An Assessment of Offshore Wind Energy Potential on Phangan Island by in Southern Thailand

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1 Available online at ScienceDirect Energy Procedia 52 (2014 ) International Conference on Alternative Energy in Developing Countries and Emerging Economies An Assessment of Offshore Wind Energy Potential on Phangan Island by in Southern Thailand Warit Werapun a,*, Yutthana Tirawanichakul b, Watsa Kongnakorn c, Jompob Waewsak d a Faculty of Science and Industrial Technology, Prince of Songkla University,Suratthani Campus,Suratthani (Thailand) b Plasma and Energy Technology Reserch Laboratory,Department of Physics,Faculty of Science,Prince of Songkla University, Hatyai Campus,90110 (Thailand) c Civil Engineering Department, Faculty of Engineering, Prince of Songkla University, Hatyai Campus,90110 (Thailand) d Solar and Wind Energy Reserch Laboratory(SWERL), Department of Physics, Faculty of Science, Thaksin University, Phatthalung Campus, (Thailand) Abstract This research aims to assess the potential of offshore wind energy in Suratthani province, located in the middle of peninsular Thailand. A 120 m Guy Mast triangle tower was installed at the Phangan Subdistrict Administrative Organization area, Phangan Island. Five weather measurement points including wind speed anemometers, relative humidity detectors and dry bulb ambient air thermometers were placed at heights of 65, 90, 100, 110 and 120 m, while the two wind vane detectors were fixed at 100 and 120 m heights. Data were continuously recorded at 10 min sampling intervals, from December 2011 to November The average wind speed was 4.28 m/s and the mean wind power density was 85 W/m 2. The dominant wind direction was from the north. Based on these data, 9 cases of wind farm layout were simulated to assess their performance. The capacity factors of offshore wind farms were in the range of This suggests that the location and layouts simulated would be poorly utilized investments. However, the higher wind speeds of elevated areas of the island should be similarly assessed Published by Elsevier by Elsevier Ltd. This Ltd. is an Selection open access and/or article under peer-review the CC BY-NC-ND under responsibility license of the Research ( Center in Energy and Environment, Thaksin University. Selection and peer-review under responsibility of the Organizing Committee of 2013 AEDCEE Keywords : offshore wind energy, modelling, wind energy assessment, Annual Energy Production, Phangan Island * Corresponding author. Tel.: ; fax: address: waritw2000@yahoo.com Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Selection and peer-review under responsibility of the Organizing Committee of 2013 AEDCEE doi: /j.egypro

2 288 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Introduction Renewable wind energy can be converted to electricity by wind turbines. It is a clean and free energy resource, but not all locations are suited for the installation of wind turbines. In general the potential of offshore wind energy is higher than on shore, because of higher wind speeds and less concerns with pollution, visual impact, or conflicts with other land use. However the disadvantages can include expensive marine foundations, and the cost of integration to the electrical network [1]. Offshore wind farms have been rapidly established in Europe because of the limited space available onshore [2,3]. The largest offshore wind farm in the world was built in England, namely Thanet which has a 300 MW capacity. In Denmark, 20% of electricity is produced from wind, whereas in China the first commercial offshore wind project was 102 MW Shanghai Donghai Bridge, with all the 34 turbines connected to the grid since June 2010 [4,5]. In Taiwan a suitable area for offshore wind farm was identified by a graphical information system [6]. Also a southwestern sea-area of the Korean Peninsula has been planned for constructing an offshore wind farm demonstration [7]. In Thailand the Ministry of Energy has set the goal of using 20 % renewable energy in Last year, during 4-6 December 2012, electricity was off on Samui and Phangan islands due to a problem with a transmission cable; this caused loss of income and business from tourism [8]. On 19 Febuary 2013 it was announced that Thailand could face a power shortage due to scheduled repair and maintenance break in the natural gas production of Myanmar. Thai government is encouraging the population to save energy in household use, to relieve an impending shortage [9]. A 1 km resolution wind resource map of Thailand and GIS based area from selection map shows that many coastal areas along the gulf of Thailand have good wind resource [10]. The gulf of Thailand has many islands, including Taoisland where an 0.25 MW wind turbine has already been installed by the Provincial Electricity Authority. Other notable islands include Samui and Phangan. These islands are shown in Figure 1. Phangan island is located in Suratthani province, and is famous for the full moon party. Each year a lot of tourists visit it, and the demand of electricity is increasing. A 33 kv power cable connects Phangan to Samui to supply electricity to this community. In the future a wind turbine installation could be the response to further increases in demand, so an assessment of wind energy potential is motivated. N Tao island Phangan island Samui island Suratthani Donsak Fig.1. The location of three islands of Thai Gulf

