Wind Energy Resource Atlas of the Philippines - NREL

February 2001 • NREL/TP-500-26129 

Wind Energy Resource Atlas of the 

Philippines 

D. Elliott, M. Schwartz, R. George, S. Haymes, 

D. Heimiller, G. Scott 

National Renewable Energy Laboratory 

617 Cole Boulevard 

Golden, Colorado 80401-3393 

NREL is a U.S. Department of Energy Laboratory 

Operated by Midwest Research Institute • Battelle • Bechtel 

Contract No. DE-AC36-99-GO10337

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Table of Contents 

LIST OF TABLES ………………………………………………………………………………………. IV 

LIST OF FIGURES ………………………………………………………………………………………. V 

EXECUTIVE SUMMARY ……………………………………………………………………………. VIII 

1.0 INTRODUCTION …………………………………………………………………………………….. 1 

2.0 GEOGRAPHY AND CLIMATE OF THE PHILIPPINES ………………………………………… 2 

2.1 GEOGRAPHY ......................................................................................................................................... 2 

2.2 CLIMATE............................................................................................................................................... 2 

3.0 WIND RESOURCE INFORMATION ………………………………………………………………. 5 

3.1 INTRODUCTION ..................................................................................................................................... 5 

3.2 SURFACE DATA..................................................................................................................................... 5 

3.2.1 PAGASA ....................................................................................................................................... 5 

3.2.2 National Power Corporation........................................................................................................ 5 

3.2.3 DATSAV2 ..................................................................................................................................... 7 

3.2.4 Marine Climatic Atlas of the World ............................................................................................. 7 

3.2.5 Special Sensor Microwave Imager (SSMI)................................................................................... 7 

3.3 UPPER-AIR DATA.................................................................................................................................. 7 

3.3.1 Automated Data Processing Reports (ADP) ................................................................................ 8 

3.3.2 Global Gridded Upper-Air Statistics............................................................................................ 8 

3.4 DATA SCREENING ................................................................................................................................. 8 

3.5 WEIBULL DISTRIBUTION FUNCTION...................................................................................................... 9 

3.6 WIND POWER DENSITY......................................................................................................................... 9 

3.7 WIND SHEAR AND THE POWER LAW................................................................................................... 10 

4.0 WIND RESOURCE ASSESSMENT AND MAPPING METHODOLOGY …………………….. 12 

4.1 INTRODUCTION ................................................................................................................................... 12 

4.2 DESCRIPTION OF MAPPING SYSTEM.................................................................................................... 12 

4.2.1 Input Data .................................................................................................................................. 12 

4.2.2 Wind Power Calculations........................................................................................................... 13 

4.2.3 Mapping Products ...................................................................................................................... 13 

4.3 LIMITATIONS OF MAPPING TECHNIQUE .............................................................................................. 14 

5.0 WIND RESOURCE CHARACTERISTICS OF THE PHILIPPINES …………………………... 15 

5.1 INTRODUCTION ................................................................................................................................... 15 

5.2 SURFACE DATA................................................................................................................................... 15 

5.2.1 PAGASA ..................................................................................................................................... 15 

5.2.2 National Power Corporation...................................................................................................... 20 

5.2.3 DATSAV2 ................................................................................................................................... 24 

5.3 UPPER-AIR DATA................................................................................................................................25 

5.4 SATELLITE OCEAN WIND DATA.......................................................................................................... 26 

5.5 WIND RESOURCE DISTRIBUTION AND CHARACTERISTICS................................................................... 35 

5.5.1 Annual Wind Resource Distribution........................................................................................... 35 

5.5.2 Seasonal Wind Resource Distribution........................................................................................ 35 

5.5.3 Diurnal Wind Speed Distribution............................................................................................... 36 

5.5.4 Wind Direction Frequency Distribution.....................................................................................37 

6.0 WIND MAPPING AND IDENTIFICATION OF RESOURCE AREAS……………………….... 38 

6.1 INTRODUCTION ................................................................................................................................... 38 

6.2 WIND POWER CLASSIFICATIONS......................................................................................................... 38 

ii

6.3 APPROACH.......................................................................................................................................... 38 

6.4 MAPPING REGIONS ............................................................................................................................. 39 

6.5 MAPPING RESULTS ............................................................................................................................. 39 

6.5.1 Batanes and Babuyan................................................................................................................. 39 

6.5.2 Northern Luzon .......................................................................................................................... 40 

6.5.3 Central Luzon............................................................................................................................. 40 

6.5.4 Mindoro, Southern Luzon, Romblon, and Marinduque.............................................................. 41 

6.5.5 Southeastern Luzon, Catanduanes and Masbate........................................................................ 42 

6.5.6 Samar and Leyte......................................................................................................................... 43 

6.5.7 Panay, Negros, Cebu, and Siquijor............................................................................................ 43 

6.5.8 Northern Mindanao and Bohol .................................................................................................. 44 

6.5.9 Southern Mindanao .................................................................................................................... 45 

6.5.10 Western Mindanao and Basilan ............................................................................................... 45 

6.5.11 Northern Palawan .................................................................................................................... 45 

6.5.12 Southern Palawan .................................................................................................................... 46 

6.5.13 Sulu, Basilan, and Tawi-Tawi .................................................................................................. 46 

7.0 WIND ELECTRIC POTENTIAL…………………………………………………………………... 87 

7.1 INTRODUCTION ................................................................................................................................... 87 

7.2 WIND ELECTRIC POTENTIAL ESTIMATES ............................................................................................ 87 

REFERENCES …………………………………………………………………………………………... 91 

APPENDIX A DATA SUMMARIES—NATIONAL POWER CORPORATION SITES 

APPENDIX B ANALYSIS SUMMARIES—SELECTED SITES FROM DATSAV2 DATA 

FILES 

APPENDIX C ANALYSIS SUMMARIES—UPPER-AIR STATIONS 

APPENDIX D WIND SPEED AND WIND POWER DENSITY COMPUTED FROM 

SATELLITE OCEAN WIND DATA 

iii

List of Tables 

TABLE S-1 WIND POWER CLASSIFICATION.......................................................................................IX 

TABLE 4-1 WIND POWER CLASSIFICATION...................................................................................... 14 

TABLE 5-1 LIST OF SYNOPTIC STATIONS PROVIDED BY PAGASA................................................. 16 

TABLE 5-2 WIND MONITORING SITES FOR NATIONAL POWER CORPORATION ............................. 22 

TABLE 5-3 AVERAGE WIND SPEED (M/S) AND POWER (W/M2) ....................................................... 22 

TABLE 5-4 PHILIPPINES’ STATIONS FROM DATSAV2 FILES.......................................................... 27 

TABLE 6-1 WIND POWER CLASSIFICATION...................................................................................... 38 

TABLE 7-1 PHILIPPINES - WIND ELECTRIC POTENTIAL.................................................... 88 

iv

List of Figures 

FIGURE 2.1 PHILIPPINES—POLITICAL BASE MAP.................................................................................. 3 

FIGURE 2.2 ELEVATION MAP................................................................................................................. 4 

FIGURE 3.1 PHILIPPINES—GTS METEOROLOGICAL STATIONS WITH SURFACE WIND DATA................ 6 

FIGURE 5.1 PHILIPPINES—PAGASA METEOROLOGICAL STATIONS WITH SURFACE WIND DATA ..... 17 

FIGURE 5.2 SURFACE AIR FLOW (JANUARY) IN THE PHILIPPINES ........................................................ 18 

FIGURE 5.3 SURFACE AIR FLOW (JULY) IN THE PHILIPPINES ............................................................... 19 

FIGURE 5.4 GENERAL LOCATION OF THE NATIONAL POWER CORPORATION MONITORING SITES IN 

THE PHILIPPINES................................................................................................................ 21 

FIGURE 5.5 MONTHLY WIND SPEED AND POWER—PAGALI................................................................ 23 

FIGURE 5.6 MONTHLY WIND SPEED AND POWER—SAGADA .............................................................. 24 

FIGURE 5.7 MONTHLY WIND SPEED AND POWER—GUIMARAS ISLAND.............................................. 24 

FIGURE 5.8 PHILIPPINES—GTS METEOROLOGICAL STATIONS WITH UPPER-AIR WIND DATA............ 29 

FIGURE 5.9 PHILIPPINES—ANNUAL WIND SPEED (1988-94) COMPUTED FROM SATELLITE OCEAN 

WIND DATA. ..................................................................................................................... 30 

FIGURE 5.10 PHILIPPINES—ANNUAL WIND POWER DENSITY (1988-94) COMPUTED FROM SATELLITE 

OCEAN WIND DATA.......................................................................................................... 31 

FIGURE 5.11 PHILIPPINES—ANNUAL WEIBULL K-VALUE COMPUTED FROM SATELLITE OCEAN WIND 

DATA. ...............................................................................................................................32 

FIGURE 5.12 PHILIPPINES—SATELLITE OCEAN WIND DATA PLOTS OF MONTHLY WIND SPEED (M/S).. 33 

FIGURE 5.13 PHILIPPINES—SATELLITE OCEAN WIND DATA PLOTS OF MONTHLY WIND POWER (W/M2). 

.......................................................................................................................................... 34 

FIGURE 6.1 KEY TO THE REGION MAPS ............................................................................................... 47 

FIGURE 6.2 BATANES AND BABUYAN—POLITICAL BASE MAP ........................................................... 48 

FIGURE 6.3 BATANES AND BABUYAN—ELEVATION MAP................................................................... 49 

FIGURE 6.4 BATANES AND BABUYAN – MAP OF FAVORABLE WIND RESOURCE AREAS ..................... 50 

FIGURE 6.5 NORTHERN LUZON – POLITICAL BASE MAP ..................................................................... 51 

FIGURE 6.6 NORTHERN LUZON – ELEVATION MAP ............................................................................. 52 

FIGURE 6.7 NORTHERN LUZON – MAP OF FAVORABLE WIND RESOURCE AREAS ............................... 53 

FIGURE 6.8 CENTRAL LUZON – POLITICAL BASE MAP ........................................................................ 54 

v

FIGURE 6.9 CENTRAL LUZON – ELEVATION MAP................................................................................ 55 

FIGURE 6.10 CENTRAL LUZON – MAP OF FAVORABLE WIND RESOURCE AREAS .................................. 56 

FIGURE 6.11 MINDORO, SOUTHERN LUZON, ROMBLON, AND MARINDUQUE – 

POLITICAL BASE MA......................................................................................................... 57 

FIGURE 6.12 MINDORO, SOUTHERN LUZON, ROMBLON, AND MARINDUQUE – ELEVATION MAP ......... 58 

FIGURE 6.13 MINDORO, SOUTHERN LUZON, ROMBLON, AND MARINDUQUE – MAP OF FAVORABLE 

WIND RESOURCE AREAS................................................................................................... 59 

FIGURE 6.14 SOUTHEASTERN LUZON, CATANDUANES, MASBATE – POLITICAL BASE MAP.................. 60 

FIGURE 6.15 SOUTHEASTERN LUZON, CATANDUANES, MASBATE – ELEVATION MAP.......................... 61 

FIGURE 6.16 SOUTHEASTERN LUZON, CATANDUANES, MASBATE – MAP OF FAVORABLE WIND 

RESOURCE AREAS............................................................................................................. 62 

FIGURE 6.17 SAMAR AND LEYTE – POLITICAL BASE MAP..................................................................... 63 

FIGURE 6.18 SAMAR AND LEYTE – ELEVATION MAP ............................................................................ 64 

FIGURE 6.19 SAMAR AND LEYTE – MAP OF FAVORABLE WIND RESOURCE AREAS............................... 65 

FIGURE 6.20 PANAY, NEGROS, CEBU, AND SIQUIJOR – POLITICAL BASE MAP ..................................... 66 

FIGURE 6.21 PANAY, NEGROS, CEBU, AND SIQUIJOR – ELEVATION MAP ............................................. 67 

FIGURE 6.22 PANAY, NEGROS, CEBU, AND SIQUIJOR – MAP OF FAVORABLE WIND RESOURCE AREAS 68 

FIGURE 6.23 NORTHERN MINDANAO AND BOHOL – POLITICAL BASE MAP .......................................... 69 

FIGURE 6.24 NORTHERN MINDANAO AND BOHOL – ELEVATION MAP .................................................. 70 

FIGURE 6.25 NORTHERN MINDANAO AND BOHOL – MAP OF FAVORABLE WIND RESOURCE AREAS .... 71 

FIGURE 6.26 SOUTHERN MINDANAO – POLITICAL BASE MAP............................................................... 72 

FIGURE 6.27 SOUTHERN MINDANAO – ELEVATION MAP....................................................................... 73 

FIGURE 6.28 SOUTHERN MINDANAO – MAP OF FAVORABLE WIND RESOURCE AREAS......................... 74 

FIGURE 6.29 WESTERN MINDANAO AND BASILAN – POLITICAL BASE MAP.......................................... 75 

FIGURE 6.30 WESTERN MINDANAO AND BASILAN – ELEVATION MAP ................................................. 76 

FIGURE 6.31 WESTERN MINDANAO AND BASILAN – MAP OF FAVORABLE WIND RESOURCE AREAS.... 77 

FIGURE 6.32 NORTH PALAWAN – POLITICAL BASE MAP....................................................................... 78 

FIGURE 6.33 NORTH PALAWAN – ELEVATION MAP .............................................................................. 79 

FIGURE 6.34 NORTH PALAWAN – MAP OF FAVORABLE WIND RESOURCE AREAS................................. 80 

vi

FIGURE 6.35 SOUTH PALAWAN – POLITICAL BASE MAP ....................................................................... 81 

FIGURE 6.36 SOUTH PALAWAN – ELEVATION MAP............................................................................... 82 

FIGURE 6.37 SOUTH PALAWAN – MAP OF FAVORABLE WIND RESOURCE AREAS ................................. 83 

FIGURE 6.38 SULU, BASILAN, AND TAWI-TAWI – POLITICAL BASE MAP.............................................. 84 

FIGURE 6.39 SULU, BASILAN, AND TAWI-TAWI – ELEVATION MAP...................................................... 85 

FIGURE 6.40 SULU, BASILAN, AND TAWI-TAWI – MAP OF FAVORABLE WIND RESOURCE AREAS........ 86 

FIGURE 7.1 PHILIPPINES – WIND ELECTRIC POTENTIAL - GOOD TO EXCELLENT WIND RESOURCE 

(UTILITY SCALE APPLICATIONS)....................................................................................... 89 

FIGURE 7.2 PHILIPPINES – WIND ELECTRIC POTENTIAL – MODERATE TO EXCELLENT WIND 

RESOURCE (UTILITY SCALE APPLICATION)....................................................................... 90 

vii

Executive Summary 

We conducted a wind resource analysis and mapping study for the Philippine archipelago to 

identify potential wind resource areas and to quantify the value of that resource within those 

areas. This is a major study and the first of its kind undertaken for the Philippines. The key to 

the successful completion of the study is an automated wind resource mapping program recently 

developed at the National Renewable Energy Laboratory (NREL). 

The wind resource mapping program uses an advanced computerized mapping system known as 

the Geographic Information System (GIS). The two primary inputs to the mapping system are 

gridded 1-square kilometer (km 2 ) terrain data and meteorological data. The meteorological data 

sources include surface (land and open-ocean) and upper-air data sets. These data are screened to 

select representative stations and data periods for use in the mapping system. The final 

meteorological inputs to the mapping system are vertical wind profile(s), wind power rose(s) (the 

percentage of total potential power from the wind by direction sector), and the open-ocean wind 

power density, where appropriate. The GIS determines any required adjustments to these 

composite distributions for each 1-km 2 grid cell. The factors that have the greatest influence on 

the adjustment for a particular grid cell are the topography in the vicinity and a combination of 

the absolute and relative elevation of the grid cell. The primary output of the mapping system is a 

color-coded map containing the estimated wind power, and equivalent wind speed, for each 

individual grid cell. 

