In the paper,daily near-surface wind speed data from 462 stations are used to study the spatiotemporal characteristics of the annual and seasonal mean wind speed(MWS)and effective wind energy density(EWED)from 1960 to...In the paper,daily near-surface wind speed data from 462 stations are used to study the spatiotemporal characteristics of the annual and seasonal mean wind speed(MWS)and effective wind energy density(EWED)from 1960 to 2016,through the methods of kriging interpolation,leastsquares,correlation coefficient testing,and empirical orthogonal function(EOF)analysis.The results show that the annual MWS is larger than 3 m s-1 and the EWED is larger than 75 W m-2 in northern China and parts of coastal areas.However,the MWS and EWED values in southern China are all smaller than in northern China.Over the past 50 years,the annual and seasonal MWS in China has shown a significant decreasing trend,with the largest rate of decline in spring for northern China and winter for coastal areas.The annual MWS in some areas of Guangdong has an increasing trend,but it shows little change in southwestern China,South China,and west of Central China.Where the MWS is high,the rate of decline is also high.The main spatial distributions of the annual MWS and the annual EWED show high consistency,with a decreasing trend year by year.The decreasing trend of wind speed and wind energy resources in China is mainly related to global warming and land use/cover change.展开更多
With high resolution （1 kin）, the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit （WEST） model developed b...With high resolution （1 kin）, the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit （WEST） model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software Wasp （Wind Atlas Analysis and Application Program）. The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST＋WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.展开更多
The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaW...The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaWinds-derived Weibull mean wind speed and energy density by considering uncertainties inherent in SeaWinds wind speed estimates. In this study, 1159 SeaWinds-derived wind speeds covering the KEO buoy are used for estimating two Weibull parameters, scale and shape. On the other hand, observed wind speeds from 2004 to 2008 at the KEO buoy are used for simulating three kinds of wind speeds in order to quantify some uncertainties inherent in SeaWinds-derived wind speeds. It is found that uncertainties associated with wind speed estimates （operational wind speed range, sampling time） show small differences in scale, shape and Weibull mean wind speed except energy density among the simulated datasets. Furthermore, the upper and lower bounds of 90% confidence interval corresponding to SeaWinds number of observations indicate 4-2.5% error of Weibull mean wind speed and 4-6.8% error of energy density, respectively.展开更多
基金This work was supported by the National Key R&D Program of China[grant numbers 2016YFA0600403 and 2016YFA0602501]the General Project of the National Natural Science Foundation of China[grant number 41875134].
文摘In the paper,daily near-surface wind speed data from 462 stations are used to study the spatiotemporal characteristics of the annual and seasonal mean wind speed(MWS)and effective wind energy density(EWED)from 1960 to 2016,through the methods of kriging interpolation,leastsquares,correlation coefficient testing,and empirical orthogonal function(EOF)analysis.The results show that the annual MWS is larger than 3 m s-1 and the EWED is larger than 75 W m-2 in northern China and parts of coastal areas.However,the MWS and EWED values in southern China are all smaller than in northern China.Over the past 50 years,the annual and seasonal MWS in China has shown a significant decreasing trend,with the largest rate of decline in spring for northern China and winter for coastal areas.The annual MWS in some areas of Guangdong has an increasing trend,but it shows little change in southwestern China,South China,and west of Central China.Where the MWS is high,the rate of decline is also high.The main spatial distributions of the annual MWS and the annual EWED show high consistency,with a decreasing trend year by year.The decreasing trend of wind speed and wind energy resources in China is mainly related to global warming and land use/cover change.
基金Project for Popularization of Advanced Meteorological Technology for 2006, China Meteorological Administration (CMATG2006M41)
文摘With high resolution （1 kin）, the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit （WEST） model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software Wasp （Wind Atlas Analysis and Application Program）. The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST＋WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.
文摘The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaWinds-derived Weibull mean wind speed and energy density by considering uncertainties inherent in SeaWinds wind speed estimates. In this study, 1159 SeaWinds-derived wind speeds covering the KEO buoy are used for estimating two Weibull parameters, scale and shape. On the other hand, observed wind speeds from 2004 to 2008 at the KEO buoy are used for simulating three kinds of wind speeds in order to quantify some uncertainties inherent in SeaWinds-derived wind speeds. It is found that uncertainties associated with wind speed estimates （operational wind speed range, sampling time） show small differences in scale, shape and Weibull mean wind speed except energy density among the simulated datasets. Furthermore, the upper and lower bounds of 90% confidence interval corresponding to SeaWinds number of observations indicate 4-2.5% error of Weibull mean wind speed and 4-6.8% error of energy density, respectively.