3 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Methodology In order to estimate wind speed at height level position above ground level. The wind speed equation has been used for extrapolation from known wind speed at known height to other heights, given the surface roughness coefficient [11]. To evaluate wind energy potential in this research, a 120m guy-mast was installed in Phangan island for monitoring wind speed and wind direction directly at various heights. The site survey, contour map and power curve for WAsP9.0 were prepared as following 2.1 Site Survey and 120 m tower installation On Phangan island, most of the area is mountainous in the range of meters from the sea level, with highly rough terrain. Requiring smooth terrain for the installation of a 120 tower, with a radius of at least 40 m for the guy cables, left only few options. The northeastern part of Phangan island belongs to a national park, so the area of Phangan subdistrict organization was selected because it satisfied the requirements and was free of charge. The 120m guy mast s triangle tower (Figure 2.) was installed at the UTM coordinate position of x and y For an assessment of wind energy potential, the wind speed was measured at 5 heights(65,90,100,110 and 120 m) using anemometers, and the wind direction at 100 and 120 m heights were measured with NRG 200P wind vanes. Data were collected every 1 minutes by Nomad II data logger, during December2011 November The 12 V DC battery for the data logger was charged by solar cells at 10 m height. The relative humidity, temperature and pressure were also recorded. For analysis the data was sampled every ten minutes. The Annual Energy Production (AEP) was estimated with widely used WAsP 9.0 software. Solar cell Lightning Obstruction lamp 120m Wind vane 110m 100m Anemometer 90m 65m 10m Data Logger Fig.2. The photo and schematic of 120 m tower installation

4 290 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Vector map preparation Vector map was prepared of a 15x15 km area around the wind tower station. The Digital Elevation Model map (L7081) from Military Map Department was processed with ArcGIS software. A roughness map was prepared from SPOT5 Satellite Images for land-use. These maps were input to WAsP 9.0 with the help of WAsP utilities. 2.3 Power curve The power curves of wind turbines 3 MW Vestas, 5 MW Repower, and 7 MW Vestas, were selected for use in predicting the Annual Energy Production (AEP) of offshore wind farms, with cut-in speeds in the range of 3-4 m/s and cut-off speeds at 25 m/s. The electricity production of offshore wind farm was estimated for 3 groups of layouts: very small power plant(vspp) in case of C1-C3 which has power installed not above of 10 MW, small power plant(spp) in case of C4-C6 which has power installed not above of 30 MW, and triple of small power plants (3SPP) in case of C7-C9 which has power installed not above of 90 MW. For each group was sampled 3 cases with different turbine capacity. The 9 cases for estimates are summarized in Table1. Table 1. Cases Study for Offshore Wind Energy Case Study Capacity (MW) Number Power Installed (MW) 1(VSPP) (VSPP) (VSPP) (SPP) (SPP) (SPP) (3SPP) (3SPP) (3SPP)

5 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Results and Discussion 3.1Average Wind Speed Analysis Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Fig. 3. Variation of mean wind speed at 120m height of the Phangan station The variation of wind speed is shown in Figure 3. The lowest monthly average was observed in November 2012, while the highest average wind speed was in June2012, at 120 m height. During December2011-Febuary2012, normally Thai gulf zone has the north-east monsoon with calm waves and low wind speeds from March to April. The wind speed increases for May to September, due to the southwest monsoon. It was no surprise that the annual average wind speed increased with the height of sensor position, being in the range m/s at the heights 65,90,100,110,120m. When the average wind speeds of each month were compared to Samui meteorological station (12.5 m height) and Suratthani meteorological station (10m height), the patterns of variation were more similar to Surathani than to Samui. It should be noted that the meteorological stations provided data recorded at 3 hr intervals; the monthly averages are shown in Figure 4. At the 110 m height of Phangan station a cable problem prevented data collection in December2011-January2012.

6 292 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) m_Phangan 110m_Phangan 100m_Phangan 90m_Phangan 65m_Phangan 12.5m_Samui 10m_Suratthani 5 Mean Wind Speed (m/s) Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Monthly Fig.4.Mean wind speeds at Phangan station (heights 65,90,100,110,120m) and the meteorological stations of Samui (12.5m) and Suratthani (10m). A wind rose plot for December 2011-November 2012 shows that 83.3% of the time the wind direction was from the north of Phangan island, within an angle less than 23 degrees as shown in Figure 5. It is expected that the high mountain in the north-east zone of the island blocks wind flow from that direction, while winds from north were observed frequently. The Weibull distribution fit to wind speed (Figure6) gave the mean speed as 4.28 m/s, which is similar to comparable areas [12], and the power density was 85 W/m m 100m Fig.5. Wind rose at the heights of 100 and 120 m

