Evaluation of wind energy potential over Thailand by using an atmospheric mesoscale model and a GIS approach

Janjai, Serm; Masiri, Itsara; Promsen, Worrapass; Pattarapanitchai, S.; Pankaew, P.; Laksanaboonsong, J.; Bischoff‐Gauß, I.; Kalthoff, Norbert

doi:10.1016/j.jweia.2014.03.010

Cited by 35 publications

(21 citation statements)

References 25 publications

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“…This annual average wind speed data set for Sweden was derived with the help of a three-dimensional meso-scale higherorder numerical model developed at the Meteorological Institute of Uppsala University (MIUU) in Sweden; aiming to investigate the wind climate in Sweden [51]. The meso-scale high order numerical models are used to predict the annual average wind speed and other weather phenomena having a horizontal grid reolution ranging between 1 km Â 1 kme10 km Â 10 km [52,53]. The MIUU-model is capable of mapping the annual average wind speed resources having resolutions between 0.5 and 10 km, using input data such as geostrophic wind (strength and direction), sea and land temperatures, topography, and roughness.…”

Section: Wind Speed and Spatial Data Layersmentioning

confidence: 99%

“…Most of the time, for wind energy assessment at a location, Weibull distribution is used with hourly wind speed data obtained from specific wind speed observation sites located there. However, the wind speed observation sites are located many kilometers away from each other throughout the land area of the country [52,63]. Therefore, hourly wind speed data obtained from those scattered wind speed observation sites cannot be used directly to estimate the Weibull parameters and the wind energy potential available in each 1 km Â 1 km sized grid cell throughout the land area of a country, for GIS-based studies.…”

Section: Wind Speed Distributionmentioning

confidence: 99%

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Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach

Siyal

Mörtberg

Mentis

et al. 2015

Energy

104

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Section: Wind Speed and Spatial Data Layersmentioning

confidence: 99%

Section: Wind Speed Distributionmentioning

confidence: 99%

Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach

Siyal

Mörtberg

Mentis

et al. 2015

Energy

104

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“…Mesoscale models introduce analytical information through databases about terrain roughness. The effect of terrain roughness on the wind shear has been discussed and validated in several works based on simulations [21] and measurements [22]. Friction from the ground slows the wind down, especially during the night, while during the day the effect is minimized thanks to convective mixing.…”

Section: Overview Of the Resulted Wind Potential In Chinamentioning

confidence: 99%

Development of Aeolian map of China using mesoscale atmospheric modelling

et al. 2015

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a b s t r a c tA mesoscale atmospheric modelling is applied in China aiming at the development and representation of Aeolian maps. The understanding of wind resource characteristics in the country with the highest wind installed capacity and the largest prospects for further wind energy development is an essential step for the further analysis of important issues related with large scale wind integration. In this connection, the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) developed at the US Naval Research Laboratory was used. Systematic application of COAMPS, with appropriate adjustment of numerical parameters for one year was carried out for China providing simultaneous information of wind statistics over every potential area for wind farm development. Analysis and processing of this information lead to the creation of mesoscale Aeolian maps over the country. Additionally, analytical wind data time-series have been reproduced providing simultaneous information of wind speed for one year. These data are essential inputs for computational tools to analyse large scale wind integration issues, simulate the whole power system of China or one of the subsystems, estimate wind energy curtailment and wind capacity credit, analyse storage solutions like hydro pumped storage and smart grids.

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“…Such presentations of information are ideal to determine hot spots of resource availability and to select the best locations for installations that generate as much energy as possible. When these resource availability maps are integrated in GIS, it is possible to combine the maps with multiple technical, economical and regulatory parameters in order to estimate deployment potentials of PV installations [57][58][59][60][61] or wind parks [62][63][64][65][66][67][68][69].…”

Section: Gis and Biomassmentioning

confidence: 99%

Spatiotemporal modelling for integrated spatial and energy planning

Camargo

Stoeglehner

2018

Energ Sustain Soc

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The transformation of the energy system to a renewable one is crucial to enable sustainable development for mankind. The integration of high shares of renewable energy sources (RES) in the energy matrix is, however, a major challenge due to the low energy density per area unit and the stochastic temporal patterns in which RES are available. Distributed generation for energy supply becomes necessary to overcome this challenge, but it sets new pressures on the use of space. To optimize the use of space, spatial planning and energy planning have to be integrated, and suitable tools to support this integrated planning process are fundamental. Spatiotemporal modelling of RES is an emerging research field that aims at supporting and improving the planning process of energy systems with high shares of RES. This paper contributes to this field by reviewing latest developments and proposing models and tools for planning distributed energy systems for municipalities. The models provide estimations of the potentials of fluctuating RES technologies and energy demand in high spatiotemporal resolutions, and the planning tools serve to configure energy systems of multiple technologies that are customized for the local energy demand. Case studies that test the spatiotemporal models and their transferability were evaluated to determine the advantages of using these instead of merely spatial models for planning municipality-wide RES-based energy systems. Spatiotemporal models allow a more detailed estimation of RES potentials and serve to find not only optimal locations but also optimal sizes for individual RES plants. While the potential of variable RES based on yearly energy generation values can be considerably larger than the energy demand, only a fraction of it can be deployed without compromising the quality and reliability of the local energy supply system. Furthermore, when spatiotemporal models are used, it can be seen that technological diversity is beneficial for the supply quality. Similarly, the advantages and limits of the deployment of storage systems and of combinations of RES-based technologies to cover the local demand were determined and evaluated. Finally, the results from the analyses provide sufficient information to define road maps of installations deployment to achieve desired RES penetration objectives.

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Evaluation of wind energy potential over Thailand by using an atmospheric mesoscale model and a GIS approach

Cited by 35 publications

References 25 publications

Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach

Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach

Development of Aeolian map of China using mesoscale atmospheric modelling

Spatiotemporal modelling for integrated spatial and energy planning

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