To portray the mapping results, the Philippine archipelago was divided into 13 regions. Each 

region is approximately 300 km by 300 km. The regional divisions were determined principally 

on the geography of the archipelago and the desire to maintain the same map scale for each 

region. Surface, satellite, and upper-air data were assembled, processed, and analyzed. These 

data sets included information provided by the Philippine Atmospheric, Geophysical, and 

Astronomical Services Administration (PAGASA), the Philippine National Power Corporation 

(NPC), data sets from the United States National Climatic Data Center (NCDC), and other U.S. 

data. The satellite data sets of calculated wind speed at 10-meter (m) heights over ocean areas 

were extremely useful in this analysis because of the large expanse of ocean surrounding the 

archipelago and the limited number and value of land-based observations. The mapping system 

was applied to each of these 13 regions, and the wind resource maps for each region were 

generated. 

A combination of wind characteristics helps determine the wind energy resource in a particular 

area. Factors such as the annual and monthly average wind speeds and the seasonal and diurnal 

wind patterns affect the suitability of an area. In general, locations with an annual average wind 

speed of 6.5 to 7.0 meters per second (m/s) or greater at turbine hub height, are the most suitable 

for utility grid-connected wind energy systems. Rural power applications are typically viable at 

lower wind speeds (5.5 to 6.0 m/s), and, in some cases, at wind speeds as low as 4.5 m/s. 

The average wind speed is not the best indicator of the resource. Instead, the level of the wind 

resource is often defined in terms of the wind-power-density value, expressed in watts per square 

meter (W/m 2 ). This value incorporates the combined effects of the wind speed frequency 

distribution, the dependence of the wind power on air density, and the cube of the wind speed. 

Thus, six wind power classifications, based on ranges of wind-power-density values, were 

established in each of two categories: one for utility-scale applications (ranging from marginal to 

viii

excellent) and one for rural power applications (ranging from moderate to excellent). This 

classification scheme is presented in Table S-1. 

Class Resource Potential 

Utility Rural 

Table S-1. Wind Power Classification 

Wind Power 

Density (W/m 2 ) 

@ 30 m 

ix 

Wind Speed (a) 

(m/s) @ 30 m 

1 Marginal Moderate 100 – 200 4.4 – 5.6 

2 Moderate Good 200 – 300 5.6 – 6.4 

3 Good Excellent 300 – 400 6.4 – 7.0 

4 Excellent Excellent 400 – 600 7.0 – 8.0 



(a) Mean wind speed is estimated assuming a Weibull distribution of wind speeds with a shape factor (k) of 2.0 and 

standard sea-level air density. The actual mean wind speed may differ from these estimated values by as much as 

20 percent, depending on the actual wind speed distribution (or Weibull k value) and the elevation above sea level. 

The wind resource in the Philippines is strongly dependent on latitude, elevation, and proximity 

to the coastline. In general, the best wind resource is in the north and northeast, and the worst 

resource is in the south and southwest of the archipelago. 

The wind mapping results show many areas of good-to-excellent wind resource for utility-scale 

applications or excellent wind resource for village power applications, particularly in the northern 

and central regions of the Philippines. The best wind resources are found in six regions: (1) the 

Batanes and Babuyan islands north of Luzon; (2) the northwest tip of Luzon (Ilocos Norte); (3) 

the higher interior terrain of Luzon, Mindoro, Samar, Leyte, Panay, Negros, Cebu, Palawan, 

eastern Mindanao, and adjacent islands; (4) well-exposed east-facing coastal locations from 

northern Luzon southward to Samar; (5) the wind corridors between Luzon and Mindoro 

(including Lubang Island); and (6) between Mindoro and Panay (including the Semirara Islands 

and extending to the Cuyo Islands). 

More than 10,000 km 2 of windy land areas are estimated to exist with good-to-excellent wind 

resource potential. Using conservative assumptions of about 7 MW per km 2 , this windy land 

could support more than 70,000 MW of potential installed capacity. Considering only the areas 

of good-to-excellent wind resource, there are 47 provinces out of 73 with at least 500 MW of 

wind potential and 25 provinces with at least 1,000 MW of wind potential. However, to 

accurately assess the wind electric potential will require additional studies, considering such 

factors as the existing transmission grid and accessibility. 

The wind mapping results also show numerous additional areas of moderate wind resource for 

utility-scale applications or good wind resource for village power applications. If these additional 

areas are considered, the estimated total land area increases to more than 25,000 km 2 . Using 

conservative assumptions of about 7 MW per km 2 , this land could support more than 170,000 

MW of potential installed capacity. On a provincial basis, there are 51 provinces out of 73 with 

at least 1,000 MW of wind potential and 64 provinces with at least 500 MW of wind potential. 

The seasons have a pronounced effect on the wind resource. The best resource is in the winter 

during the northeast monsoon, and the poorest resource is in the summer during the southwest 

monsoon. Throughout most of the Philippines, the highest wind resource occurs from November

through February, and the lowest from April to September. However, there are some regional 

differences in the seasonal variability. For example, in the northern Philippines, the months with 

the highest wind resource are October through February; and in much of the central and southern 

Philippines, November through March are the months with the highest wind resource. Two areas 

of the Philippines (the southeastern Mindanao coast and the western coast of Palawan) have a 

relatively high wind resource from June through September during the southwest monsoon. 

The wind resource maps and other wind resource characteristic information will be useful in 

identifying prospective areas for wind-energy applications. However, very limited data of 

sufficient quality were available to validate the wind resource estimates. Therefore, we strongly 

recommend that wind measurement programs be conducted to validate the resource estimates and 

to refine the wind maps and assessment methods where necessary. 

x

1.0 Introduction 

1 

Wind Energy Resource 

Atlas of the Philippines 

Upon learning of the National Renewable Energy Laboratory’s (NREL) capability in regional- or 

national-scale wind energy resource assessment, the Winrock International Philippines 

Renewable Energy Project Support Office (REPSO) and Preferred Energy, Inc. (PEI), worked 

with other interested parties in the Philippines to propose and fund the development of a nationallevel 

Wind Energy Resource Atlas. The Philippine Council for Industry and Energy Research 

and Development (PCIERD), of the Department of Science and Technology (DOST), and the 

Philippines National Oil Company (PNOC) each provided funding for the study through Winrock 

International. The U.S. Department of Energy (DOE) provided significant funding for the 

development of the Wind Energy Resource Atlas, and the U.S. Agency for International 

Development (USAID) supported the overall coordination and data gathering for the Wind Atlas 

development effort. The project was intended to facilitate and accelerate the use of wind energy 

technologies—both for utility-scale generation and off-grid wind energy applications—in the 

Philippines, by providing the best possible estimates of wind energy resources over the entire 

national territory. The Philippines National Power Corporation (NPC) supported the project by 

contributing wind-monitoring data collected at 14 prospective wind energy sites and by providing 

other technical assistance. 

Winrock International and REPSO had the lead responsibility in administering this project and in 

collaborating with the Philippine organizations and NREL on project activities. NREL had the 

technical lead for the wind resource analysis and mapping activities. The primary goal was to 

develop detailed wind resource maps for all regions of the Philippines and to produce a 

comprehensive wind-resource atlas documenting the mapping results. 

This document, the “Wind Energy Resource Atlas of the Philippines,” presents the wind-resource 

analysis and mapping results for the Philippines. The maps identifying the wind resource were 

created using a Geographic Information System- (GIS) based program developed at NREL. The 

mapping program, which combines high-resolution terrain data and formatted meteorological 

data, is designed to highlight areas possessing a favorable wind resource where specific wind 

energy projects, both for utility-grid applications and rural power applications, are likely to be 

feasible. The entire Philippines archipelago was mapped as part of this study. This is the first 

detailed national-scale wind energy resource atlas for a developing country, and one of the very 

first in the world. In addition to the Philippines, NREL has applied its new wind mapping system 

to produce wind resource assessments of the Dominican Republic (Elliott, 1999) and Mongolia 

(Elliott et al., 1998), and specific regions of Chile, China, Indonesia, Mexico, and the United 

States (Schwartz, 1999; Elliott et al., 1999). 

The report is divided into six sections. An overview of the geography and climate of the 

Philippines is presented in Section 2.0. The wind resource information used to create the 

meteorological input files is highlighted in Section 3.0. A description of the mapping system is 

presented in Section 4.0. The wind resource characteristics of the Philippines and the wind 

mapping results are presented in Sections 5.0 and 6.0, respectively. 

Appendices are included that highlight the analysis results from the NPC monitoring sites and 

selected surface-based sites from the DATSAV2 database, summarize data for three of the upperair 

stations, and show maps and monthly summaries of wind speed and wind power from the 

satellite ocean wind data.

2.0 Geography and Climate of the Philippines 

2.1 Geography 

2 



The Philippines is an archipelago consisting of 7,107 islands in the western Pacific. Figure 2-1 is 

a political base map of the Philippines and includes the names of major islands and cities. 

Boundaries of the 73 provinces are also shown in the figure. The population of the Philippines is 

76,103,564 (July 1997 est.). The land area is approximately 299,000 square kilometers (km) 

(116,610 square miles), and there is approximately 36,289 km of coastline. The Philippines 

archipelago is centered at approximately 13 degrees north latitude and 122 degrees east longitude. 

Taiwan is north of the archipelago, Indonesia is south, and Eastern Malaysia and Brunei are 

southwest. Of all the islands in the archipelago, only 2,000 are inhabited. Luzon and Mindanao 

are the largest islands and comprise 66% of the total area of the country. 

The terrain, shown in Figure 2-2, is largely mountainous with narrow coastal plains and interior 

plains and valleys. The principal valleys are in Central Luzon and include the northeastern 

Cagayan Valley and the Agusan Basin in the far south. There are numerous dormant and active 

volcanoes, such as Mt. Pinatubo on Luzon. The highest point in the archipelago is Mt. Apo on 

Mindanao at 2,954 meters (9,689 feet). 

2.2 Climate 

The Philippines has a tropical marine climate dominated by a wet season and a dry season. 

Prevailing winds govern the seasons. The southwest monsoon brings heavy rains to the 

archipelago from May to October, while the northeast monsoon brings cooler and drier air from 

December to February. The easterly trade winds induce hot, dry weather in March and April. 

However, the climate varies somewhat by region. 

The northeast monsoon affects the northern part of the Philippines in October and reaches the 

southern portion of the archipelago by November. This wind flow attains its maximum strength 

in December throughout much of the Philippines and generally weakens by late March. The 

southwest wind first affects the northern part of the archipelago by early May and reaches the 

southern portion by June, attaining maximum intensity in August and gradually disappearing in 

October. 

Mean annual sea-level temperatures rarely fall below 27 degrees Centigrade (°C). Annual rainfall 

is quite heavy in the mountains, but is much less in some sheltered valley areas. Typhoons, or 

eastern Pacific hurricanes, frequently hit the Philippines during the hurricane season, which 

extends from July through October, especially in northern and eastern Luzon, Bicol, and the 

eastern Visayas.

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

3.0 Wind Resource Information 


5 



An accurate wind resource assessment is highly dependent on the quantity and quality of the 

input data. NREL reviews numerous sources of wind speed data and previous wind energy 

assessments as part of its overall evaluation. We used several global wind data sets that have 

recently become available in this assessment. These data sets included land surface observations, 

marine data, and upper-air data. Multiple data sets are used because the quality of data in any 

particular data set can vary, and because high-quality data can be quite sparse in many regions of 

the world. Each data set plays an integral role in the overall assessment. This chapter 

summarizes the data sets analyzed in the wind resource mapping effort for the Philippines. 

3.2 Surface Data 

High-quality surface wind data from well-exposed locations can provide the best indication of the 

magnitude and distribution of the wind resource in the analysis region. The locations of 

meteorological stations in the Philippines where surface wind speed data were available are 

presented in Figure 3-1. The following sections present a summary of the surface data sets used 

in the assessment. 

3.2.1 PAGASA 

The National Institute of Climatology, Philippine Atmospheric, Geophysical, and Astronomical 

Services Administration (PAGASA) provided summarized data and several reports for this study. 

The summarized data included average wind speed and prevailing direction, by month, for 44 

stations covering the period from 1961 to 1992. The two reports provided for this study included 

Climatological Normal of Surface Winds in the Philippines, prepared by the National Institute of 

Climatology, PAGASA, in January 1988, and Solar Radiation and Wind Mapping of the 

Philippines, also prepared by the National Institute of Climatology, PAGASA, in October 1986. 

3.2.2 National Power Corporation 

The NPC provided data from several wind-resource monitoring programs operated by NPC from 

1994 to 1997, including hourly average wind speed and prevailing direction from nine sites, using 

30-m-tall towers and state-of-the-art data acquisition equipment. The period of record at these 

nine sites varied from 9 months to 20 months. Monthly average wind speeds from five additional 

sites employing shorter towers were also provided.

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

3.2.3 DATSAV2 

7 



This global climatic database, obtained from the U.S. National Climatic Data Center (NCDC), 

contains the hourly surface weather observations from first-order meteorological stations 

throughout the world. This data set is the primary source of surface wind information used in the 

analysis. NREL currently has 24 years of DATSAV2 data in its archive, spanning the period 

1973 to 1996. Additional years of data, in some cases back to the 1940s, were available in 

DATSAV2 for many stations in the Philippines. Meteorological parameters such as wind speed, 

wind direction, temperature, pressure, and altimeter setting are extracted from the hourly 

observations and used to create statistical summaries of wind characteristics. Most of the stations 

in the Philippines transmitted synoptic observations every 3 hours; many stations did not transmit 

during late-night hours. At many stations, the transmission frequency changed over the years. 

Some stations transmitted more frequently (hourly) or less frequently (such as every 6 hours) 

during some time periods. Each station in the DATSAV2 data set is identified by a unique sixdigit 

number based on the World Meteorological Organization (WMO) numbering system for the 

stations in the Philippines. 

3.2.4 Marine Climatic Atlas of the World 

This is one of two global marine wind data sets used by NREL to provide estimates of the wind 

resource for offshore areas as well as coastal and inland sites that are well-exposed to the ocean 

winds. This data set, compiled from historical ship observations, presents summarized wind 

statistics for a 1-degree-latitude by 1-degree-longitude grid. Measurements are concentrated 

along the major shipping routes. Included are summaries of the monthly means and standard 

deviations of wind speed, pressure, temperature, and wind direction frequency and speed. 

3.2.5 Special Sensor Microwave Imager (SSMI) 

The SSMI, which is part of the Defense Meteorological Satellite Program, provides 10-m ocean 

wind speed measurements. This data set provides much more uniform and detailed coverage of 

oceanic wind speeds than the Marine Climatic Atlas of the World. Comparisons of satellitederived 

winds with ship observations along major shipping routes indicate consistent results. 

NREL currently has 9 years of SSMI data covering the period 1988 to 1996. 

3.3 Upper-Air Data 

Upper-air data can provide an estimate of the wind resource at low levels in the atmosphere and 

contribute to the understanding of the vertical distribution of the wind resource. This is useful in 

estimating the winds on elevated terrain features and for estimating the wind resource at exposed 

locations in areas without reliable surface wind observations. The following two upper-air data 

sets were employed in the assessment.

3.3.1 Automated Data Processing Reports (ADP) 

8 



This data set contains upper-air observations from rawinsonde instruments and pilot balloons for 

approximately 1,800 stations worldwide. Observation times include 00, 06, 12, and 18 

Greenwich Mean Time (GMT). Wind information is available from the surface, from mandatory 

pressure levels (1,000 mb, 850 mb, 700 mb, and 500 mb), from significant pressure levels (as 

determined by the vertical profiles of temperature and moisture), and from specified geopotential 

heights above the surface. The significant pressure levels and geopotential heights are different 

for each upper-air observation. The data set housed at NREL has approximately 25 years of 

observations, beginning in 1973. 

