The objective of this work was to assess the accuracy of various coupled mesoscale-microscale wind flow modeling methodologies for wind energy applications. This is achieved by examining and comparing mean wind speeds from several wind flow modeling methodologies with observational measurements from several 50 m met towers distributed across the study area. At the mesoscale level, with a 5 km resolution, two scenarios are examined based on the Mesoscale Compressible Community Model (MC2) model: the Canadian Wind Energy Atlas (CWEA) scenario, which is based on standard input data, and the CWEA High Definition (CWEAHD) scenario where high resolution land cover input data is used. A downscaling of the obtained mesoscale wind climate to the microscale level is then performed, where two linear microscale models, i.e., MsMicro and the Wind Atlas Analysis and Application Program (WAsP), are evaluated following three downscaling scenarios: CWEA-WAsP, CWEA-MsMicro and CWEAHD-MsMicro. Results show that, for the territory studied, with a modeling approach based on the MC2 and MsMicro models, also known as Wind Energy Simulation Toolkit (WEST), the use of high resolution land cover and topography data at the mesoscale level helps reduce modeling errors for both the mesoscale and microscale models, albeit only marginally. At the microscale level, results show that the MC2-WAsP modeling approach gave substantially better results than both MC2 and MsMicro modeling approaches due to tweaked meso-micro coupling.

A strategic challenge facing all governments today is how to deliver services effectively and efficiently. At one time, they thought that they could meet this challenge by exploiting technology and going the E-government route with the promise of single-window, integrated, intelligent service delivery. Very quickly, however, they had to accept the fact that they would have to overcome a multitude of obstacles and that individual and corporate clients often preferred to receive service in traditional ways. As a result, the delivery of public services is becoming increasingly multichannel: over the counter, by mail and telephone, over the Internet, via text and television, etc. There is therefore a need to identify some kind of model for managing this highly complex new phenomenon effectively and efficiently. By conducting research in the field with the help of case studies and international benchmarking, it was possible to identify the main variables in the degree of effectiveness and efficiency of multichannel public service delivery and develop the outline of a model representing the underlying factors.

This paper presents the wind resource assessment of the southernmost region of Thailand using atmospheric and computational fluid dynamics (CFD) wind flow modeling. The predicted wind data by the Weather Research and Forecasting (WRF) atmospheric modeling, assimilated to a virtual met mast, along with high-resolution topographic and roughness digital data, are then used as the main input for the CFD microscale wind flow modeling and high resolution wind resource mapping at elevations of 80 m, 100 m, 120 m, and 140 m agl. Numerical results are validated using measured wind data. Results show that the potential area where the wind speeds at 120 m agl are above 8.0 m/s is 86 km², corresponding to a technical power potential in the order of 300 MW. The installation of wind power plants in the areas with the best wind resource could generate 690 GWh/year of electricity, thus avoiding greenhouse gas emissions of 1.2 million tonnes CO_2eq/year to the atmosphere. On the other hand, developing power plants with International Electrotechnical Commission (IEC) Class IV wind turbines in areas of lower wind resource, but with easier access, could generate nearly 3000 GWh/yr of energy, with a CO_2eq emissions avoidance of 5 million tonnes CO_2eq on a yearly basis.