Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago

Fang, Hsin-Fa

doi:10.1016/j.renene.2013.11.047

Cited by 51 publications

(24 citation statements)

References 4 publications

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“…In 2015, Ko et al assessed small-scale wind energy potential in Chuuk State of Micronesia based on meteorological observation data [15]. In 2014, Fang studied nearshore wind energy potential on the west coast of Taiwan and Penghu Islands based on a mesoscale numerical weather prediction model (MM5) [16]. In 2013, Rusu and Onea assessed wind energy for the Caspian Sea using ECMWF wind data [17].…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Joint Development Potential of Wave and Wind Energy in the South China Sea

et al. 2018

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Abstract:The South China Sea is a major shipping hub between the West Pacific and Indian Oceans. In this region, the demand for energy is enormous, both for residents' daily lives and for economic development. Wave energy and wind energy are two major clean and low-cost ocean sources of renewable energy. The reasonable development and utilization of these energy sources can provide a stable energy supply for coastal cities and remote islands of China. Before wave energy and wind energy development, however, we must assess the potential of each of these sources. Based on high-resolution and high-accuracy wave field data and wind field data obtained by ERA-Interim reanalysis for the recent 38-year period from 1979-2016, the joint development potential of wave energy and wind energy was assessed in detail for offshore and nearshore areas in the South China Sea. Based on potential installed capacity, the results revealed three promising areas for the joint development of nearshore wave energy and wind energy, including the Taiwan Strait, Luzon Strait and the sea southeast of the Indo-China Peninsula. For these three dominant areas (key stations), the directionality of wave energy and wind energy propagation were good in various seasons; the dominant wave conditions and the dominant wind conditions were the same, which is advantageous for the joint development of wave and wind energy. Existing well-known wave energy converters (WECs) are not suitable for wave energy development in the areas of interest. Therefore, we must consider the distributions of wave conditions and develop more suitable WECs for these areas. The economic and environmental benefits of the joint development of wave and wind energy are high in these promising areas. The results described in this paper can provide references for the joint development of wave and wind energy in the South China Sea.

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Section: Introductionmentioning

confidence: 99%

Assessment of the Joint Development Potential of Wave and Wind Energy in the South China Sea

et al. 2018

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“…Wind speed statistics, as a basic descriptor of regional or local climate change, have provided significant information in global climate change, transportation, urban construction, city planning, utilization of wind energy resources, and other fields (Xu et al 2006;Yiannis and George 2014;Fang 2014;Soukissian and Karathanasi 2016). Therefore, it is necessary to homogenize climate data before assessing interannual and multidecadal variabilities in wind speed (Pryor et al 2009;Fu et al 2011;Chen et al 2013;William and Martha 2014).…”

Section: Introductionmentioning

confidence: 99%

Homogenization of Tianjin monthly near-surface wind speed using RHtestsV4 for 1951–2014

Luo

Liang

2017

Theor Appl Climatol

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Historical Chinese surface meteorological records provided by the special fund for basic meteorological data from the National Meteorological Information Center (NMIC) were processed to produce accurate wind speed data. Monthly 2-min near-surface wind speeds from 13 observation stations in Tianjin covering 1951-2014 were homogenized using RHtestV4 combined with their metadata. Results indicate that 10 stations had significant breakpoints-77% of the Tianjin stations-suggesting that inhomogeneity was common in the Tianjin wind speed series. Instrument change accounted for most changes, based on the metadata, including changes in type and height, especially for the instrument type. Average positive quantile matching (QM) adjustments were more than negative adjustments at 10 stations; positive biases with a probability density of 0.2 or more were mainly concentrates in the range 0.2 m s −1 to 1.2 m s −1 , while the corresponding negative biases were mainly in the range −0.1 to −1.2 m s −1 . Here, changes in variances and trends in the monthly mean surface wind speed series at 10 stations before and after adjustment were compared. Climate characteristics of wind speed in Tianjin were more reasonably reflected by the adjusted data; inhomogeneity in wind speed series was largely corrected. Moreover, error analysis reveals that there was a high consistency between the two datasets here and that from the NMIC, with the latter as the reference. The adjusted monthly near-surface wind speed series shows a certain reliability for the period 1951-2014 in Tianjin.

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“…In the wind energy sector, such characterisation exercises, referred to as resource assessments, are carried out to assess the wind energy availability and predict prevailing wind patterns at potential sites for new wind power plants [1][2][3][4]. This is necessary for project financiers and operators to estimate the power output from the plant and hence calculate the potential returns from the investment.…”

Section: Introductionmentioning

confidence: 99%

Variance Characteristics of Tropical Radiosonde Winds Using a Vector-Tensor Method

et al. 2018

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Abstract:In this paper, an exploratory study on the variance characteristics of upper-air winds in a near-equator monsoon region is presented. The data were obtained from historical radiosonde observations from up to 250 stations within the region of interest for the period between 1954 and 2013. An alternative method based on vector statistics was employed in this study which characterises the mean by a vector and the variance by a tensor. Unlike the conventional approach of using scalar wind speeds, this vector-tensor approach allows the directional properties of the variance to be studied. A suite of statistics to describe the geometric properties of the variance tensor was also developed. These characterise the size of the variance, its degree of anisotropy, and the alignment of the preferred direction (if anisotropy is present) with the direction of the mean wind vector. Through analysis of these statistics, several salient trends were observed for the middle troposphere. It was found that the variance size and anisotropy exhibit significant variation with height whereas the alignment with the mean vector varies with the mean wind magnitude instead. It was also found that the scalar variance increases with mean wind speed.

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Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago

Cited by 51 publications

References 4 publications

Assessment of the Joint Development Potential of Wave and Wind Energy in the South China Sea

Assessment of the Joint Development Potential of Wave and Wind Energy in the South China Sea

Homogenization of Tianjin monthly near-surface wind speed using RHtestsV4 for 1951–2014

Variance Characteristics of Tropical Radiosonde Winds Using a Vector-Tensor Method

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