3.3.2 Global Gridded Upper-Air Statistics 

This data set contains monthly means and standard deviations of climatic elements for 15 

atmospheric levels on a 2.5-degree global grid. We obtained the data, which covers the period 

1980 to 1991, from the NCDC. This data set is used to supplement the ADP information in areas 

where upper-air data are scarce. 

3.4 Data Screening 

The reliability of the meteorological input data is the most important factor in creating an 

accurate wind resource map. A recent NREL paper (Schwartz and Elliott, 1997) describes the 

integration, analysis, and evaluation of different meteorological data sets for use in wind resource 

assessment. Known problems associated with observations taken at many meteorological stations 

around the world include a lack of information on anemometer height, exposure, hardware, 

maintenance history, and observational procedures. In addition, many areas of the world with the 

potential to have good or excellent wind resource sites have very little or no meteorological 

stations to provide guidance on assessing the wind magnitude and characteristics. 

An analysis of the meteorological data is performed using techniques developed by NREL 

specifically for wind resource analysis. We used a comprehensive data-processing package to 

convert the surface and upper-air data to statistical summaries of the wind characteristics. The 

summaries, presented as a series of graphs and tables in the appendices, were used to highlight 

the regional wind characteristics. The DATSAV2 summaries include the interannual variability 

of the wind speed and wind power, the average wind speed and power on a monthly basis, the 

diurnal distribution of the wind resource, and the mean wind speed and frequency by direction 

sector. The wind power density is also computed and analyzed because it provides a truer 

indication of the wind resource potential than wind speed. We generated similar types of 

summaries for the upper-air data at specific geopotential heights or pressure levels of interest. 

We also generated monthly and annual average vertical profiles of wind speed by geopotential 

height or pressure level from the upper-air data. 

Site-specific products are screened for consistency and reasonableness. For example, the 

interannual wind speeds are evaluated to identify obvious trends in the data, or periods of 

questionable data. Only representative data periods are selected from the entire record for the 

assessment. The summarized products are also cross-referenced against each other to select sites 

that apparently have the best exposure and to develop an understanding of the wind 

characteristics of the study region. This is important because of the variable quality of the data

9 



and, in most cases, the lack of documentation of the anemometer height and exposure. For 

assessment purposes, NREL assumes an anemometer height of 10 m (the WMO standard height) 

unless specific height information is provided. When there is a conflict among the information as 

to certain wind characteristics in the analysis region, the preponderance of meteorological 

evidence from the region serves as the basis of the input. The goal of the data analysis and 

screening process is to develop a conceptual model of the physical mechanisms, both regional 

and local in scale, that influence the wind flow. 

3.5 Weibull Distribution Function 

The Weibull Distribution Function is a generally accepted methodology used to estimate the wind 

speed frequency distribution. The Weibull Function is defined as follows: 

where f(V) is the Weibull probability density function where the probability of encountering a 

wind speed of V m/s is f(V); c, expressed in m/s, is the Weibull scale factor, which is typically 

related to the average wind speed through the shape factor; and k is the Weibull shape factor, 

which describes the distribution of the wind speeds. Detailed explanations of the Weibull 

Distribution Function and its application are available in many texts, such as that by Rohatgi and 

Nelson (1994). 

3.6 Wind Power Density 

The wind resource at a site can be described by the mean wind speed, but the wind power density 

(WPD) provides a truer indication of a site’s wind energy potential. The power density is 

proportional to the sum of the cube of the instantaneous or short-term average wind speed and the 

air density. The wind power density, in units of W/m 2 , is computed by the following equation: 

where 

( )( ) ( ) k 

k −1 

k / c V / c exp −V 

c 

f ( V ) = 

/ 

n 

1 

3 2 

WPD = ∑ ρ × v i ( W/m ) 

2n 

n = the number of records in the averaging interval; 

ρ = the air density (kg/m 3 ) at a particular observation time; and 

vi 3 = the cube of the wind speed (m/s) at the same observation time. 

i= 1 

This equation should only be used for instantaneous (n = 1) or multiple average wind speed 

values (n>1) and not for a single long-term average, such as a yearly value. 

The air density term is dependent on temperature and pressure and can vary by 10% to 15% 

seasonally. If the site pressure is known, the hourly air-density values, with respect to air 

temperature, can be calculated using the following equation: 

ρ = 

P 

3 

(kg / m ) 

R× T

where 

P = the air pressure (Pa or N/m 2 ); 

R = the specific gas constant for air (287 J/kg⋅K); and 

T = the air temperature in degrees Kelvin (°C+273). 

10 



If site pressure is not available, air density can be estimated as a function of site elevation (z) and 

temperature (T) as follows: 

where 

⎛ 

⎛ P ⎞ ⎜ 

0 ⎝ 

ρ = ⎜ ⎟ε 

⎝ R⋅T⎠ −gz ⋅ ⎞ 

⎟ 

RT ⋅ ⎠ 

3 

(kg / m ) 

P0 = the standard sea level atmospheric pressure (101,325 Pa), or the actual sealevel 

adjusted pressure reading from a local airport; 

g = the gravitational constant (9.8 m/s 2 ); and 

z = the site elevation above sea level (m). 

Substituting in the numerical values for P0, R, and g, the resulting equation is: 

ρ = ε 

⎛ ⎞ 

⎜ ⎟ 

⎝ ⎠ 

− 353.05 

T 

⎛ z ⎞ 

0. 034⎜ 

⎟ 

⎝ t ⎠ 

3 

(kg / m ) 

This air density equation can be substituted into the WPD equation for the determination of each 

instantaneous or multiple average value. 

3.7 Wind Shear and the Power Law 

The wind shear is a description of the change in horizontal wind speed with height. The 

magnitude of the wind shear is site-specific and dependent on wind direction, wind speed, and 

atmospheric stability. By determining the wind shear, one can extrapolate existing wind speed or 

wind-power-density data to other heights. The following form of the power law equation is used 

to make these adjustments: 

U = U0 (z/z0) α [Wind Speed] 

P = P0 (z/z0) 3α 

[Wind Power Density]

where 

U = the unknown wind speed at height z above ground; 

U0 = the known speed at a reference height z0; 

P = the unknown wind power density at height z above ground; 

P0 = the known wind power density at a reference height z0; 

α = the power law exponent. 

11 



An exponent of 1/7 (or 0.143), which is representative of well-exposed areas with low surface 

roughness, is often used to extrapolate data to higher heights.

12 



4.0 Wind Resource Assessment and Mapping Methodology 


NREL has been developing its GIS-based wind resource mapping technique since 1996. This 

technique replaces the manual analysis techniques employed in previous mapping efforts, such as 

the Wind Energy Resource Atlas of the United States (Elliott et al., 1987) and the “Mexico Wind 

Resource Assessment Project” (Schwartz and Elliott, 1995). NREL developed the system with 

the following two primary goals in mind: 

1) To produce a more consistent and detailed analysis of the wind resource, particularly in areas 

of complex terrain; and, 

2) To generate user-friendly high-quality map products. 

4.2 Description of Mapping System 

The mapping procedure uses GIS advanced computerized mapping system. The main GIS 

software is ARC/INFO, a powerful and complex package featuring a large number of routines for 

scientific analysis. None of the ARC/INFO analysis routines is specifically designed for wind 

resource assessment work, so NREL’s mapping technique requires extensive programming in 

ARC/INFO to create combinations of scientific routines that mimic direct wind-resource 

assessment methods. The mapping system is divided into three main components: input data, 

wind power calculations, and the output section that produces the final wind resource map. These 

components are described below. 

4.2.1 Input Data 

The two primary model inputs are digital terrain data and formatted meteorological data. The 

elevation information consists of Digital Elevation Model (DEM) terrain data that are used to 

divide the analysis region into individual grid cells, each having its own unique elevation value. 

The United States Geological Survey (USGS) and the Earth Resource Observing Satellite Data 

Center (EROS) recently produced updated DEMs for most of the world from previously 

classified Department of Defense data and other sources. The new data sets have a resolution of 

1 km 2 and are available for large parts of the world. This represents a significant improvement in 

elevation data used by the mapping system. It previously relied on 1:1,000,000 scale maps and 

305-m (1,000 ft) elevation contours. Most of the final wind resource maps are gridded to 1 km 2 . 

The final meteorological inputs to the mapping system, following the data screening process, are 

vertical wind profile(s), wind power rose(s) (the percentage of total potential power from the 

wind by direction sector), and the open-ocean wind-power density, where appropriate. The data 

are brought in as ARC/INFO-compatible files and used in the power calculation algorithms. The 

vertical profiles are broken down into 100-m intervals centered every 100 m above sea level (asl), 

except for the lowest layer, which is at 50 m asl. The wind power rose is used to determine the 

degree of exposure of a particular grid cell to the power-producing winds. The open-ocean wind 

power density is derived from the SSMI and ship wind speed observations, converted to wind 

power density, and extrapolated to 30 m for use by the model.

4.2.2 Wind Power Calculations 

13 



The wind-power-calculation methodology is presented in Section 3.6. The factors that either 

decrease or increase the base wind power value for a particular grid cell are terrain 

considerations, relative and absolute elevation, aspect (the slope of the terrain relative to the 

prevailing wind direction), distance from ocean or lake shorelines, and influence of small-scale 

wind flow patterns. The factors that have the greatest influence on the adjustment of the base 

wind power for a particular grid cell are the topography of the area in the vicinity and a 

combination of the absolute and relative elevation. The wind-power-calculation modules use the 

wind power rose and vertical wind profile of a region to account for the effects of short-range 

(less than 10 km), medium-range (10-50 km), and long-range (greater than 50 km) blocking of 

the ambient wind flow by the terrain; the slope and aspect of the terrain surrounding a particular 

grid cell; and the relative elevation of a grid cell compared to its surroundings. 

The wind power calculations are performed in three modules, depending upon the existence or 

proximity of oceans or large lakes to the mapping region. These include “land,” “ocean,” and 

“lake” modules. The land module is run for the entire area only if there is no ocean present in the 

mapping region. Likewise, the ocean module is run for the entire area in instances where there is 

an ocean shoreline present in the mapping region. The lake module is run only if there are lakes, 

estuaries, or fjords with an area of 50 km 2 or greater. This module only calculates the wind 

power for the area within 5 km of any non-ocean body of water in the mapped region. If more 

than one module is run for a particular region, the results are combined to produce the final wind 

map. Each of the three modules contains identical routines that use a general topographical 

description to adjust the base wind power density. The topographical description can be 

classified as either complex terrain (hills and ridges), complex terrain with large flat areas 

present, or areas that are designated as flat. The adjustment to the base wind-power density 

depends on which terrain routine is activated during the mapping run. 

4.2.3 Mapping Products 

The primary output of the mapping system is a color-coded wind power map in units of W/m 2 

and the equivalent mean wind speed for each individual grid cell. The wind power classification 

scheme for the Philippines maps is presented in Table 4-1. We used the one-seventh-power law 

(see Section 3.7) to adjust the power densities to a height of 30 m above ground, used as the 

reference height in the classification. The 30-m height was chosen as a compromise hub height 

between large utility-scale wind turbines (which may range between 30 m to 60 m) and small 

wind turbines (which may range between 15 m and 30 m) for rural power applications. 

Wind power is calculated only for those grid cells that meet certain exposure and slope 

requirements. As a result, only the most favorable wind resource areas are highlighted. For 

example, a grid cell is excluded if there is major blocking of the ambient wind flow by local 

terrain features. The exposure must be at least 70% to be included. A grid cell can also be 

excluded if the slope of the terrain is too steep. To be included, the slope must not exceed 20%. 

The wind resource values presented are estimates for low surface roughness (e.g., grassland with 

no major obstructions, such as trees or buildings).


Utility Rural 

Table 4-1. Wind Power Classification 



@ 30 m 

14 




(m/s) @ 30 m 

1 Marginal Moderate 100 - 200 4.4 - 5.6 

2 Moderate Good 200 - 300 5.6 - 6.4 

3 Good Excellent 300 - 400 6.4 - 7.0 

4 Excellent Excellent 400 - 600 7.0 - 8.0 


6 Excellent Excellent 800 -1200 8.8 -10.1 



20 percent, depending on the actual wind-speed distribution (or Weibull k value) and elevation above sea level. 

The output portion of the mapping system also includes software to produce the proper map 

projection for the region. It labels the map with useful information, such as a legend, latitude and 

longitude lines, locations of meteorological stations, prevailing wind direction(s), important 

cities, and a distance scale. The DEM data can also be used to create a color-coded elevation 

map, a hill-shaded relief map, and a map of the elevation contours. When combined with the 

wind power maps, these products enable the user to obtain a feel for the three-dimensional 

distribution of the wind power in the analysis region. 

4.3 Limitations of Mapping Technique 

There are several limitations to the mapping technique, the first being the resolution of the DEM 

data. Significant terrain variations can occur within the DEM’s 1 km 2 area; thus, the wind 

resource estimate for a particular grid cell may not apply to all areas within the cell. A second 

potential problem is the development of the conceptual model of the wind flow and its 

extrapolation to the analysis region. There are many complexities in the wind flow that make this 

an inexact methodology, including the structure of low-level jets and their interaction with the 

boundary layer, and localized circulations, such as land-sea breezes, mountain-valley flows, and 

channeling effects in steeply sloped areas. Finally, the power estimates are valid for areas with 

low surface roughness. Estimates for areas with a higher surface roughness need to be adjusted 

accordingly.

15 



5.0 Wind Resource Characteristics of the Philippines 


This section presents and discusses both surface and upper-air data, collected for this study. 

These data sources include those data archives available at NREL and the data provided by local 

agencies in the Philippines. 

5.2 Surface Data 

5.2.1 PAGASA 

PAGASA provided NREL a summary of the average wind speed and prevailing direction for 44 

surface-based stations and two reports: Climatological Normal of Surface Winds in the 

Philippines (January 1988) and Solar Radiation and Wind Mapping of the Philippines (October 

1986). 

The Climate Data Section, the Climatology and Agrometeorology Branch of PAGASA, prepared 

a summary of monthly average wind speeds and prevailing directions for 44 stations in the 

Philippines. These are principally the synoptic reporting stations managed by PAGASA, listed in 

Table 5-1 and shown in Figure 5-1. Wind speed and direction is collected nominally at 10 m (33 

feet) above ground level. The annual average wind speeds at these stations are quite low, ranging 

from 1.0 to 5.0 m/s. 

The PAGASA Report Climatological Normal of Surface Winds In the Philippines presents a 

series of maps with average wind speed and prevailing wind direction, by month, for the 

archipelago. Samples of the maps are included as Figures 5-2 and 5-3. These maps are based on 

a variety of data sources, including stations where winds are estimated using the Beaufort Scale 

of Wind. This report included a table of the highest wind speeds recorded in the Philippines, by 

month. The highest wind gust recorded in the country was 77 m/s at Virac Synop on October 13, 

1970, associated with the landfall of Typhoon “Sening”. 

The PAGASA Report Solar Radiation and Wind Mapping of the Philippines presents wind flow 

maps, but also includes, by month, an analysis of the shape and scale parameters (both related to 

the Weibull distribution), the mean wind speed, and the mean wind-power density. The 

conclusions are based on two data sets. The first set consists of 30 years (1951–1980) of surface 

wind data at 10 m for 23 synoptic stations. These data were observed using a 3–5-minute 

averaging period from a wind instrument indicator or the Beaufort Scale Wind Force method 

taken every 3 hours. The second set of surface wind data is based on data extracted from chart 

recorders. The period of record covers mid-1981 to mid-1984 (approximately 3 years). 

These data were then plotted and analyzed. The highest annual average wind speeds and 

corresponding high wind-power density occurred along the north coast of Luzon and the northern 

islands, the east and west central parts of the archipelago, and on a ridgeline overlooking the Taal 

Volcano. Mean monthly wind speeds are highest in the winter during the northeast monsoon and 

lower during the summer. The diurnal variation of the wind speeds showed significant 

variability. For example, some sites showed the highest wind speeds were during midday, other 

sites showed a peak at midnight.