7 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Wind speed frequency distribution analysis The frequency histogram with wind speed bins and weibull distribution curve are shown in Figure 6. The wind speed values were calculated using observed wind climate wizard in the software and showing with excel program. The average wind speed was above 3 m/s for 66.3 % of the time at 120 m, allowing a wind turbine to produce energy. The average power density was 85 w/m 2 which is corresponds to winds of class1 [13]. Frequency(%) Wind speed Weibull Distribution Sector :All A=4.8m/s k=2.16 U=4.28 m/s P=85W/m Wind Speed (m/s) 3.3 Wind energy yield estimation Fig.6. Histogram of wind speed and weibull distribution at 120m From the wind data analysis, winds mostly came from the north direction of Phangan island, so the 9 cases of power plants were placed north of Phangan. In a wind farm layout the wake effect of a turbine can reduce the energy production of other turbines downstream. Such wake losses are reduced by increasing the distance between wind turbines, but this in turn will increase the cost of the farm. Balancing these aspects is done by optimizing the wind farm layout, to minimize the cost of energy and maximize the energy production. The Annual Energy Production was calculated using WAsP9.0 as shown in the Figure 7. For the very small power plants (C1-C3) the AEP was in the range of GWh/year, while for small power plants (C4-C6) the range was GWh/year. The triple cases of small power plants (C7-C9) had the range GWh/year. The wake loss was reduced with increased distance between the wind turbines: in the layout case 15DX15D the wake loss was below 5 %, as shown in Figure 8. The plant capacity factor of a wind energy conversion system was obtained, by dividing the actual energy output during one year by the rated power and the number of hours in a year. It is found that at 120m, the plant capacity factor is in the range of % as shown in Figure9.

8 294 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Fig.7. Annual Energy Production for C1-C9 Fig.8. Wake Loss of wind farm layout for C1-C9 Fig.9. Capacity Factors for cases C1-C9

9 Warit Werapun et al. / Energy Procedia 52 ( 2014 ) Because the plant capacity factors are quite low, other areas of Phangan island could be considered. Simulations with the WAsP software suggest that the wind speeds on the mountain are higher than at the sea level, on Phangan island. On shore wind turbines for water pumping and lighting could be considered. 4. Conclusion Wind data collected for a year during December2011-November2012 revealed an average wind speed of 4.28 m/s, from north 83.3 % of the time, on Phangan island at 120m height. Simulations of wind farms based on these data gave capacity factors in the range % suggesting that such investment would be poorly utilized. The potential of wind turbine installations on the more elevated parts of Phangan island should be assessed, as those locations have higher wind speeds. Acknowledgements We gratefully acknowledge financial support by the National Research Council Thailand; the Prince of Songkla University, Suratthani Campus; and the Faculty of Science, Hatyai Campus, Research and Development Office. We also thank Administration Subdistrict Organization (Phangan Island) for permitting the land installation of the tower. We also thank Assoc.Prof.Dr. Seppo Juhani Karrila for his comment and corrected manuscript. References [1] Esteban Dolares M., Javier Diez J., Lopez Jose S., Negro Vicente; Why offshore wind energy, Renewable Energy2011; 36 : [2] Bilgili Mehmet, Yasar Abdulkadir, Simek Erdogan; Offshore wind power development in Europe and its comparison with onshore counterpart, Renewable and Sustainable Energy Review2011;15: [3] Breton Simon-Philippe, Moe Geir; Status, plans and technologies for offshore wind turbines in Europe and North America, Renewable Energy2009; 34: [4] Da Zhang, Xiliang Zhang, Jiankun He, Qimin Chai; Offshore wind energy development in China: Current status and future perspective,renewable and Sustainable Energy Reviews2011; 15: [5] Sun Xiaojing, Huang Diangui, Wu Guoqing; The current state of offshore wind energy technology development, Energy 2012;41: [6] Yue Cheng-Dar and Yang Min-How; Exploring the potential of wind energy for a coastal state, Energy Policy2009; 37: [7] Oh Ki-Yong, Kim ji-yong, Lee Jae-Kyung, Ryu Moo-Sung, Lee Jun-Shin; An assessment of wind energy potential at the demonstration offshore wind farm, Energy2012; 46: [8] Bangkok Post Samui, Phangan still without power [Available Online] accessed on 21 Febuary [9] United Press International Thailand to face April energy crisis? [Available Online] accessed on 21 Febuary [10] Manomaiphiboon K, Wind Resource Assessment Using Advanced Atmospheric Modeling and GIS Analysis, Final report 2010,TRF [Available Online] accessed on 20 January [11] Adaramola M.S., Oyewola O.M; On wind speed pattern and energy potential in Nigeria, Energy Policy2011;39 : [12] Promsen W., Masiri I., Janjai S; Development of microscale wind maps for Phaluay Island, Thailand, Procedia Engineering2012; 32 : [13] Yu Xiao, Qu Hang; Wind power in China-Opportunity goes with challenge, Renewable and Sustainable Energy Reviews2010;14: