Wind energy is one of the most promising renewable energy technologies worldwide; however, assessing potential sites for wind energy exploitation is a challenging task. This study presents a site suitability analysis to develop a small–scale wind farm in south–eastern Thailand. To this aim, the most recent available data from 2017 to 2019, recorded near the surface, at nine weather stations of the Thai Meteorological Department (TMD) were acquired. The analysis was conducted using standard wind–industry software WAsP. It was found that the mountain peaks and ridges are highly suitable for small–scale wind farm development. Nevertheless, the wind data analysis indicates that regions fall in low–to–moderate wind classes. The selected sites in south–eastern Thailand have mean wind speeds ranging from 5.1 m/s to 9.4 m/s. Moreover, annual energy production (AEP) of 102 MWh to 311 MWh could be generated using an Enercon E–18 wind turbine with a rated power of 80-kW at the hub height of 28.5 m. The Levelized Cost of Energy (LCOE) reveals that the development cost of a small–scale wind farm is lowest in the Songkhla and Yala provinces of Thailand, therefore these two locations from the investigated study region are financially most suitable. The findings could encourage researchers to further investigate low–speed wind energy mechanisms in tropical regions, and the demonstrated approach could be reused for other regions.
Due to environmental problems associated with fossil fuels and rising need for energy, wind power renewable energy will play a vital role in transformation of future energy structure in Thailand. Exploitation of wind energy for sustainable development, wind resource assessment plays an important role in wind power utilization. This case study presents wind resource assessment using the wind atlas analysis and application program (WAsP), in order to assess the potential of wind energy in Hat Yai, Thailand. Ten-minutes interval wind data observed by the Thai Meteorological Department recorded during the period 2017-2019, have been used to harness adequate wind power density and wind energy potential. The annual mean wind speed is 3.5 m/s at 10 m height above the ground. The prevailing direction southwest, south and northeast of the wind rose are very pronounced. The WAsP analysis estimates about 2,731.28 MWh of the total net annual energy production for the specific sites using the Enercon E-18 (80 kW) wind turbine of 1.92 MW capacity. The findings of this study indicate the possibility of the small-scale wind farm project for electricity generation in future.
This paper presents a techno-economic assessment of a 100 kWp solar rooftop photovoltaic (PV) system at five hospitals in central southern Thailand. The system encompasses 100 kWp PV panels, 100 kW grid-tied inverters and balance of system (BOS) under the grid code of the Provincial Electricity Authority (PEA). The latest PV technology of bifacial mono-crystalline solar panels, inverters and BOS were simulated along with the Meteonorm 7.3 database using the PVsyst simulation toolkit with different tilt angles, orientations, solar radiations and ambient temperature. The technical aspects of solar rooftop PV power generation systems include the annual energy output and the performance ratio (PR) under IEC standard. Further, an economic analysis of the model was examined using a cost benefit analysis (CBA) and various assumptions. Four main financial criteria, i.e., benefit cost ratio (BCR), net present value (NPV), internal rate of return (IRR), and payback period (PBP) were evaluated under three different scenarios: (1) self-consumption scheme, (2) feed-in tariff (FiT) scheme, and (3) private power purchase agreement (PPA) scheme. Finally, the levelized cost of energy (LCOE) was also calculated. The results reveal that the Takua Thung hospital is characterized by the maximum average global horizontal irradiation (GHI) and the maximum annual produced energy of 199 kWh/m2 and 164.8 MWh/year, respectively. The PR calculated for all hospital sites is above 85%. The outcomes of the financial analysis show that the optimum scenarios are PPA and FiT schemes. The LCOE analysed in this study indicates that the Takua Thung hospital site has the lowest LCOE at 2.47 THB/kWh (0.07 USD/kWh). This research confirms the potential for hospitals and stakeholders in central southern Thailand for investments in solar rooftop PV systems
Globally, wind energy has proven to be one of the most sustainable sources of energy. Wind energy assessment plays a critical role on determining installation of wind turbines worldwide. This work presents the technical evaluation of wind energy potential using three available wind turbine models for prospective onshore wind farm in the southern Thailand at Krabi and Songkhla sites. Ten-minute interval wind data over a period of 3 to 4 years obtained from Weather Observing Station is utilized to observe the diurnal and monthly wind speed, as well as frequency distribution. WAsP program is applied for energy yield calculations and wind resource maps. Our results reveal that Krabi and Songkhla has the highest mean wind speed of 4.39 m/s in December and 3.91 m/s in February, respectively. The prevailing wind direction in Krabi and Songkhla are north-east and south-east, respectively. WAsP analyses show that the total net AEP for Krabi is 7163.782 MWh, 7762 MWh and 12731 MWh using 275 kW, 300 kW and 500 kW wind turbine models, respectively. Similarly, the total net AEP for Songkhla is 7116.63 MWh, 7775.245 MWh and 12390 MWh using 275 kW, 300 kW and 500 kW wind turbine models, respectively. The total capacity factor for Songkhla and Krabi is 29.1% and 28.3%, respectively. Our results indicate that Enercon E-40/5.40 500 kW wind turbine model produces the highest total gross AEP and total net AEP for Krabi and Songkhla sites. Besides, the Vergnet GEV MP-C 275 kW turbine model shows slightly higher capacity factor in case of both sites. The findings of this study reflect that small to medium size wind turbines can be utilized to generate electricity at the sites.