Table 5-1 

List of Synoptic Stations Provided By PAGASA 

Station Name Latitude Longitude Elevation 

(m) 

16 

Period of 

Record 



Annual Average 

Wind Speed 

(m/s) 

Alabat, Quezon 14 01 122 01 5.0 1961-92 3.0 

Ambulong, Batangas 14 05 121 03 10.0 1961-92 2.0 

Aparri, Cagayan 18 22 121 38 3.0 1961-92 3.0 

Baguio City, Benguet 16 25 120 36 1,500.0 1961-92 2.0 

Baler, Quezon 15 46 121 34 6.0 1961-92 2.0 

Basco, Batanes 20 27 121 58 11.0 1961-92 5.0 

Butuan City, Agusan Del Norte 08 56 125 31 18.0 1981-92 1.0 

Cabanatuan, Nueva Ecija 15 29 120 58 32.0 1961-92 2.0 

Cagayan De Oro, Misamis Oriental 08 29 124 38 6.0 1961-92 1.0 

Calapan, Oriental Mindoro 13 25 121 11 40.5 1961-92 2.0 

Casiguran, Quezon 16 17 122 07 4.0 1961-92 2.0 

Catarman, Northern Samar 12 29 124 38 50.0 1961-92 2.0 

Catbalogan, Western Samar 11 47 124 53 5.0 1961-92 2.0 

Coron, Palawan 12 00 120 12 14.0 1961-92 2.0 

Cuyo, Palawan 10 51 121 02 4.0 1961-92 5.0 

Dagupan City, Pangasinan 16 03 120 20 2.0 1961-92 3.0 

Davao City, Davao Del Sur 07 07 125 39 18.0 1961-92 2.0 

Dipolog, Zamboanga Del Norte 08 36 123 21 4.0 1961-92 2.0 

Dumaguete City, Negros Oriental 09 18 123 18 8.0 1961-92 2.0 

General Santos, South Cotabato 06 07 125 11 15.0 1961-92 2.0 

Iba, Zambales 15 20 119 58 4.7 1961-92 3.0 

Iloilo City, Iloilo 10 42 122 34 8.0 1961-92 4.0 

Infanta, Quezon 14 45 121 39 7.0 1961-92 2.0 

Laoag City, Ilocos Norte 18 11 120 32 5.0 1961-92 3.0 

Legaspi City, Albay 13 08 123 44 17.0 1961-92 3.0 

Maasin, Southern Leyte 10 08 124 50 71.8 1971-92 2.0 

Mactan, Cebu 10 18 123 58 12.8 1972-92 3.0 

Malaybalay, Bukidnon 08 09 125 05 627.0 1961-92 1.0 

Masbate, Masbate 12 22 123 37 6.0 1961-92 2.0 

Naia, Pasay City 14 31 121 01 21.0 1961-92 3.0 

Port Area, Manila 14 35 120 59 16.0 1961-92 3.0 

Puerto Princesa, Palawan 09 45 118 44 16.0 1961-92 2.0 

Romblon, Romblon 12 35 122 16 47.0 1961-92 3.0 

Roxas City, Aklan 11 35 122 45 4.0 1961-92 3.0 

San Francisco, Quezon 13 22 122 31 45.0 1961-92 3.0 

San Jose, Occidental Mindoro 12 21 121 02 0.3 1981-92 3.0 

Surigao, Surigao De Norte 09 48 125 30 39.0 1961-92 3.0 

Tacloban City, Leyte 11 14 125 02 3.0 1961-92 2.0 

Tagbilaran City, Bohol 09 36 123 52 6.0 1961-92 2.0 

Tayabas, Quezon 14 02 121 35 157.7 1971-92 2.0 

Tuguegarao, Cagayan 17 37 121 44 61.8 1961-92 2.0 

Vigan, Ilocos Sur 17 34 120 23 33.0 1961-92 3.0 

Virac Synop, Catanduanes 13 35 124 14 40.0 1961-92 3.0 

Zamboanga City, Zamboanga Del 

Sur 

06 54 122 04 6.0 1961-92 2.0

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

Figure 5.2 Surface Air Flow (January) in the Philippines 

18 


Atlas of the Philippines

Figure 5.3 Surface Air Flow (July) in the Philippines 

19 


Atlas of the Philippines



These reports represent a good starting point in understanding the wind resource in the 

Philippines; however, the studies do have some significant limitations: 

• The conclusions are based on the data from only 35 stations. 

• There is no information on the exposure of the instruments at these 35 stations. This type of 

knowledge is extremely useful in judging the quality of the data used in the study. 

• There is no information regarding the quality of the measurements at each of the sites. 

Failure to properly maintain the anemometer, location changes, urbanization, and vegetation 

changes surrounding the anemometer site affect the measurements. 

• The analysis did not take into account the topography of the archipelago or other factors that 

may accelerate or retard the wind. 

5.2.2 National Power Corporation 

NPC conducted a wind-resource-measurement program by placing towers with wind-speedmeasurement 

equipment at various sites in Luzon, Batanes, Catanduanes, Romblon Island, Cuyo 

Island, and Guimaras Island. These were the general locations of the better wind resource areas 

from the previous PAGASA studies. At nine of the sites, the wind-resource-measurement 

equipment consisted of NRG Systems 30-m-tall towers, NRG Systems 9200 data loggers, 

Maximum #40 wind speed sensors, and #200P wind direction sensors. The general location of 

the monitoring sites is presented in Figure 5-4. Two levels of wind speed and two levels of wind 

direction (20 m and 30 m) were installed on each tall tower. The sampling rate was every 2 

seconds, and the data were averaged into hourly values. For the other five sites, we used a shorter 

tower, either 12-m or 15.5-m, and the data acquisition equipment is not identified. The 

monitoring sites are installed in eight specific areas: Ilocos Norte (7 sites), Mountain Province (1 

site), Guimaras Island (1 site), Romblon Island (1 site), Catanduanes (1 site), Cuyo Island (1 site), 

and Batanes (1 site). A description of each site is presented in Table 5-2. 

Seven of the sites are in the northwestern portion of Luzon, along the coast and in the coastal 

hills. The hourly wind speed and wind direction data were available for Bayog, Pagali, Saoit, 

Agaga, Bangui, Caparispisan, Subec, Sagada, and Guimaras. NREL processed these data to 

produce estimates of monthly average power and monthly average wind speed, as well as average 

speed and power by hour of the day, and joint frequencies of wind speed and wind direction (see 

Appendix A). The annual average wind speed and power for the 30-m sites are presented in 

Table 5-3. The monthly average wind speed and wind power for three sites—Pagali, Sagada, and 

Guimaras Island—are presented in Figures 5-5 to 5-7. Due to the short collection period at all 

NPC sites, some months are underrepresented relative to others (see plots of ‘Observations by 

Month’ in Appendix A). Averaging all records can bias the average towards those months with 

more records. To eliminate this bias, all annual averages reported here were computed by 

averaging the 12 monthly values. Some of these monthly values may have been derived from 

data from 2 years, while others represent only a single year. 

The sites at Bayog, Pagali, and Saoit are located on the northwest coast of Luzon near the town of 

Burgos. The site maps provided by NPC indicate that Bayog and Pagali are along the coast, 

while Saoit is located on the inland hills. Annual wind speeds at 30 m above ground level were 

5.6 m/s at Saoit, 6.9 m/s at Bayog, and 7.2 m/s at Pagali. There are significant differences in the 

magnitude of the wind speed between the months with the highest and lowest average wind 

speeds. For example, at Bayog the highest monthly average wind speed is 12.4 m/s (December), 

while the lowest value is 4.0 m/s (June). At Saoit, the highest value is 9.0 m/s (December), and 

20

21 



the lowest is 3.7 m/s (June). At Pagali, the highest value is 11.9 m/s (December), and the lowest 

is 3.6 m/s (June). For Bayog, Pagali, and Saoit, the annual average wind powers are 510 W/m 2 , 

569 W/m 2 , and 266 W/m 2 , respectively, with the highest values occurring in December and the 

lowest values in June. 

The sites at Agaga, Caparispisan, and Subec are also located in northwestern Luzon, north of the 

town of Laoag. The Agaga and Subec sites are located on interior hills, while Caparispisan is on 

Figure 5.4 General location of the National Power Corporation monitoring sites in the 

Philippines

Table 5-2. Wind Monitoring Sites for National Power Corporation 

Region Site Tower 

Height 

(m) 

Latitude Longitude Elevation 

(m) 

22 



Period Of 

Record 

Wind 

Speed 

(m/s) 

Ilocos North Bayog 30 18 30 120 35 5 05/95-10/96 6.9 

Pagali 30 18 32 120 37 1 07/95-04/97 7.2 

Saoit 30 18 31 120 37 80 06/95-03/97 5.6 

Agaga 30 18 27 120 39 280 07/95-03/97 6.2 

Bangui 20 18 31 120 43 175 07/95-04/96 6.6 

Caparispisan 30 18 36 120 47 140 05/95-02/97 7.6 

Subec 30 18 36 120 49 80 06/95-03/97 7.7 

Mt. Province Sagada 30 17 06 120 52 1871 06/95-12/96 6.7 

Guimaras Is. Guimaras 30 10 32 122 39 160 06/95-05/97 5.0 

Romblon Is. Romblon 12 N/A N/A N/A 10/91-07/93 4.6 

Catanduanes Catanduanes 12 N/A N/A N/A 11/93-04/95 5.2 

Cuyo Is. Cuyo 12 N/A N/A N/A 11/93-03/95 4.7 

Guimaras Is. Guimaras 15.5 N/A N/A N/A 03/94-06/95 4.9 

Batanes Basco 12 N/A N/A N/A 04/94-08/94 6.3 

Table 5-3. Average Wind Speed (m/s) and Power (W/m 2 ) 

Site Average Wind 

Speed (m/s) 

Average Wind 

Power (W/m 2 ) 

Highest Monthly 



Lowest Monthly 



Bayog 6.9 510 1474 (Dec) 98 (Jun) 

Pagali 7.2 569 1378 (Dec) 79 (Jun) 

Saoit 5.6 266 623 (Dec) 83 (Jun) 

Agaga 6.2 393 1006 (Dec) 72 (Jun) 

Bangui* 6.6 425 1139 (Dec) 51 (Aug) 

Caparispisan 7.6 516 1001 (Dec) 179 (Jun) 

Subec 7.7 669 1813 (Dec) 110 (Jun) 

Sagada 6.7 356 977 (Dec) 67 (Apr) 

Guimaras 5.0 143 437 (Feb) 38 (Jun) 

* Bangui had insufficient data at the 30-m tower height. Values are based on 9 months of data at 20-m tower height. 

the coastal bluffs overlooking the ocean. Annual wind speeds at 30 m above ground level were 

7.7 m/s at Subec, 7.6 m/s at Caparispisan, and 6.2 m/s at Agaga. Again, there are significant 

differences in magnitude between the months with the highest and lowest average wind speeds. 

For example, at Subec, the highest monthly average wind speed is 13.2 m/s (December), while 

the lowest value is 3.8 m/s (June). At Caparispisan, the highest value is 11.3 m/s (December), 

and the lowest is 4.7 m/s (June). At Agaga, the highest value is 9.8 m/s (December), and the 

lowest is 3.6 m/s (June). For Subec, Caparispisan, and Agaga, the annual average wind powers 

are 669 W/m 2 , 518 W/m 2 , and 393 W/m 2 , respectively, with the highest values occurring in 

December and the lowest values in June. 

The frequency of occurrence of wind speed and direction for these six sites shows the 

predominant northeast flow in the late fall through early spring months (October to April) and the 

increased variability of wind directions in the summer months. The diurnal trend at these six sites 

shows a daytime maximum and nighttime minimum.

23 



The site at Sagada is also in northern Luzon; however, as a high-elevation, interior site, it has a 

very different exposure than the other sites. The site is northwest of the town of Sagada at an 

elevation of 1,871 m, and is on a north–south-oriented mountain range. The annual wind speed at 

30 m above ground level is 6.7 m/s, and the annual wind power is 356 W/m 2 . The monthly wind 

power ranges from 977 W/m 2 in December to 67 W/m 2 in April. The wind direction is 

predominantly from the northeast during the winter. However, during the summer, except for 

September, the wind direction is split evenly between east-northeast and west-southwest. The 

diurnal wind speed pattern is typical for a mountain site with, on average, little change from hour 

to hour. There is a slight increase in wind speeds during the nighttime hours during stable 

conditions and a decrease during the daytime, most likely due to instability and increased mixing. 

A 30-m tower was installed on Guimaras Island. The island is in the Guimaras Strait, southeast 

of Panay. The tower was installed on a small hill on the southeast quarter of the island, well 

away from the coast. The annual average wind speed and annual average wind power are 

marginal (5.0 m/s and 143 W/m 2 , respectively) for utility-scale power. However, the resource at 

this site may be sufficient for rural power applications. The frequency distribution of wind 

directions shows the typical predominance of northeast winds during the winter and the 

variability in wind directions during the summer. This particular site does show a pronounced 

peak in southwesterly wind directions during the late summer and early fall. 

NPC also provided monthly average wind speeds for five other sites. These data were measured 

on either 12-m- or 15.5-m-tall towers. The sites: Romblon Island in the Sibuyan Sea in the 

central part of the archipelago, Catanduanes on the eastern side of the archipelago, Cuyo Island in 

the Cuyo East Pass, and Basco on Batan Island north of Luzon, appear to have good wind 

resources. However, the relatively low measurement heights, poor data recovery, and missing 

months of data undermine the usefulness of the information. 

The NPC data has significant value for this study. The results of the 30-m-tower program 

indicate that there is good wind resource in the coastal region and higher interior mountains of 

northern Luzon. These data also yield valuable information on the diurnal trends in the wind 

speed and, consequently, the wind power. 

Wind Power (W/m 2 ) 

1500 

1000 

500 

0 

Jan 

Mar 

May 

Jul 

Month 

Sep 

Nov 

Wind Power Wind Speed 

12 

10 

8 

6 

4 

2 

0 

Figure 5.5 Monthly wind speed and power—Pagali 

Wind Speed (m/s)


5.2.3 DATSAV2 

1400 

1200 

1000 

800 

600 

400 

200 

0 

Jan 

Feb 

Mar 

Apr 

May 

Jun 

Figure 5.6 Monthly wind speed and power—Sagada 


1400 

1200 

1000 

800 

600 

400 

200 

0 

Jan 

Feb 

Figure 5.7 Monthly wind speed and power – Guimaras Island 

24 



There are data for 67 stations in the Philippine archipelago available from the climatic data set 

known as DATSAV2. We obtained the data set from the NCDC; it consists of hourly surface 

observations of meteorological variables. These observations were transmitted, for the most part, 

via the Global Telecommunications System (GTS). A map of the station locations, and the total 

number of observations for each station, was previously shown in Figure 3-1. 

The number of hourly observations within each year and from year to year for the individual sites 

is highly variable. Some stations, such as Clark Air Force Base (AFB), Olongapo, and Mactan 

International Airport, have approximately 8,760 hourly observations in each year. Other sites, 

Jul 

Month 

Aug 

Sep 

Oct 

Nov 


Mar 

Apr 

May 

Jun 

Jul 

Month 

Aug 

Sep 

Oct 

Nov 


Dec 

Dec 

12 

10 

8 

6 

4 

2 

0 

12 

10 

8 

6 

4 

2 

0 

Wind Speed (m/s) 

Wind Speed (m/s)

25 



such as Maasin on Leyte Island, have no more than 2,000 observations in any year and sometimes 

less than 500 observations. 

The data records for each of these stations were processed to produce monthly and annual 

averages of wind speed and power. The summarized data are presented in Table 5-4, and copies 

of the processed files are presented in Appendix B for selected stations. These data are useful for 

evaluating the inter-annual, monthly, and diurnal variability of wind speed and power, and the 

joint frequency of wind speed and wind direction. 

