the spatial distribution of the solarresource for various tilt angles will allow for more cost effective design and operation ofphotovoltaic systems for meeting small, distributed loads. The goal of this task is todevelop a solar assessment for the Philippines that incorporates and builds upon currentunderstanding of the spatial distribution of the resource. This assessment provides datathat developers and investors can use to help establish successful business activity in off-grid solar technologies in the Philippines.

Although solar resource assessments have been conducted for the Philippines, thesegenerally make use of ground-based measurements of the daily total number of hours ofsunshine duration. The updated assessment provided here combines existing groundmeasurement data collected in the Philippines with the output of NREL’s ClimatologicalSolar Radiation (CSR) Model. This model converts information on satellite- and surface-derived cloud cover data collected at a 40-km spatial resolution to estimates of themonthly average daily total global horizontal solar resource. This spatial resolution isgenerally much higher than the spacing of ground stations, and therefore allows for amore detailed analysis of the effects of microclimate variability on the solar resource, andprovides a more accurate interpolation of the solar resource between ground stations.

2. Overview of Existing Solar Data in the Philippines

2.1 PAGASA Solar Lab

Data files in electronic format were acquired from the PAGASA Solar Lab during April,1999. The data acquired are as follows:

Sunshine duration data for the following cities and dates:

Baguio City (#328), 1970-1983, 1984-1998.Quezon (Science Garden) (#430), 1970-1987, 1988-1998.Tacloban (#550), 1971-1988, 1995 (missing: July, August 1986, all months for 1989-1991).Cagayan de Oro (#748), 1982-1995 (missing: April, May 1985; Sept. 1986; Feb. 1988;July 1989).

Puerto Princesa (#618), 1984-1997 (missing: January 1985, April, May 1988). Tuquegarao (#233), 1975-1997 (missing: Feb., May – Dec. 1985, all months for 1986-1987, Jan. – Aug. 1988, Feb. 1991). Catarman (#546), 1970-1986, 1987-1995 Laoag (#223), 1970-1985, 1986-1995 (missing: March, April 1985; May – August1988). Victoria's Milling Corporation (#618c), 1971-1982, 1983-1995 (missing: Sept., Oct.1987; Jan. 1988, April, May, 1991).

Global Horizontal data for the following cities and dates:

Victoria's Milling Corporation, 1984-1995 Quezon, 1972-1989, 1994-1996 (also known as Science Garden)

Each of the stations (except Catarman, Baguio, and Cagayan de Oro) with the sunshinerecorder data also have global horizontal measurements, either collected with a bimettalicstrip device (Laoag and Tacloban) or with a pyranometer (the four remaining stations).However, these data were not included with the electronic data, and were not availablefor this study.

The list of PAGASA solar radiation stations that provided by PAGASA shows manyadditional stations with global horizontal measurements, using pyranometers. Thesestations are:BascoEchague, IsabelaLa Trinidad, BenguetCasiguran, QuezonMunoz, Nueva EcijaIba, ZabalesInfanta, QuezonUPLB College, LagunaDaet, Camarines NortePili, Camarines SurSan Francisco, QuezonRomblonSan Jose, Mindoro Occ.CatbaloganIloilo AirportBaybay, LeyteLa Carlota CitySurigaoHinatuan, Surigao del SurMarawi CityTagum, Davao (Twin Rivers)

However, data in electronic format for these stations are not available from the Solar Lab.

2.2 Report: “The Profile of Solar Insolation in the Philippines”

The report “The Profile of Solar Insolation in the Philippines” provides tables and mapsof monthly average global horizontal solar resource data based on stations with actualsolar measurements as well as stations that have only sunshine recorders or cloud coverobservations. For the latter types of stations, empirical techniques such as a modificationof the Angstrom relation were used to develop solar resource estimates. The reportshows 17 stations with some form of solar measurement (Kahlisco pyranometer, LicorPyranometer, or other such as bimetallic strip recorder), where data collected in the early1980s are used. Seven of these stations also have sunshine recorders, which allows forthe development of the Angstrom coefficients. Data for 65 stations where sunshinerecorders or cloud cover observations are made are also provided.

2.3 UMASS/Lowell Data Report

In 1991 the University of Lowell Photovoltaic Program developed an international solarradiation data base, providing monthly average daily total solar radiation data fornumerous stations around the world. Most of the data were derived from sunshinerecorders. The report shows a total of fifteen stations for the Philippines.

2.4 World Radiation Data Center Archive of Science Garden Data

An archive of measured solar data from around the world is mainatained at the WorldRadiation Data Center in St. Petersburg, Russia. Much of this archive is accessiblethrough the worldwide web at http://wrdc-mgo.nrel.gov. For the Philippines, only datafrom the Science Garden station are available through this archive. Daily values ofglobal horizontal solar radiation for the period 1964-1993, and diffuse radiation for theperiod 1991-1993 can be found on the archive.

