Investigation of Wind Energy Potential in Asia-Pacific Region: Thailand, South Korea and Bangladesh Perspectives

Abstract

This dissertation simply deeply focuses on the wind energy analysis in Thailand, South Korea and Bangladesh, a small but not a least part of the Asia-Pacific Region in terms of energy issues through statistical wind data interpretations, building wind energy atlas as well as launching machine learning modeling for the sake of training and testing sample wind data for the selection of the suitable methods and algorithms. In order for the statistical analysis of the wind data, the areas have been chosen based on the data availability. Wind data statistical analysis were done as per the rule of internationally recognized standard like IEC 61400-12-1. Following the standard, a part of the research, this dissertation analyzes the prospects and possibilities of wind energy from the engineering point of view in Hoenggyeong do and Mal do two of the small Islands of the Jeollabuk province of the Republic of Korea. As wind resource is a prominent sector of renewable energy of Korea in the recent era having lots of wind flow in a varying speed all around the year, this research attempts to analyze the 10-minutes averaged real wind speed and direction data of the proposed Islands with a view to identify the possibilities of building up offshore wind farm in the near future. In terms of the research work regarding Thailand, satellite data from NOAA has been retrieved from its own FTP server from which wind speed and direction data were used for analysis. Wind data of hourly averaged available for every day basis, i.e. the downloaded file was one for every single day. Finally, wind maps were created using some mathematical tool most prominent for wind energy analysis. This was indeed used in ArcMap through raster calculator. As an annexure of the thesis for validation work, machine learning was introduced for training and testing a sample wind data of Thailand recorded at 10 m above ground level (AGL) which was interpolated to get wind speed at different heights like 20 m, 15 m or 30 m AGL using regression method. As a part of the research, this work investigates coastal wind resource of Bangladesh through time-series measured (1-year: 2017) and predicted (2000-2017) wind data analysis as per IEC 61400-12-1. Building high resolution mesoscale (resolution: 3000 m) and microscale (resolution: 200 m) wind resource maps at 60 m, 80 m and 100 m above ground level (AGL) as a part of weather research and forecasting (WRF) through MERRA2/NASA global reanalysis climate database have also been applied in this research. Simulated (i.e. predicted) wind speed data have been validated through a number statistical tests by the use of measured wind speed of seven coastal area of the country. Using computational fluid dynamics MC2/MS-Micro wind flow modeling along with measured wind data interpretation, a number of test WTGs (wind turbine generators) with the range of 1-3.3 MW of capacity have been employed for gaining sufficient idea of available energy that may be produced in these micro-sites. The research concerns with the mitigation of the carbon as a global point of view of energy when carbon issue is one of the most crying bargaining points at present. Results show that, 1 MW WTG at 60 m AGL in each site can produce a total of 2.79 GWh (AEP of 1.72 GWh and 1.08 GWh respectively) of energy in one year (reducing 1781.69 Ton of CO2/year), 3.30 MW WTG at 80 m AGL can reduce 12098.54 Ton CO2/year by producing a total of 18.99 GWh (AEP of 10.81 GWh and 8.19 GWh respectively) and 1.6 MW WTG at 100 m AGL can produce a total of 11.04 GWh (AEP of 6.22 GWh and 4.83 GWh respectively) of energy reducing 7035.03 Ton CO2/year. In addition to the wind energy analysis in a number of ways, this dissertation analyzes the wind turbine noise generated from a 5 kW test wind turbine generator (WTG) with hub height, rotor diameter, cut-in and rated speed of 15m, 4m, 3 m/s and 12 m/s respectively according to IEC 61400-11 (acoustic noise) standard. It discusses the realistic and comparable performances of small WTG that sets its own characteristics in terms of power and acoustic performances. Standard set by American Wind Energy Association (AWEA 2009) has also been incorporated together with IEC 61400-11. For the measurements of noise level, the averaging period has been considered to be 10-second as per AWEA 2009. The study attempts to analyze time-series noise data recorded at different distance from the WTG for finding Noise (dB)-Frequency (Hz), RPM-Volt and Noise-RPM relationship. The analysis has been done with the help of wind speed histogram bin each of size 1 m/s which estimates that, RPM ranges between 0 - 170, overall noise ranges between 45.17 (dB) - 48.78 (dB) and background noise ranges between 33.2 (dB) - 65.6 (dB). The relationship between the noises coming from WTG with background noise demonstrates for the deeper understanding that the environmental hazard created by WTG noise is likely to demand for analysis which can never be ignored. The thesis, as a part of doctoral activities was basically meant for learning, thinking, realizing the current global energy issues through creating and implementing wind maps from satellite remote sensing wind data along with statistical analysis of wind data, validating the maps with real met station data along with launching machine learning for wind data test with a view to be a part of creating a sustainable world.