Visual inspection of the plots of the various wind characteristics data for each station sometimes 

revealed trends and peculiarities, particularly in the inter-annual variability. For example, the 

long-term average wind speed and power density at Cuyo Island from 1973 to 1996 was 3.5 m/s 

and 123 W/m 2 , respectively. However, an inspection of the yearly wind speeds and power 

densities from 1973 to 1996 reveals that the average wind speeds were about 5 m/s in the 1970s 

and had decreased to about 2 m/s by the mid-1990s. The wind power was in the range of 200 to 

300 W/m 2 in the 1970s and decreased to less than 20 W/m 2 by the mid-1990s. A long-term 

downward trend in wind speed and power at a station frequently indicates that either the site is 

becoming less exposed to the prevailing wind because of an increase in obstructions around the 

site or there is a degradation of the anemometer. Similar types of trends and peculiarities were 

found at many other stations in the Philippines. 

Although the average wind speeds and power densities are presented in Table 5-4 for each 

station, these data may not be a reliable indicator of the area’s wind resource because of problems 

with the data. Unfortunately, information on exposure of the wind measurement equipment and 

maintenance of the equipment is not available for meteorological stations in the Philippines, (nor 

most countries of the world, for that matter). With the various inherent problems in the reliability 

of the surface data from meteorological stations, using the appropriate upper-air data and ocean 

satellite data to characterize the ambient wind-flow characteristics and to develop the 

meteorological inputs for the wind mapping system becomes even more important. Nevertheless, 

screening the available surface data helps identify the most reliable data for evaluating the wind 

characteristics and helps validate the resource estimates generated by the mapping system. 

5.3 Upper-Air Data 

The upper-air data, consisting of wind speed and direction profiles, are an important component 

in the development of the wind resource projections. These data are available in either the ADP 

database or the Global Upper Air Climatic Atlas (GUACA). 

The upper-air database consists of information obtained from surface-launched meteorological 

instrument packages. These packages are usually launched once or twice daily, at 0000 GMT and 

1200 GMT, via balloon, and are managed under WMO guidance and procedures. There are 11 

locations in the Philippine archipelago where upper-air wind data are available from the ADP 

Database: Basco, Laoag, Baguio, Crow Valley, Clark AFB, Olongapo, Legaspi, Cebu, Puerto 

Princesa, Davao, and Zamboanga. These locations are shown in Figure 5-8. 

The GUACA data consist of monthly means and standard deviations of upper-air parameters for 

the mandatory pressure levels on a 2.5-degree global grid. The mandatory levels of interest 

include surface, 850 millibar (mb), 700 mb, and 500 mb.

26 



Vertical profiles of wind speed and direction are an important meteorological input parameter for 

the wind mapping. Therefore, the vertical profiles must reflect ambient regional atmospheric 

flow and not be subject to major blocking effects from terrain features. Unfortunately, of these 

11 stations, only the data from one (Legaspi) meet this particular requirement and could be used. 

Most of the stations could not be used because the local mountain ranges blocked the ambient 

flow. Some stations, such as Batanes, had insufficient data. Upper-air data from two stations 

near the Philippines were useful in estimating regional ambient vertical profiles. These stations 

were Pratas Island, located about 500 km west of Batanes, and Palau Island, located about 800 

km east of Mindanao. Summaries of the upper-air data for the three stations—Legaspi, Palau 

Island, and Pratas Island—are presented in Appendix C. 

The ADP data yielded profiles of monthly and annual average wind speed and frequency 

distributions of wind speed and direction for a number of pressure levels and height levels from 

the surface through 700 mb, or approximately 3,000 m. The ADP data was supplemented by the 

GUACA data, which expanded the analysis to cover the entire archipelago. 

5.4 Satellite Ocean Wind Data 

Because the Philippines is an archipelago, there is a large amount of water surface surrounding 

the country. The SSMI data set contains estimates of 10-m ocean wind speed measurements. 

These data also provide an excellent overview of the ambient wind conditions around the islands. 

The annual wind speeds for the 7-year period from 1988 to 1994, based on satellite data, are 

presented in Figure 5-9. The best wind speeds are along the northern Luzon coast, the Batanes 

and Babuyan Islands, the northeast coastal areas, and the southeast coast of Mindanao. The 

lowest annual average wind speeds occur in the Celebes Sea, west of Mindoro, and the westsouthwest 

coast of Luzon. The annual data imply the presence of wind corridors in the straits 

between Luzon and Mindoro, Mindoro and Panay, and Panay and Negros. 

The wind power density map (Figure 5-10) parallels the annual wind speeds with the highest 

density off the northwest coast of Luzon and the lowest density in the Celebes Sea. The SSMI 

data was also used to determine the Weibull k (shape) factor for the ocean areas. The k-value, 

shown in Figure 5-11, has a magnitude of 2.4–2.7 in the Batanes and Babuyan islands off the 

north coast of Luzon, a magnitude of 1.8–2.2 along the northeast coast, and a magnitude of 

1.8-2.2 off the north and east coasts of much of the Philippines from northern Luzon southward to 

northern Mindanao. 

The seasonal variation in wind speed and power density is dramatically illustrated for some areas 

in Figures 5-12 and 5-13. Plots for all of the areas are included in Appendix D. In December, 

monthly average wind speeds off the northern coast of Luzon exceed 11.0 m/s, and wind speeds 

are in the range of 8.0 to 10.0 m/s off the east and northeast coast of the archipelago. The wind 

corridors between the islands of Luzon and Mindoro, Mindoro and Panay, and Panay and Negros 

appear to have December monthly wind speeds in excess of 8.0 m/s. Also, the southeast corner 

of Mindanao Island appears to have December monthly average wind speed of 7.5 m/s.

Station 

WMO No. 

Table 5-4. Philippines’ Stations from DATSAV2 Files 

Station 

Name 

Latitude 

dd mm 

Longitude 

dd mm 

27 


Record 



Average 

WS 

(m/s) 

Average 


(W/m 2 ) 

984350 Alabat Is. 14 05 122 01 1973-96 2.9 49 

984320 Ambulong/Luzon 14 05 121 03 1973-96 1.6 14 

982320 Aparri/Luzon 18 22 121 38 1973-96 3.6 86 

983280 Baguio/Luzon 16 25 120 36 1973-96 2.0 24 

983330 Baler/Luzon 15 46 121 34 1973-96 2.1 36 

983260 Basa 14 59 120 29 1973-85 2.6 24 

981350 Basco/Batan Is. 20 27 121 58 1973-96 4.1 125 

985530 Borongan/Samar Is. 11 37 125 26 1973-87 2.2 26 

987520 Butuan/Mindanao is. 8 56 125 31 1981-96 1.2 12 

983300 Cabananatuan/Luzon 15 29 120 58 1990-96 1.7 17 

987480 Cagayan de Oro 8 29 124 38 1973-96 1.1 7 

984310 Calapan/Mindoro Is. 12 21 121 02 1973-96 2.1 26 

981330 Calayan Is. 19 16 121 28 1973-96 3.0 54 

983360 Casiguran /Luzon 16 17 122 07 1973-96 1.7 30 

984470 Cataduanes Radar 13 59 124 19 1973-96 3.7 71 

985460 Catarman/Samar 12 29 124 38 1973-96 2.1 36 

985480 Catbalogan/Samar Is. 11 47 124 53 1973-96 1.1 11 

983270 Clark 15 11 120 33 1973-91 1.9 16 

985260 Coron/Calamin 12 00 120 12 1973-96 1.6 13 

987460 Cotabato 7 10 124 13 1986-96 2.2 24 

983220 Crow Valley 15 19 120 23 1975-90 2.2 17 

986300 Cuyo Is. 10 51 121 02 1973-96 3.5 123 

984390 Daet 14 07 122 57 1973-93 2.0 18 

984400 Daet 14 08 122 59 1974-96 3.4 80 

983250 Dagupan/Luzon 16 03 120 20 1973-96 2.6 45 

987540 Davao 7 04 125 36 1973-75 2.2 31 

987530 Davao 7 07 125 39 1974-96 1.5 12 

987410 Dipolog/Mindanao 8 36 123 21 1973-96 1.6 14 

986420 Dumaguette.Negros Is. 9 18 123 18 1973-96 1.6 18 

988510 General Santos 6 07 125 11 1973-96 1.4 12 

985580 Guiuan/Samar Is. 11 02 125 44 1974-96 3.7 102 

987550 Hinatuan/Mindanao 8 22 126 20 1973-96 2.1 23 

983240 Iba/Luzon 15 20 119 58 1973-96 3.0 52 

986370 Iloilo/Panay Is. 10 42 122 34 1973-96 3.1 49 

984340 Infanta/Luzon 14 45 121 39 1973-96 1.8 23 

981320 Itbayat Is. 20 48 121 51 1973-96 3.6 70 

988300 Jolo Is. 6 03 121 00 1973-90 1.1 11 

982230 Laoag 18 11 120 32 1973-96 2.6 37 

984440 Legaspi/Luzon Is. 13 08 123 44 1973-96 2.8 42 

987470 Lumbia Airport 8 26 124 17 1977-96 2.1 17 

986480 Maasin/Leyte Is. 10 08 124 50 1973-96 2.3 22 

985430 Macatan/Masbate 12 22 123 37 1973-96 2.3 27 

986460 Mactan 10 18 123 58 1973-96 2.5 30

Station 

WMO No. 

Table 5-4 Philippines’ Stations from DATSAV2 Files (continued) 

Station 

Name 

Latitude 

dd mm 

Longitude 

dd mm 

28 


Record 



Average 

WS 

(m/s) 

Average 


(W/m 2 ) 

987510 Malaybalay Is./Mindanao 8 09 125 05 1973-96 0.9 5 

984250 Manila 14 35 120 59 1978-96 2.7 49 

984375 Marinduque Is. 13 22 121 50 1984-91 6.3 242 

983290 Munoz/Luzon 15 43 120 54 1973-96 2.2 29 

986020 Nanshan Is. 10 43 115 49 1983-89 4.4 131 

984295 Nichols 14 31 121 01 1973-85 3.2 48 

984290 Ninoy Aquino 14 31 121 00 1973-96 3.6 165 

984260 Olongapo 14 48 120 16 1973-96 3.2 52 

985010 Pagasa Is. 11 01 114 10 1979-81 4.3 114 

986180 Puerto Princesa 9 45 118 44 1973-96 1.8 22 

984300 Quezon City 14 38 121 01 1973-96 1.4 18 

985360 Romblon/Tablas Is. 12 35 122 16 1973-96 2.8 47 

985380 Roxas/Panay Is. 11 35 122 45 1973-96 3.3 51 

984370 San Francisco 13 22 122 31 1985-96 2.7 45 

984310 San Jose/Mindoro Is. 12 21 121 02 1981-96 3.0 58 

984280 Sangley Point 14 30 120 55 1974-96 2.7 41 

986530 Surigao/Mindanao 9 48 125 30 1973-96 2.4 26 

985500 Tacloban/Leyte Is. 11 15 125 00 1973-96 1.8 23 

986440 Tagbilaran 9 36 123 51 1973-96 1.4 13 

984270 Tayabas 14 02 121 35 1973-96 1.6 19 

982330 Tuguegardo/Luzon 17 37 121 44 1973-96 1.9 42 

982220 Vigan/Luzon 17 34 120 23 1973-96 2.6 44 

984460 Virac/Catanduanes Is. 13 35 124 14 1973-96 3.1 60 

988360 Zamboanga 6 54 122 04 1973-96 1.7 18 

The wind power density in December exceeds 1200 W/m 2 off the northwest tip of Luzon. The 

wind power density in December is also quite good along the northeastern and eastern coast of 

the archipelago and along the wind corridors between the islands. 

In August, under the southwest monsoon conditions, the wind resource is substantially less across 

the archipelago. The northwest coast of Luzon continues to have a good wind resource with wind 

speeds of 6.5–7.0 m/s. There are also good areas of wind resource in August off the southeast 

Mindanao coast, with wind speeds of 7.0–8.0 m/s. The wind resource along the northeast Luzon 

coast is substantially less in August, because the terrain blocks the prevailing southwest monsoon 

flow. The analysis of the satellite wind-speed data indicates the highest wind power density in 

August is off the southeast coast of Mindanao and the northern portion of the Sibuyan Sea.

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

5.5 Wind Resource Distribution and Characteristics 

5.5.1 Annual Wind Resource Distribution 



The wind resource over the Philippines varies considerably and is strongly dependent on three 

main factors: latitude, topography or elevation, and proximity to the coastline. 

According to the wind speed and power density computed from the satellite ocean wind data, the 

best annual wind resource is in the islands of Batanes Province north of Luzon; the north and 

northwest coast of Luzon; the northeast- and east-facing coasts of Luzon and Samar; the southeast 

coast of Mindanao; and the straits between Mindoro and Luzon, Mindoro and Panay, and Panay 

and Negros. The satellite wind data and wind power density shows, in general, a strong 

relationship between latitude and the resource (Figure 5-9). Wind power density ranges from 

500–600 W/m 2 along the northwest Luzon coast (Figure 5-10) to 250-350 W/m 2 between 

Mindoro and Panay, 250–300 W/m 2 along the eastern coast of Luzon and the northern coast of 

Samar, and less than 100 W/m 2 off the southwest coast of Mindanao. 

The NPC wind data, presented in Tables 5-2 and 5-3, show that hilly areas along the immediate 

coast of northern Luzon in Ilocos Norte, and at one interior ridge top in Mountain Province, have 

a good annual wind resource. At the seven monitoring sites in Ilocos Norte, the annual average 

wind speed over the period of record ranges from 5.7 m/s (Saoit) to 7.7 m/s (Subec). The average 

annual wind power density ranges from 267 W/m 2 to 669 W/m 2 . At the ridge top site (Sagada), 

with an elevation of 1,871 m, the annual average wind speed at 30 m above ground level was 7.1 

m/s, and the power density was 393 W/m 2 . 

5.5.2 Seasonal Wind Resource Distribution 

The satellite ocean wind data were processed to compare the seasonal distribution of the wind 

resource among the different regions of the Philippines. Plots of the monthly average wind 

speeds and power densities are shown for some areas in Figures 5-12 and 5-13 and for all areas in 

Appendix D. Through an examination of these plots, some conclusions can be made regarding 

patterns for the seasonal wind resource in the coastal regions and offshore islands of the 

Philippines. 

Throughout most of the Philippines, the highest wind resource occurs from November through 

February and the lowest from April through September. However, there are some significant 

regional differences in the seasonal variability. For example, the months with the highest wind 

resource are October through February in the northern Philippines, and November through March 

in much of the central and southern Philippines. Two regions of the Philippines—the 

southeastern Mindanao coast and the western coast of Palawan—have a relatively high wind 

resource during the southwest monsoon, about as high as that of the northeast monsoon. In all 

other regions with significant wind resource potential, the wind resource during the northeast 

monsoon is considerably greater than that during the southwest monsoon. 

The analysis of surface wind-resource data from meteorological stations may or may not provide 

reliable indications of the seasonal variation at exposed sites in the area. For example, long-term 

wind data (1973–1996) from the meteorological station at Basco in Batanes Province indicate that 

the month with the highest wind resource is August, during the peak of the southwest monsoon. 

However, the seasonal pattern of wind resource at the meteorological station is substantially 

35

36 



different from that of the ocean satellite wind data for the Batanes region. The satellite data 

indicate that the wind-power density during the northeast monsoon (October through February) is 

in the range of 400–600 W/m 2 , whereas, during the southwest monsoon (July and August), the 

wind power density is in the range of 200–300 W/m 2 . The wind power measured at the Basco 

meteorological station is almost as great as that indicated by the satellite data during the 

southwest monsoon. However, during the northeast monsoon, the wind power at the 

meteorological station averages only about one-fourth that of the satellite data. From an 

inspection of topographic maps, it appears that the meteorological station is blocked from the 

northeast monsoon flow by a mountain upwind. This probably explains the peculiar seasonal 

pattern observed at the meteorological station and the severely reduced wind power during the 

northeast monsoon season. 