2.5 Summary of Data Stations

Figure 1 shows the location of the major solar resource data stations available for thisstudy. The Figure is divided into two panels. The left hand panel shows the location ofthe PAGASA Solar Lab stations for which electronic data are available (although most ofthese data are monthly average hours of direct sunlight per day). The right hand panelshows the location of measurement stations taken from the “Profiles” report, as well asthe stations used in the Lowell report.

3. Description of the Climatological Solar Radiation Model

The modeling approach that was developed for the production of the U.S. National SolarRadiation Data Base (NSRDB 1993) was modified to provide large area, high spatialresolution of solar resources using a global satellite-derived cloud cover data base. Theoriginal model, METSTAT (Maxwell 1998a), calculates atmospheric extinction for clear-sky and cloudy conditions using inputs of opaque and translucent cloud cover derivedfrom ground observations, precipitable water vapor, ozone, and aerosol optical depth.The output, then, is hourly values of surface direct normal, global horizontal, and diffusesolar radiation. The METSTAT model was modified to generate monthly average dailytotal values of the three elements for each Real-Time Nephanalysis (RTNEPH) grid cell.The modified model is known as the Climatological Solar Radiation (CSR) model(Maxwell, George, and Wilcox 1998b). The RTNEPH data use ground-based cloudcover observations where available (generally, these are three-hourly observationsobtained from national weather services around the world), and Polar OrbitingEnvironmental Satellite imagery to interpolate between the stations. Although the world-wide RTNEPH data are available on a three-hourly basis for a period beginning 1August, 1983, the version of the data used in the CSR model is a histogram data basecovering the period from 1985 to 1992. The histograms of total cloud cover for hoursbetween sunrise and sunset were used to determine monthly average total cloud coverduring daytime hours. The histograms for low, middle, and high cloud layers were usedto estimate monthly average opaque cloud cover.

The CSR model has been run for a number of regions around the world, including theentire east Asia region. The Philippines were included in the east Asia calculations, andthe results of these calculations form the basis of the modeled assessment provided here.Preliminary evaluations of the monthly average daily total model output for severallocations around the world show agreement with ground stations between 5 - 15%, withthe best agreement found when compared with U.S. network stations (on which themodel is partly based).

4. Model Results

Figures 2 through 14 provide annual and twelve monthly average daily total globalhorizontal solar resource data on a 40-km grid for the Philippines. Each figure (annual orindividual month) also shows the comparison of the data grid value with thecorresponding surface value for Science Garden and Victorias Milling Corporation. Anexample of how a regional map would look is shown in Figure 15 for northern Luzon.

The Philippines climate is characterized as monsoonal. Figure 16 is used to show howthe solar resource varies between the dry season (March – May)) and the wet season(November - January).

5. Comparison with Existing Ground Data

It was noted in Figures 2 through 14 that two ground stations are available with which tocompare the CSR model data grid values. Here, in Figures 17-18, we see profiles of themonthly values comparing the ground station with the corresponding CSR model datagrid value. The figures show that, particularly at Science Garden, the CSR model tendsto produce slightly higher values than the ground observation. However, it is importantto note that the data grid represents the average resource over a 1600 km2, while theground station is a point value, which could be valid throughout some portions of thearea.

6. Summary and Conclusions

The results of this analysis shows that the CSR model output provides results that arecomparable to values obtained from surface stations. However, the CSR model iscapable of providing higher resolution data than the ground network. Nevertheless, thespatial variation of the solar resource across the Philippines in any given month is low(approximately 10% to 20%), while the variation between the wet and dry seasons isquite high (30% to 50%).

7. References

Maxwell E. L., METSTAT—the solar radiation model used in the production of theNational Solar Radiation Data Base (NSRDB). Solar Energy 62, 4, 263-279, (1998a).

Maxwell, Eugene L., Raymond L. George, and Stephen M. Wilcox, A ClimatologicalSolar Radiation Model, Proceedings of the 1998 Annual Conference, American SolarEnergy Society, Albuquerque, pp. 505-510, June 14-17, (1998b).

University of Lowell Photovoltaic Program, 1991: International Solar IrradiationDatabase, Version 1.0. University of Lowell Research Foundation, 450 Aitken Street,Lowell, Massachusetts, 01854, USA.

Bonjoc, Manuel C., Rodito D. Buan, and Victor Leano: The Profile of Solar Insolation inthe Philippines. Pp. 185-260.

Victorias, Negros, Occ., #618C Comparison of CSR Model Values with Measured Data

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