The aim of this research is to study the wind speed, wind direction and the temperature of 15 stations of Thailand at 5 levels from 16 November 2019 - 13 February 2020. WAsP application is used in this research to calculate the two parameters Weibull distribution namely K shape and C scale. Furthermore, maximum and minimum wind speed is recorded. Data from Nakhon Si Thammarat shows the maximum mean wind speed 5.02 m/s. and Nan shows the minimum mean wind speed 0.8 m/s. Additionally, the prominent wind direction of every station is observed as well. Main wind direction for Nakhon Si Thammarat is from (Southwest). These results facilitate for the further research on wind characteristic feasible for small wind farm by increasing the timeline of data recorded.
This paper presents the optimization of a 10 MW solar/wind/diesel power generation system with a battery energy storage system (BESS) for one feeder of the distribution system in Koh Samui, an island in southern Thailand. The main objectives are to maximize the deployment of renewable energy-based power generation and to minimize the levelized cost of energy (LCOE). A hybrid renewable energy-based power generation system, consisting of solar PV, wind turbine generators, diesel generator (DiG), bi-directional grid-tied charging inverter (CONV) and BESS, was simulated using HOMER Pro®. This study accessed the database of the National Aeronautics and Space Administration (NASA) for the Surface meteorology and Solar Energy (SSE) for the global solar radiation and temperature, along with the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) wind database. The simulations show that Scenario 1 (PV/Wind/DiG/BESS/CONV) and Scenario 3 (PV/DiG/BESS/CONV) are the optimal configurations regarding the economic indicators (i.e. minimum net present costs (NPC) of 438 M$ and LCOE of 0.20 $/kWh) and the environmental indicators (i.e. lowest greenhouse gases (GHG) emission avoidances of 6,339 tonnes/year and highest renewable fraction (RF) of 89.4%). Furthermore, the sensitivity analysis illustrates that Scenario 3 offers the optimal system type with the largest annual energy production (AEP). Besides contributing to the body of knowledge of optimization methodologies for microgrid hybrid power systems, the outcome of this work will assist the regional energy practitioners and policy makers regarding optimal configurations of microgrid hybrid systems in the development of a Green Island concept for Koh Samui.
This study focuses on the collection and observation of mean wind speed and power density of 15 stations in Thailand merged with the topographic map of the stations. The wind data was collected by installing anemometers at 10m, 15m, 20m,25m and 30m height at 15 selected stations around Thailand. Wind Analysis and Application Program (WAsP) is used to generate mean wind speed and power density. Meanwhile, roughness and surface elevation map are produced and merged with the data in WAsP. The results showed the highest wind speed in Songkhla station which was 3.16 to 12.15m/s and on the other hand data from Narathiwat showed the lowest mean wind ranging from 1.13 to 1.72m/s. Finally, Songkhla station power density ranges from 24-1372W/m2 and in Narathiwat station ranging from 2-5W/m2 in terms of power density. In Thailand, the landscape is diverse such as plateau, plains, coastal plains, land, mountains, mountain ranges and hills. Generally, the wind speeds and directions change due to landscape. For this season, to study wind resource, investigation on topography is vital.
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