The pronounced seasonal variation in the wind resource is also seen in Figures 5-5 to 5-7 

(previously presented). These data, from the NPC sites at Pagali (coastal) and Sagada (inland, 

elevated) clearly show that both wind speed and power reach their minimums in the late spring to 

late summer, with June having the lowest values. The wind resource increases beginning in 

October, reaches a peak in December, and gradually decreases through the spring. For Guimaras 

Island, the peak wind speeds occur in February, later than they do in northern Luzon. 

5.5.3 Diurnal Wind Speed Distribution 

The diurnal wind speed distribution, or wind speed versus time of day, is influenced by site 

elevation and proximity to the Pacific Ocean. The distribution at low-elevation, inland sites in 

simple terrain typically reveals a maximum wind speed during the afternoon and a minimum near 

sunrise. The primary forcing mechanism for this pattern is the daytime heating, which 

destabilizes the lower levels of the atmosphere, resulting in a downward transfer of momentum to 

the surface. The near-surface winds tend to peak in the early afternoon, which corresponds to the 

time of maximum heating. In the late afternoon and evening, the declining supply of sunshine 

leads to surface cooling and a decoupling of the thermally forced momentum exchange. Surface 

winds begin to decelerate, while winds aloft, previously restrained by friction, are free to 

accelerate. The minimum in surface wind speed near sunrise corresponds to the time of 

maximum atmospheric stability. The chart of speed and power by hour in Appendix A for the 

NPC sites in Ilocos Norte shows this phenomenon. From an early morning minimum, wind 

speeds increase rapidly following sunrise, reaching a peak during the mid-afternoon. Winds 

decrease until after sunset and then remain steady during the late night and early morning hours. 

Mountaintop diurnal distributions differ from those of low-elevation sites. The strongest winds at 

mountain locations occur at night, while the lowest wind speeds are observed during the midday 

hours. The chart for Sagada, showing speed and power by the hour, is included in Appendix A. 

The chart shows a well-defined maximum late at night and a minimum during the mid-afternoon. 

Over the ocean, the diurnal variation of the atmospheric instability is typically reversed, resulting 

in a wind speed maximum at night and a minimum in the afternoon. However, diurnal wind 

speed changes are more complicated on the islands. The curves of average diurnal wind speed 

for island sites are often flatter than those observed over land. The plots of wind speed and power 

by hour for Guimaras and Cuyo Islands show a general peak during the early afternoon and a 

relative minimum during the night. The distribution is relatively flat for Cuyo Island, varying by 

less than 3 m/s, but is much more pronounced for Guimaras Island.

37 



The magnitude of the diurnal variation is a function of the season, elevation, and influence of the 

ocean. From the NPC data, the seven stations in Ilocos Norte show a more pronounced diurnal 

variation in the winter and slightly less in the summer. For the high elevation site, the diurnal 

variation is also more pronounced during the winter and less so in the summer. For the island 

sites, Cuyo and Guimaras, the diurnal variations are greater during the winter than the summer. 

5.5.4 Wind Direction Frequency Distribution 

The wind speed frequency distribution at a site in the Philippines is influenced principally by the 

northeast and southwest monsoons and secondarily by latitude and elevation. 

Appendix B contains data from the DATSAV2 database, including the hourly wind speed and 

wind direction data for Daet on Luzon, Guiuan on Samar Island, and Cuyo Island. On an annual 

basis, the wind is from the northeast nearly 25% of the time at Daet, 28% of the time at Guiuan, 

and more than 40% at Cuyo Island. The wind direction is southwest approximately 20% of the 

time at Cuyo Island; however, the southwest wind direction is not as pronounced at Daet or 

Guiuan. On a monthly basis, the predominance of the monsoon flow can clearly be seen. For 

Daet on Luzon, the wind direction is either northeast or east from December to April and south or 

southwest in August. The other months are transitional months with a mix of wind directions as 

the different monsoon flows become established. The pattern is slightly different at Guiuan, with 

a predominant northeast or east wind direction extending from November to May and southwest 

or west winds from July through September. For Cuyo Island, the wind direction is exclusively 

northeast from November to March and principally southwest from June through September. 

The NPC data (Appendix A) from the stations in Ilocos Norte show a slightly different 

distribution of wind directions. On an annual basis, four stations—Bayog, Caparispisan, Pagali, 

and Saoit—show that nearly 30% of the time the wind is from the northeast or east. On a 

monthly basis, these four sites show that northeast wind directions predominate from October 

through April and then become much more variable from May through September. The northeast 

wind direction is associated with the best wind resource; that is, the highest monthly wind speeds 

and highest wind power density, for Ilocos Norte. For two other stations, Agaga and Subec, a 

predominately north component is indicated. This could be due to a local effect or, more likely, 

to faulty wind direction data in the data set. At Sagada, the interior mountain site in Mountain 

Province, on an annual basis, the wind directions are from the north 20% of the time, northeast 

25% of the time, and west 7.5% of the time. On a monthly basis, the wind direction is 

predominately east-northeast from January to March with a secondary peak from the west. From 

April to August, the wind directions are evenly distributed, either east-northeast or west 35% to 

40 % of the time, with the remainder spread over the other directions. This site also indicated a 

significant northerly component to the wind direction distribution from September to December. 

Again, this could be due to a local effect, or more likely, to faulty wind direction data in the data 

set.

38 



6.0 Wind Mapping and Identification of Resource Areas 


This section presents an overview of the input data files, the results of the wind mapping, and 

wind-power density estimates for the Philippines. Two classification schemes for wind power 

density are used: one for wind power technology in rural areas and one for utility-scale 

applications. A description of the detailed meteorological data files is also presented. We used 

22 different wind profiles in the modeling study, because of the large variability of the 

meteorological attributes across the archipelago. 

To portray the mapping results, the Philippine archipelago was divided into 13 regions. Each 

region covered an area approximately 300 km by 300 km. The regional divisions were 

determined principally on the geography of the archipelago and the desire to maintain the same 

map scale for each region. 

6.2 Wind Power Classifications 

The wind power classifications for the Philippines are presented in Table 6-1. Two different 

classifications are used in the analysis: one for utility-scale applications and one for rural power 

applications. For utility-scale applications, areas with a Class 2 and higher resource potential are 

considered suitable for wind power development. For rural applications, areas with a Class 1 or 

higher are considered suitable for wind power development. In reviewing the mapping results, it 

is important to keep these classifications separate, because an area considered marginal from a 

utility-scale-application point of view is considered moderate from a rural power application 

point of view. 


Utility Rural 

Table 6-1. Wind Power Classification 



@ 30 m 


(m/s) @ 30 m 

1 Marginal Moderate 100 - 200 4.4 - 5.6 

2 Moderate Good 200 - 300 5.6 - 6.4 

3 Good Excellent 300 - 400 6.4 - 7.0 



6 Excellent Excellent 800 -1200 8.8 -10.1 



20%, depending on the actual wind speed distribution (or Weibull k value) and elevation above sea level. 

6.3 Approach 

We previously presented the description of the mapping methodology in Section 4.0. NREL 

prepared the digital terrain data set from the DEM information for the Philippines. NREL also 

prepared the meteorological data files necessary for the modeling analysis. These meteorological

39 



data files included vertical wind profiles, wind power roses that express the percentage of total 

wind-power density by direction sector, and open-ocean wind power density. The vertical 

profiles are broken down into 100-m intervals and centered every 100 m above sea level, except 

for the lowest layer, which is at 50 meters. 

The vertical profiles were carefully determined, based primarily on the upper-air data, and then 

subjectively modified to derive the final profiles for 22 specific geographic zones. Wind roses 

were developed to account for the effects of short-range (less than 10 km), medium-range (10–50 

km), and long-range (>50 km) blocking of the ambient wind flow by terrain. For this analysis, 

we incorporated the medium- and short-range blocking into one wind rose and the long-range 

blocking into a second wind rose. 

6.4 Mapping Regions 

The Philippine archipelago is divided into 13 regions. These regions are presented in Figure 6-1. 

The regions are: 

1) Batanes and Babuyan 

2) Northern Luzon 

3) Central Luzon 

4) Mindoro, Southern Luzon, Romblon, and Marinduque 

5) Southeastern Luzon, Catanduanes, and Masbate 

6) Samar and Leyte 

7) Panay, Negros, Cebu, and Siquijor 

8) Northern Mindanao and Bohol 

9) Southern Mindanao 

10) Western Mindanao and Basilan 

11) Northern Palawan 

12) Southern Palawan 

13) Sulu, Basilan, and Tawi-Tawi 

6.5 Mapping Results 

6.5.1 Batanes and Babuyan 

This region is the northernmost land area in the Philippines and consists of eight large islands— 

Itbayat, Batan, Sabtang, Babuyan, Calayan, Dalupiri, Fuga, and Camiguin—and numerous 

smaller islands. There are areas with good-to-excellent wind resource on each of these islands for 

both rural and utility-scale applications. Figures 6-2, 6-3, and 6-4 illustrate the significant 

political features, topography, and potential wind resource of this region. 

On Itbayat Island, the wind resource is rated excellent (500–700 W/m 2 ) at the northeast tip of the 

island and good elsewhere. On Batan Island, there is an area of excellent resource at Rocavato 

Point and the higher terrain on the south end of the island. Coastal areas along the southeast and 

south end of the island are considered to have a good wind resource. The inland area at the north 

end of the island, north and east of the town of Basco, is considered to have a poor wind resource.

40 



In a similar fashion, the higher terrain in the north-central part of Sabtang Island has an excellent 

resource, and the north-, east-, and south-facing coastal areas have a good wind resource. The 

only area considered to have a poor wind resource is the central-west side of the island, which is 

sheltered from the prevailing easterly flow. For Babuyan Island, an excellent wind resource 

exists in the higher, central portion of the island, while a good-to-excellent wind resource exists 

on the coastal portions of the northeast cape, the southern tip, and the western cape. 

For Camiguin Island, an excellent wind resource exists on the interior high terrain and at the 

southern tip (Genlous Point). A moderate-to-good wind resource exists along all coastal sections 

with better resources at Machibat Point and Nagayaman Point. For Calayan Island, the interior 

hills and ridges have an excellent wind resource with good-to-excellent resources along the 

northern and eastern coastline including Priddan Point, Batang Point, and Tumulod Point. The 

wind resource on Dalupiri Island and Fuga Island is rated excellent on the interior elevations and 

good to excellent across the coastal and interior areas of each island. 

6.5.2 Northern Luzon 

The significant political features, topography, and potential wind resource of northern Luzon are 

illustrated in Figures 6-5, 6-6, and 6-7. The wind resource in northern Luzon is confined to the 

eastern, northern, and northwestern coastal sections; coastal hills; and interior high-elevation 

areas. The flat coastal sections, from the coastline to several kilometers inland, are classified as 

having a marginal wind resource for utility-scale applications and a good resource for rural power 

applications. The area inland (south) from Aparri along the Cagayan River is also classified as 

moderate for rural wind power applications. 

For the coastal sections, areas with a better wind resource include the capes at Bangui Bay and 

Pasaleng Bay, Palaui Island, the coastline between Escarpada Point and Matador Point, Palanan 

Bay, and the peninsula on the east coast near Casiguran. 

Good-to-excellent wind resources exist in Ilocos Norte in the coastal hills extending from Agaga 

to Dumalneg. This resource is generally confirmed by the NPC sites installed in this area. The 

wind-power-density measurements ranged from 267 W/m 2 at Saoit to 669 W/m 2 at Subec. Goodto-excellent 

wind resources are found in the Sierra Madre Mountains extending north to south 

along the eastern coast of northern Luzon and the Cordillera Central Mountains in the interior of 

Luzon. An area of moderate-to-good wind resource potential is found in the lake region 

northwest of Cabarroquis. The interior plains along the Cagayan River and from Lingayen Gulf 

past Tarlac have a poor wind resource, even for rural power applications. 

Other areas with a moderate wind resource for rural power applications are the western and 

northern coastal plains of the Province of Pangasinan in the southwest part of northern Luzon. 

The hills and mountains extending south-southeast from Burgos to Mt. Iba are classified as 

having a good-to-excellent resource. 

6.5.3 Central Luzon 

The significant political features, topography, and wind mapping results for Central Luzon are 

illustrated in Figures 6-8, 6-9, and 6-10. The Central Luzon region encompasses the area from 

16.5 degrees to 13.5 degrees north latitude and includes metropolitan areas surrounding Manila. 

The wind resource in the flat interior and coastal sections of this area is generally moderate to 

good for rural power applications and marginal to moderate for utility-scale applications. The

41 



area surrounding Manila Bay and extending north to Cabanatuan fits this description. Good-toexcellent 

wind resources are evident in the mountain chain running north–south into Bataan, the 

high terrain north and southeast of Lake Taal, and the higher terrain southeast of Batangas. 

Good-to-excellent wind resources are evident in the mountains in the provinces of Bulacan, Rizal, 

and Quezon. The east-to-west-oriented ridgelines near Lamon Bay are also classified as having a 

good-to-excellent resource. Both Polillo Island, to the east of Central Luzon, and Lubang Island, 

to the southwest, have extensive areas of moderate-to-good wind resource. The majority of the 

coastal and interior areas of the isthmus and peninsula between Tayabas Bay and Ragay Gulf, as 

well as Alabat Island, have a marginal-to-moderate wind resource (utility scale) and a moderateto-good 

resource (rural power scale). A good-to-excellent wind resource exists in the higher 

terrain at the southern end of the peninsula east of San Francisco, at Dapdap Point, and the higher 

terrain surrounding Mt. Cadig. 

6.5.4 Mindoro, Southern Luzon, Romblon, and Marinduque 

The significant political features, topography, and wind mapping results for this region are 

illustrated in Figures 6-11, 6-12, and 6-13. Mindoro, a large island in the Philippines archipelago, 

centered at 13 degrees north and 121 degrees east, is divided into two provinces, Occidental 

Mindoro and Oriental Mindoro. The topography consists of a coastal plain and a high mountain 

interior. Except in certain specific locations, the island has a limited developable wind resource. 

However, good-to-moderate wind resources for rural power applications can be found in several 

areas of the region: the northeast portion near Balingawan Point and Dumali Point, the northwest 

corner of the island at Calisurigan Point, along the southeast coastal sections from Soguicay Bay 

to Buruncan Point, and around Ilin Island on the south-southwest. Good-to-excellent wind 

resources are evident along the central mountain range from Tandrac Peak in the north to just 

north of Bulalakao in the south. Another area of good-to-excellent wind resource is evident in the 

high terrain north of Mamburao in the northwest and near Tusk Peak in the southwest. The 

Semirara Islands south of Mindoro have a uniformly good-to-excellent wind resource across all 

three islands. 

A similar wind resource pattern is evident in the Romblon Island group—Sibuyan, Tablas, 

Carabao and Romblon. On Sibuyan Island, a good-to-excellent wind resource is evident on the 

high terrain in the eastern and central part of the island. A limited area of moderate-to-good wind 

resource for rural power applications exists on the immediate north coast. On Romblon Island 

itself, a moderate-to-good wind resource extends from north to south along the central part of the 

island. On Tablas Island, a moderate-to-good wind resource exists on the southwest and southern 

plains extending from Odiongan to Cabalian Point. A good-to-excellent wind resource occurs in 

the high mountains along the eastern side of the island. On Carabao Island, the wind resource 

across the entire island is classified as excellent for rural power applications. 

The northwest, north, and east coastal sections of Marinduque have a moderate-to-good wind 

resource for rural power applications and marginal to moderate for utility-scale power 

applications. Good-to-excellent wind resources are evident from Mogpog in the north to Suban 

Point in the south, along the interior mountain ranges on the eastern and southwestern sides of the 

island. 

The wind resource in the portion of Luzon presented in Figure 6-13 was previously discussed in 

Section 6.5.4.

