Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand

This paper presents the offshore wind resource assessment and an offshore wind power plant optimization in the Gulf of Thailand (GoT). The Weather Research and Forecasting (WRF) atmospheric model, along with the NCEP/NCAR R2 reanalysis climatic database, are applied to create wind resource maps at 80 m, 100 m, and 120 m above mean sea level (amsl) in order to identify the potential surface areas for the development of offshore wind power plants. The predicted wind speeds are validated using observed wind speeds obtained from 13 met masts installed along the coastline of the GoT. Results show that the average annual mean wind speeds reach the range of 5.5-6.5 m/s in specific areas of the Bay of Bangkok, situated in the northern part of the GoT. Based on the results of the wind resource assessment and using computational fluid dynamics microscale wind flow modelings, a wind power plant optimization is performed. The technical power potential and a priority zoning for offshore wind power development is performed using wind turbine generators of 3.3-8.0 MW capacity. Depending on the wind turbine generator selected, it is found that 642-924 MW of capacity could be installed in the short-term planning; 2658 to 3825 MW of additional capacity could be added in the medium-term planning, and 2864 to 4120 MW of additional capacity in the long-term planning. These wind power plants would have an annual energy production in the order of 5.68 PWh in the short-term, an additional 23 to 33 PWh in the medium-term, and an additional 25 to 36 PWh in the long-term, thus avoiding CO2eq emissions in the order of 3-4.5 million tons CO2eq per year in the short-term, 13 to 18 million tons in the medium-term, and 14 to 20 million tons in the long-term. In total, depending on the wind turbine generator selected, wind power plants in the GoT could have a total installed capacity of 6000 to over 8000 MW, would generate between 50 and 75 PWh of energy per year, while avoiding emissions of 30-40 million tons CO2eq per year. (C) 2017 Elsevier Ltd. All rights reserved.