An Evaluation of Economic Potential Solar Photovoltaic Farm in Thailand: Case study of Polycrystalline Silicon and Amorphous Silicon Thin Film

Solar energy in Thailand plays an important role to achieve the target of the Alternative Energy Development Plan (AEDP). Enormous investments from investors are expected to occur for support AEDP. Therefore, the objective of this study was to evaluate and compare the economic potential of solar PV farm between polycrystalline silicon (PCSS) and amorphous silicon thin film (ASTF) type. Questionnaires submitted to private solar PV farm for collecting data. As a result, four main investment costs of PSS are identified: (1) photovoltaic module; (2) connection system; (3) inverter, and (4) engineering construction, distributed as 58.09%, 19.66%, 12.96%, and 4.47%, respectively. The financial analysis found that Payback period (PB), Internal Rate of Return (IRR), and Solar Plant capital of ASTF were less than PCSS; however, it returns low income along 25 years than PCSS. It could be suggested that the investment on PCSS is worth than ASTF. Keywords: Economic potential, Solar PV farm, Investment, Financial economic. JEL Classifications: C8, G0, M

High resolution wind atlas for Nakhon Si Thammarat and Songkhla provinces, Thailand

In this work, a high resolution wind atlas for Nakhon Si Thammarat and Songkhla provinces in southern Thailand was developed using combined mesoscale, MC2, and microscale, MsMicro, modeling techniques. The model inputs consist of long-term statistical climate data, i.e. the NCEP/ NCAR database, high resolution topography and land cover data. The 200 m resolution wind resource maps were validated with observed mean wind speeds from 10 met stations located along the coastlines of the territory studied. These comparisons have shown that the wind atlas provides a good representation of the wind resource throughout the territory of Nakhon Si Thammarat and Songkhla provinces, Thailand. The technical power potential and potential annual energy production are then identified. Results from the technical power potential at 80 m above ground level show that a total of 1374 MW of wind farms, generating annually 3.6 TWh of electricity, could be installed; while 407 MW of small wind turbines (50 kW), generating annually 1.0 TWh of electricity, could be installed

Comparative Study of Five Methods to Estimate Weibull Parameters for Wind Speed on Phangan Island, Thailand

AbstractThe Weibull distribution has been widely used to represent the time distribution of wind speed. The two parameters to fit are k for shape and c for scale, and five methods were compared to estimate these Weibull parameters. Wind speed data from January 2012 to December 2014 from Phangan island were used with the fitting methods, namely empirical, energy pattern factor, maximum likelihood, modified maximum likelihood, and graphical method. The goodness of fit was quantified using Kolmogorov-Sminorv test, R2, RMSE and the percent error of wind power density. With these data, the energy pattern factor method performed the best in terms of percent error of power density, and had the highest R2. The graphical method performed the worst among these methods, in this case study

Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand

Situated in the southern part and on the western coast of Thailand, the Andaman Coast covers the provinces of Ranong, Phangnga, Phuket, Krabi, Trang and Satun. Using a coupled mesoscale atmospheric model and a microscale wind flow model, along with computational fluid dynamics (CFD) modeling, this paper presents a detailed assessment of the wind energy potential for power generation along the Andaman Coast of Thailand. The climatic data are obtained from the Modern Era Retrospective analysis for Research and Applications (MERRA), along with a high-resolution topography database and Land Use Land Cover digital data. The results are compared to the equivalent wind speeds obtained with the Weather Research and Forecasting (WRF) atmospheric model. The results showed that, at 120 m above ground level (agl), the predicted wind speeds from the models proposed were 20% lower for the mesoscale model and 10% lower for the microscale model when compared to the equivalent wind speeds obtained from the WRF model. A CFD wind flow model was then used to investigate 3D wind fields at 120–125 m agl over five potential sites offering promising wind resources. The annual energy productions (AEP) and the capacity factors under three different wake loss models and for five wind turbine generator technologies were optimized for 10-MW wind power plants, as per Thailand’s energy policies. With capacity factors ranging from 20 to 40%, it was found that the AEPs of the best sites were in the range of 18–36 GWh/year, with a total AEP in the vicinity of 135 GWh/year when using a single wind turbine model for the five sites studied. The combined energy productions by these wind power plants, once operational, could avoid GHG emissions of more than 80 ktons of CO2eq/year.</jats:p