6.5.5 Southeastern Luzon, Catanduanes and Masbate 

42 



The significant political features, topography, and wind mapping results for Southeastern Luzon, 

Catanduanes, and Masbate are illustrated in Figures 6-14, 6-15, and 6-16. Southeastern Luzon 

includes the provinces of Camarines Norte, Camarines Sur, Albay, and portions of Sorsogon. 

The coastal areas, including several kilometers inland, as well as the plains south of San Miguel 

Bay and the plains west and south of Legaspi, have a marginal-to-moderate resource for utilityscale 

power applications and a moderate-to-good resource for rural power applications. Other 

areas in Sorsogon having a similar resource include the coastal area and interior plains from 

Prieto Diaz to Barcellona, westward to Casiguran. 

The best wind resource in the coastal areas is found at Gumaus Point in Camarines Norte, near 

Daet; on Camarines Sur, at Quinabucasan Point southeast to Maslog; at the far eastern end of the 

province at Rungus Point; and at Prieto Diaz and San Jose in Sorsogon. Good-to-excellent wind 

resources exist in the high interior areas of the provinces near Mt. Cadig, Mt Labo, the mountains 

west of San Miguel Bay, Mt Isarog, the east–west-oriented mountain chain from Buludan to 

Bitaogan in Camarines Sur, and the mountains in Albay and Sorsogon. 

The wind resource on San Miguel Island, Gagrary Island, Batan Island, and Rapu Rapu Island are 

also rated moderate to good for rural power applications and marginal to moderate for utilityscale 

power applications. The best resources are found on the higher terrain of Batan Island and 

Rapu Rapu Island. 

The Province of Catanduanes is located directly east of Camarines Sur. A moderate-to-good 

wind resource for rural power applications and marginal-to-moderate for utility-scale power 

applications exists along the north, east, and south coastal sections of the province. The best 

coastal resources appear to be at Binorong Point and Nagumbuaya Point, in the southeast part of 

the island, and at Virac Point in the south. A good-to-excellent wind resource exists on the higher 

terrain in the north-central part of the island, on the eastern side of the island west of Gigmoto, at 

the southern end in the higher terrain north of Virac, and in the terrain east of Codon in the 

southwest part of the island. 

Masbate includes three separate islands—Burias, Ticao, and Masbate. The distribution of wind 

resource is very similar to other areas of the Philippines: the best resource is on the highest 

terrain. For Burias Island, the north-, east- and south-facing coastal sections have, in general, a 

moderate-to-good wind resource for rural power applications and a marginal-to-moderate 

resource for utility-scale power applications. The coastal and interior plains at the north end of 

the island and in the center have a similar resource. A good-to-excellent resource for rural power 

applications (moderate to good for utility-scale applications) is indicated at the far north end of 

the island and in the northwest. The best wind resource is associated with the higher terrain in the 

central part of the island near Dancalan and in the south around Mt. Enganoso and Maputing 

Baybay. 

Ticao Island has a similar distribution of resources with a moderate-to-good wind resource for 

rural power applications and a marginal-to-moderate resource for utility-scale power applications 

along east-facing coastal sections. However, the best wind resource is on the highest terrain in 

the northwest part of the island, but this only ranks as good for utility-scale applications. 

Masbate also has large areas classified as moderate to good for rural power applications and 

marginal to moderate for utility-scale power applications. This includes all coastal sections and

43 



the plains in the southwestern and northwestern parts of the island. A moderate-to-good resource 

exists at Cadurnan Point at the southern tip of the island, the high terrain northwest of Cataingan, 

and the high terrain directly south of the town of Masbate. The best resource on the island is the 

high terrain directly west of Masbate and north of Milagros. 

6.5.6 Samar and Leyte 

The significant political features, topography, and wind mapping results for Samar and Leyte are 

illustrated in Figures 6-17, 6-18, and 6-19. As in Southeastern Luzon, there is a good distribution 

of wind resources across the island. The coastal sections, including inland areas across the 

interior plains and the islands on the western side of Samar in the Samar Sea, have a moderate-togood 

wind resource for rural power applications and a marginal-to-moderate resource for utilityscale 

power applications. In the coastal sections, the best wind resource, classified as good for 

utility-scale applications and excellent for village power applications, is on the northwest tip of 

the island, near and including Biri Island, and the northern tip of the island, including Batag 

Island. Good resources at coastal locations are also found at Bunga Point on the eastern side of 

the island, Tugnug Point on the southeastern part of the island, and near the Town of Mercedes 

and Calicon Island in the south. The best wind resources on Samar, good to excellent from the 

utility-scale classification, are found in the northwest on the high terrain southwest of Catarman 

and the mountains in the central interior (Mt. Bingo, Mt. Canyaba, and Mt. Cabalantina). A good 

wind resource is also found on the interior high terrain in the southern part of the island. 

Compared to Samar, the coastal sections of Leyte generally have less wind resource, as can be 

seen in Figure 6-19. A moderate-to-good wind resource for rural power applications and a 

marginal-to-moderate resource for utility-scale power applications exists in the plains at the north 

end of Leyte, the north coast around Capoocan, the northeast corner near Rizal, and the southern 

end of Leyte, near Himayanan and Liloan. The best wind resource, much like on Samar, exists in 

the interior high terrain extending through the center of the island from the area north of Mt. Lobi 

to the high terrain west of Sogod Bay at the south end. 

6.5.7 Panay, Negros, Cebu, and Siquijor 

The significant political features, topography, and wind mapping results for Panay, Negros, Cebu, 

and Siquijor are illustrated in Figures 6-20, 6-21, and 6-22. A moderate-to-good wind resource 

for rural power applications and a marginal-to-moderate resource for utility-scale power 

applications exists along the north coastline along Jintotolo Channel and southeast coastlines of 

the island along Guimaras Strait, including Guimaras Island. A better wind resource in the 

coastal areas includes Potol Point in the far northwest, the areas east and south of Roxas, the 

northeast point near Balasam, southeast near Concepcion, north of Iloilo City, and in the far south 

at Naso Point. A good wind resource is found in the mountains (Mt. Agudo and Mt. Lantuan) in 

the northeast and the east (Mt. Caniapasan). The best wind resource on Panay is in the northsouth-oriented 

mountain range along the western side of the island. 

On Negros, a moderate-to-good wind resource for rural power applications and a marginal-tomoderate 

resource for utility-scale power applications exists along the northwest coastline of 

Guimaras Strait, including the area around Bacolod; the northeast area near Sagay Point; the eastwest 

coastline in the Panay Gulf from Sojoton Point to Diut Point; and the west-facing coastline 

from Binigsian Point to Matatindoe Point. Moderate-to-good wind resources occur in the hilly 

terrain in the southwest part of the island; however, the best wind resources occur in the high 

terrain in the north end of the island and along the eastern interior. This includes the areas around

44 



Mt. Silay, Mt. Mandalagan, and Canlaon Volcan in the north; from Razor Back Mountain along 

the eastern side of the island to just southwest of Bais; and in the southern part of the island 

around Cuemos de Negros and Dome Peak. 

For Cebu, a moderate-to-good wind resource for rural power applications and a marginal-tomoderate 

resource for utility-scale power applications exists across the north end of the island 

from Bulalquit Point south to the beginning of the higher terrain near Sogod; east of Cebu City, 

including Mactan Island; and in selected areas on the west coast along the Tanon Strait, especially 

around Alcantara. A good-to-excellent wind resource exists in the hills and mountains, including 

Mt. Lanibga, Mt. Cabalasan, and Mt. Uling, which run north to south along the length of the 

island. 

Siquijor Island sits at the confluence of the Bohol Strait, the Cebu Strait, and the Tanon Strait. 

The indicated wind resource on the island is very similar to the nearby islands except that it does 

not have the higher terrain needed to accelerate the wind power density from the marginal-tomoderate 

classification into a higher category. A moderate-to-good wind resource for rural 

power applications and a marginal-to-moderate resource for utility-scale power applications 

exists at Tongo Point to the west, Sandagan Point in the north, Daquit Point in the east, and east 

of Minalulan. The best wind resource, classified as good for utility-scale applications, occurs on 

the hills that run generally west to east across the island. 

6.5.8 Northern Mindanao and Bohol 

The significant political features, topography, and wind mapping results for Northern Mindanao 

and Bohol are illustrated in Figures 6-23, 6-24, and 6-25. For Bohol, a good-to-excellent wind 

resource is present on the high terrain in the southeast part of the island. Good wind resources 

occur in the high terrain at the eastern end of the island, near Talisay, and in the southwestern part 

of the island, east of Cruz Point. A moderate-to-good wind resource for rural power applications 

and marginal-to-moderate for utility-scale power applications exists in the northern third of 

Bohol, from Mahanay Island in the west to Lapining Island in the east, and south to Dagohoy in 

the central interior. A similar resource exists across most of the southern interior plains extending 

southwestward to Panglao Island. 

Northern Mindanao lacks a consistent, widespread wind resource, principally due to the latitude 

and the resultant lower wind speeds over the ocean. However, because of the accelerating effects 

of the terrain, there are a limited number of areas with a usable wind resource. A good-toexcellent 

wind resource occurs at the crest of a long, narrow mountain range that extends from 

Macopa in Surigao del Norte to west of Lake Mainit in Agusan del Norte. A good wind resource 

also exists in the higher terrain east of Lake Mainit in Surigao del Norte, Surigao del Sur, Agusan 

del Norte, and Agusan del Sur. 

The high terrain extends from Mt Legaspi in the north to Mt. Divata in the south and eastnortheast 

to Canit Point. Other good wind resource areas are scattered in the higher terrain on the 

eastern side of northern Mindanao. The resource is considered marginal (utility-scale) to 

moderate (rural power), on the successive ridgelines progressing from east to west. Siargao 

Island, Dinagat Island, the area around Surigao, the east coast from Tandag to Jobo Point and 

from Bakulin Point to Lamon Point, and Taglo Point, northeast of Dipolog, all exhibit a marginalto-moderate 

wind resource. For other areas in northern Mindanao, the wind resource is classified 

as poor.

6.5.9 Southern Mindanao 

45 



The significant political features, topography, and wind mapping results for Southern Mindanao 

are illustrated in Figures 6-26, 6-27, and 6-28. This region, defined as Southern Mindanao, 

extends from Lanao del Sur on the west to Davao Oriental on the east, and from northern 

Cotabato in the north to Davao del Sur in the south. A marginal (utility-scale) wind resource 

exists in some east-facing coastal sections in Davao Oriental from Pusan Point to Tugubun Point 

near Mayo Bay and Cape San Augustin. The best wind resource areas, principally good (utilityscale) 

to excellent (rural scale), in Southern Mindanao are the higher terrain areas east of Davao 

Gulf, along the mountains that separate Davao del Sur from southern Cotabato, west of Sarangani 

Bay, and west of Isulan. Two locations, Sharp Peak and Saddle Peak, in Davao del Sur, are 

classified as having an excellent wind resource. The large interior valley, extending from 

Cotabato City, Maguindanao, in the northwest to Koronadal, southern Cotabato, in the southeast, 

is considered to have a poor wind resource for either rural or utility applications. 

6.5.10 Western Mindanao and Basilan 

The significant political features, topography, and wind mapping results for Western Mindanao 

and Basilan are illustrated in Figures 6-29, 6-30, and 6-31. The wind resource is classified as 

moderate for rural power applications and marginal for utility-scale applications. The areas with 

this limited resource include the coastal areas immediately northeast of Dipolog, the coastal areas 

near Patauag, and the higher terrain in the interior of Mindanao. A similar, limited wind resource 

exists on the higher terrain on Basilan. 

6.5.11 Northern Palawan 

We divided the province of Palawan into two regions—Northern Palawan and Southern Palawan. 

The significant political features, topography, and wind mapping results for Northern Palawan are 

illustrated in Figures 6-32, 6-33, and 6-34. This region includes the northern part of Palawan 

Island and the islands at the northern end of Palawan, including Lincapan Island and Dumaran 

Island. The wind resource on the northern part of Palawan Island is generally classified as 

moderate to good for rural power applications and marginal for utility-scale applications. There 

are a very limited number of areas with a good-to-excellent resource in the higher terrain areas 

southwest of Roxas. 

The wind power on Lincapan and Dumaran islands is classified as moderate to good for rural 

power applications and marginal to moderate for utility-scale applications. The immediate 

coastline and high terrain in the far northern portion of Palawan is classified as having a good-toexcellent 

resource for rural power applications and a moderate-to-good resource for utility-scale 

applications. There are two small areas with the best resource (good to excellent). These are the 

high terrains east of El Nido and the high terrain northwest of San Vincente. Other areas with a 

good-to-excellent wind resource include the high terrain west of Caramay and southwest of 

Roxas. The wind resource in the immediate vicinity of Puerto Princesa is marginal for utilityscale 

applications, but moderate for rural power applications. However, the higher terrain west of 

Puerto Princesa is characterized as having a good to excellent resource.

6.5.12 Southern Palawan 

46 



The significant political features, topography, and wind mapping results for Northern Palawan are 

illustrated in Figures 6-35, 6-36, and 6-37. A moderate-to-good resource for rural power 

applications is evident in the coastal areas at the far southern end of Palawan, including Bugsuk 

Island, Balabac Island, and areas along the eastern coast near Bivouac Point. A limited area, 

characterized by a good-to-excellent wind resource, extends along the higher terrain in the center 

of Palawan. These areas are principally west of Aborian, Panacan, and Tacbolubu, and north of 

Rio Tuba. 

6.5.13 Sulu, Basilan, and Tawi-Tawi 

The significant political features, topography, and wind mapping results for the Sulu Archipelago, 

including Basilan and Tawi-Tawi, are illustrated in Figures 6-38, 6-39, and 6-40. The Sulu 

Archipelago extends from the western tip of Mindanao southwest toward Malaysia. This group 

of islands is bracketed by the Sulu Sea to the northwest and the Celebes Sea to the southeast. 

Based on the satellite-computed wind speed information presented previously, the wind resource 

in this area is quite low. There is a small area of moderate wind resource associated with the 

higher terrain in the south-central part of Basilan, on the eastern tip and north central part (east of 

Jolo) of Sulu, and on the islands of the Jolo and Tapul groups.

PHILIPPINES 

Area 

ILOCOS 

NORTE 

BATANES 

CAGAYAN

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area 

LA UNION 

PANGASINAN 

ILOCOS 

SUR 

ILOCOS 

NORTE 

ABRA 

BENGUET 

KALINGA- 

APAYAO 

MOUNTAIN PROV. 

IFUGAO 

NUEVA 

VIZCAYA 

NUEVA 

ECIJA 

QUIRINO 

CAGAYAN 

AURORA 

ISABELA

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

LA UNION 

PANGASINAN 

ZAMBALES 

Area 

BATAAN 

BENGUET 

TARLAC 

PAMPANGA 

CAVITE 

NUEVA 

VIZCAYA 

NUEVA 

ECIJA 

BULUCAN 

RIZAL 

BATANGAS 

QUIRINO 

LAGUNA 

AURORA 

QUEZON 

ISABELA

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

BATAAN 

Area 

PAMPANGA 

CAVITE 

BULACAN 

BATANGAS 

ORIENTAL 

MINDORO 

OCCIDENTAL 

MINDORO 

RIZAL 

LAGUNA 

QUEZON 

MARINDUQUE 

ROMBLON 

CAMARINES 

NORTE

PHILIPPINES 

Area

CAMARINES 

NORTE 

QUEZON 

ROMBLON 

AKLAN 

MASBATE 

CAMARINES 

SUR CATANDUANES 

ALBAY 

SORSOGON 

NORTHERN SAMAR 

SAMAR 

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area

MASBATE 

NEGROS 

OCCIDENTAL 

CEBU 

BOHOL 

NORTHERN SAMAR 

SAMAR 

LEYTE 

SOUTHERN 

LEYTE 

PHILIPPINES 

EASTERN 

SAMAR 

SURIGAO 

DEL 

NORTE 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area 

ANTIQUE 

ALKAN 

CAPIZ 

NEGROS 

OCCIDENTAL 

NEGROS 

ORIENTAL 

ILOILO 

MASBATE 

CEBU 

SIQUIJOR 

BOHOL

PHILIPPINES 

Area

PHILIPPINES 

Area

CEBU 

SIQUIJOR 

MISAMIS 

OCCIDENTAL 

LANAO 

DEL NORTE 

BOHOL 

CAMIGUIN 

MISAMIS 

ORIENTAL 

LANAO 

DEL SUR 

NORTH 

COTABATO 

SOUTHERN 

LEYTE 

BUKIDNON 

AGUSAN 

DEL NORTE 

SURIGAO 

DEL NORTE 

AGUSAN 

DEL SUR 

DAVAO 

DEL NORTE 

PHILIPPINES 

SURIGAO 

DEL SUR 

Area 

DAVAO 

ORIENTAL

PHILIPPINES 

Area

PHILIPPINES 

Area 

LANAO 

DEL NORTE 

LANAO 

DEL SUR 

MAGUINDANAO 

SULTAN 

KUDARAT 

NORTH 

COTABATO 

SOUTH 

COTABATO 

BUKIDNON 

AGUSAN 

DEL SUR 

DAVAO 

DEL NORTE 

DAVAO 

DEL 

SUR 

DAVAO 

ORIENTAL

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area 

SULU 

BASILAN 

ZAMBOANGA 

DEL NORTE 

ZAMBOANGA 

DEL SUR 

MISAMIS 

OCCIDENTAL

PHILIPPINES 

Area

PHILIPPINES 

Area

Area 

PHILIPPINES 

PALAWAN 

OCCIDENTAL 

MINDORO

Area 

PHILIPPINES

Area 

PHILIPPINES

PHILIPPINES 

Area 

PALAWAN

PHILIPPINES 

Area

PHILIPPINES 

Area

PHILIPPINES 

Area 

TAWI-TAWI 

ZAMBOANGA 

DEL NORTE 

SULU 

ZAMBOANGA 

DEL SUR 

BASILAN

PHILIPPINES 

Area

PHILIPPINES 

Area

7.0 Wind Electric Potential 


87 



The assumptions and methods for converting the wind resource to wind energy potential are 

based on those in the report “Renewable Energy Technology Characterizations” (DeMeo and 

Galdo, 1997) and are listed at the bottom of Table 7-1. Each square kilometer on the map has an 

annual average wind power density, in W/m 2 , at a 30-m height. We developed an equation to 

compute the total net annual energy delivery for each square kilometer of grid cells with an 

annual average wind power density of 200 W/m 2 or greater. If the wind power density was less 

than 200 W/m 2 , the net energy potential was set equal to zero, because these grid cells have 

insufficient wind potential for the economic development of utility-scale wind energy. Although 

the areas with lower wind resource (100-200 W/m 2 ) are not economic for utility-scale wind and 

thus have been discounted, these areas have the potential for isolated use of small wind for rural 

electrification projects. Under another scenario (good-to-excellent resource levels) only grid cells 

with an annual average wind power of 300 W/m 2 or greater were included. 

The wind resource levels in Table 7-1 are consistent with those on the wind resource maps for the 

Philippines. The numbers in the table represent total net wind-energy potential, and they have not 

been reduced by factors such as land-use exclusions. The net energy is already reduced by about 

15%–20% because of expected losses from downtime, wake-effects, etc. When the wind energy 

potential is computed, the wind power density to the turbine-hub-height level is adjusted so the 

total wind energy potential is not dependent on the height used in our wind resource 

classification. 

7.2 Wind Electric Potential Estimates 

More than 10,000 km 2 of windy land area is estimated to exist with a good-to-excellent wind 

resource potential. The proportion of windy land and potential wind capacity in each wind power 

category is listed in Table 7-1. These windy land areas represent less than 4% of the total land 

area (299,000 km 2 ) in the Philippines. Using conservative assumptions of about 7 MW per km 2 , 

these windy areas could support more than 70,000 MW of potential installed capacity, delivering 

more than 195 billion kWh per year. Considering only these areas of good-to-excellent wind 

resource, Figure 7-1 shows there are 47 provinces out of 73 in the Philippines with at least 500 

MW of wind potential and 25 provinces with at least 1,000 MW of wind potential. However, to 

assess the wind electric potential more accurately, additional studies, considering factors such as 

the existing transmission grid and accessibility, are required. 

If we consider additional areas that have a moderate wind resource potential or that have a good 

wind resource for rural power applications, the estimated total land area increases to more than 

25,000 km 2 (slightly more than 8% of the total land area of the Philippines, as shown in Table 7- 

1). This land could support over 170,000 MW of potential installed capacity, delivering 

361 billion kWh per year. Figure 7-2 shows 51 provinces out of 73 with at least 1,000 MW of 

wind potential and 64 provinces with at least 500 MW of wind potential.

Wind Resource 

Utility Scale 

Table 7-1 

Philippines - Wind Electric Potential 

Good-to-Excellent Wind Resource at 30 m (Utility Scale) 


W/m 2 


m/s * 

88 

Total 

Area km 2 



Total Cap 

Installed MW 

Total Power 

GWh/yr 

Good 300 – 400 6.4 – 7.0 5,541 38,400 85,400 

Excellent 400 – 500 7.0 – 8.0 2,841 19,700 52,200 

Excellent 500 – 700 8.0 – 8.8 2,258 15,600 47,900 

Excellent 700 – 1250 8.8 – 10.1 415 2,900 9,700 

Total 11,055 76,600 195,200 

Wind Resource 

Utility Scale 

Moderate-to-Excellent Wind Resource at 30 m (Utility Scale) 


W/m 2 


m/s * 

Total 

Area km 2 

Total Capacity 

Installed MW 

Total Power 

GWh/yr 

Moderate 200 – 300 5.6 – 6.4 14,002 97,000 165,800 

Good 300 – 400 6.4 – 7.0 5,541 38,400 85,400 

Excellent 400 – 500 7.0 – 8.0 2,841 19,700 52,200 

Excellent 500 – 700 8.0 – 8.8 2,258 15,600 47,900 

Excellent 700 – 1250 8.8 – 10.1 415 2,900 9,700 

Total 25,057 173,600 361,000 

* Wind speeds are based on a Weibull k value of 2.0 

Assumptions 

Turbine Size – 500 kW 

Hub Height – 40 m 

Rotor Diameter – 38 m 

Turbine Spacing – 10D by 5D 

Capacity/km 2 – 6.9 MW

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

PALAWAN 

MINDORO 

PANAY 

SULU 

NEGROS 

BATANES 

LUZON 

SAMAR 

LEYTE 

MINDANAO

References 

91 



Solar Radiation and Wind Mapping of the Philippines, USAID GOP Project No. 492-0294, 

National Institute of Climatology, October 1986. 

Climatological Normal of Surface Winds in the Philippines, National Institute of Climatology, 

PAGASA, January 1988. 

Average Wind Speed and Direction 1961–1992, Climate Data Section, Climatology and 

Agrometeorology Branch, PAGASA, January 1995. 

DeMeo, E.A.; Galdo, J.F. Renewable Energy Technology Characterizations, Office of Utility 

Technologies, Energy Efficiency and Renewable Energy, U.S. Department of Energy, 

Washington D.C., 1997. 

Elliott, D.L. “Dominican Republic Wind Energy Resource Atlas Development”, NREL/CP-500- 

27032, National Renewable Energy Laboratory, Golden, Colorado, 1999. 

Elliott, D.L.; Chadraa, B.; Natsagdorj, L. “Mongolia Wind Resource Assessment Project”, 

NREL/CP-500-25148, National Renewable Energy Laboratory, Golden, Colorado 1998. 

Elliott, D.L.; Holladay, C.G.; Barchet, W.R.; Foote, H.P.; Sandusky, W.F. Wind Energy Resource 

Atlas of the United States, Solar Energy Research Institute, Golden, Colorado, 1987. 

Elliott, D.; Schwartz, M.; Nierenberg, R. “Wind Resource Mapping of the State of Vermont”, 

NREL/CP-500-27507, National Renewable Energy Laboratory, Golden, Colorado, 1999. 

Rohatgi, J.S.; Nelson, V. Wind Characteristics: An Analysis For The Generation of Wind Power, 

Alternative Energy Institute, West Texas A&M University, Canyon, Texas, 1994, 239 pp. 

Schwartz, M.N. “Wind Resource Estimation and Mapping at the National Renewable Energy 

Laboratory”, NREL/CP-500-26245, National Renewable Energy Laboratory, Golden, Colorado, 

1999. 

Schwartz, M.N.; Elliott, D.L. “Mexico Wind Resource Assessment Project”, NREL/TP-441- 

7809, National Renewable Energy Laboratory, Golden, Colorado, 1995. 

Schwartz, M.N.; Elliott, D.L. “The Integration of Climatic Data Sets for Wind Resource 

Assessment”, Preprints, 10 th Conference on Applied Climatology, Reno, Nevada, pp. 368-372. 

1997.

Appendix A 

Data Summaries 

National Power Corporation Sites 

Agaga 

Bangui 

Bayog 

Caparispisan 

Guimaras 

Pagali 

Sagada 

Saoit 

Subec

A-1

A-2

A-3

A-4

A-5

A-6

A-7

A-8

A-9

A-10

A-11

A-12

A-13

A-14

A-15

A-16

A-17

A-18

A-19

A-20

A-21

A-22

A-23

A-24

A-25

A-26

A-27

A-28

A-29

A-30

A-31

A-32

A-33

A-34

A-35

A-36

Appendix B 

Analysis Summaries—Selected Sites from 

DATSAV2 Data Files 

Cuyo 

Daet 

Guiuan

B-1

B-2

B-3

B-4

B-5

B-6

B-7

B-8

B-9

B-10

B-11

B-12

B-13

B-14

B-15

B-16

B-17

B-18

B-19

B-20

B-21

B-22

B-23

Appendix C 

Analysis Summaries—Upper-Air Stations 

Legaspi 

Palau Island 

Pratas Island

C-1

C-2

C-3

C-4

C-5

C-6

C-7

C-8

C-9

C-10

C-11

C-12

C-13

C-14

C-15

C-16

C-17

C-18

C-19

Appendix D 

Wind Speed and Wind Power Density Computed from 

Satellite Ocean Wind Data 

August and December 

Wind Speed and Wind Power Density Maps 

Computed from Satellite Ocean Wind Data 

Region Location Map for the Satellite Ocean Wind Data 

Satellite Ocean Wind Speeds at 10 m 

Extreme North, East Coast, North Mindanao, East Mindanao, 

Palawan-East Coast, Palawan-West Coast, and 

West Coast Wind Corridors 

Satellite Ocean Wind Power Densities at 10 m 

Extreme North, East Coast, North Mindanao, East Mindanao, 

Palawan–East Coast, Palawan–West Coast, and 

West Coast Wind Corridors

€2E2‚2v—2w— 

p2ƒ—2y—2‡2h—— 

†—22IH22r 

IIV 

IPH 

PH 

I 

PH 

R 

P 

Q 

IV IV 

IT IT 

P 

IR 

Q 

IR 

I 

R 

IP 

P 

IP 

IH 

V Q 

P 

Q 

I 

P 

I 

Q 

Q 

P 

I 

I 

IH 

V 

v 

‚2q T 

Q 

T 

i2x2E2 

f——22x2v 

i—2g—2E2 

v22ƒ—— IIV 

‡2g—2‡2g2E 

w22x 

x2w—— 

IPH IPP IPR IPT 

i—2w—— 

€———2E2‡2g— 

€———2E2i—2g— 

x‚iv2g—X 

h2i2@QHQA2QVRETWQS 

w—2ƒ—2@QHQA2QVRETWQT 

2 

2 

IPP 

I 

IPR 

IPT 

P 

IHH H IHH PHH QHH RHH SHH u 

x 

…ƒ2hF22i2E2x—— 

‚—˜2i2v—˜— 

hw2r2IWEhigEPHHH2IFI


12 

10 

8 

6 

4 

2 

0 

Philippines - Extreme North - Batanes to North Luzon 

Satellite-based Ocean Wind Speeds 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

D-6 

Region Annual Speed 

1 7.3 

2 7.0 

3 7.0 

4 7.7 

Period: 1988-1994


12 

10 

8 

6 

4 

2 

0 

Philippines - East Coast - Luzon to Samar 



D-7 


1 6.2 

2 6.1 

3 6.3 

4 6.3 

Period: 1988-1994


12 

10 

8 

6 

4 

2 

0 

Philippines - North Mindanao 



D-8 


1 5.8 

2 5.5 

3 5.2 

Period: 1988-1994


12 

10 

8 

6 

4 

2 

0 

Philippines - East Mindanao 



D-9 


1 5.3 

2 6.0 

3 6.3 

Period: 1988-1994


12 

10 

8 

6 

4 

2 

0 

Philippines - Palawan - East Coast 



D-10 


1 6.0 

2 5.1 

3 5.3 

Period: 1988-1994


12 

10 

8 

6 

4 

2 

0 

Philippines - Palawan - West Coast 



D-11 


1 5.3 

2 5.3 

3 5.6 

Period: 1988-1994


Philippines - West Coast Wind Corridors - Mindoro to Negros 


12 

10 

8 

6 

4 

2 

0 


D-12 


1 6.4 

2 6.7 

3 5.8 

Period: 1988-1994


1200 

1000 

800 

600 

400 

200 

0 

Philippines - Extreme North - Batanes to North Luzon 

Satellite-based Ocean Wind Power Densities 


D-13 

Region Annual Power 

1 371 

2 332 

3 341 

4 549 

Period: 1988-1994


1200 

1000 

800 

600 

400 

200 

0 

Philippines - East Coast - Luzon to Samar 



D-14 


1 298 

2 307 

3 296 

4 272 

Period: 1988-1994


800 

600 

400 

200 

0 

Philippines - North Mindanao 



D-15 


1 205 

2 193 

3 169 

Period: 1988-1994


800 

600 

400 

200 

0 

Philippines - East Mindanao 



D-16 


1 180 

2 241 

3 238 

Period: 1988-1994


800 

600 

400 

200 

0 

Philippines - Palawan - East Coast 



D-17 


1 243 

2 171 

3 177 

Period: 1988-1994


800 

600 

400 

200 

0 

Philippines - Palawan - West Coast 



D-18 


1 174 

2 186 

3 184 

Period: 1988-1994


Philippines - West Coast Wind Corridors - Mindoro to Negros 


800 

600 

400 

200 

0 


D-19 


1 286 

2 320 

3 246 

Period: 1988-1994

REPORT DOCUMENTATION PAGE 

Form Approved 

OMB NO. 0704-0188 

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, 

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this 

collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson 

Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503. 

1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 

February 2001 

4. TITLE AND SUBTITLE 

Wind Energy Resource Atlas of the Philippines 

6. AUTHOR(S) 

D. Elliott, M. Schwartz, R. George, S. Haymes, D. Heimiller, G. Scott 

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401-3393 

3. REPORT TYPE AND DATES COVERED 

Technical Report 

5. FUNDING NUMBERS 

WER11050 

DO059999 

8. PERFORMING ORGANIZATION 

REPORT NUMBER 

NREL/TP-500-26129 

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING 

AGENCY REPORT NUMBER 

11. SUPPLEMENTARY NOTES 

12a. DISTRIBUTION/AVAILABILITY STATEMENT 

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

12b. DISTRIBUTION CODE 

13. ABSTRACT (Maximum 200 words) 

This report contains the results of a wind resource analysis and mapping study for the Philippine archipelago. The study's 

objective was to identify potential wind resource areas and quantify the value of those resources within those areas. The wind 

resource maps and other wind resource characteristic information will be used to identify prospective areas for wind-energy 

applications. 

14. SUBJECT TERMS 

Philippines; wind resource; maps; Geographic Information System 

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