Research on Representative Engineering Applications of Anemometer Towers Location in Complex TopographyWind Resource Assessment

The typical location and number of anemometer towers in the assessed area are the key to the accuracy of wind resource assessment in complex topography.As calculation examples,this paper used two typical complex topography wind farms in Guangxi,Yunnan province in China.Firstly,we simulated the wind resource status of the anemometer tower in the Meteodyn WT software.Secondly,we compared the simulated wind resource with the actual measured data by the anemometer tower in the same situation.Thirdly,we analyzed the influence of anemometer tower location and quantity in the accuracy of wind resource assessment through the comparison results.The results showed that the range which the anemometer tower can represent is limited(<5 kilometers),and the prediction error more than 5%.Besides,the anemometer towers in special terrain areas(such as wind acceleration areas)cannot be used as a representative choice.The relative error of the simulated average annual wind speed by choose different number of anemometer towers is about 4%,and the grid-connected power generation more than 6%.The representative effect of anemometer towers is of crucial for improving the accuracy of wind resource assessment in engineering applications.

Wind Energy Data Analysis and Resource Mapping of Dangla,Gojjam,Ethiopia

Energy is one of the most important factors in socio-economic development.The rapid increase in energy demand and air pollution has increased the number of ways to generate energy in the power sector.Currently,wind energy capacity in Ethiopia is estimated at 10,000 MW.Of these,however,only eight percent of its capacity has been used in recent years.One of the reasons for the low use of wind energy is the lack of accurate wind atlases in the country.Therefore,the purpose of this study is to develop an accurate wind atlas and review the wind resources using Wind Atlas Analysis and Application Program in Dangla so that the best sites used for the installation of wind farms can be easily identified.Wind climatology data,vector maps,and wind turbine data were used to model the Wind Atlas Analysis and Application Program.The wind data collected from National Meteorology Survey Agency over three years were used for the analysis.Besides,vector data for the survey area was prepared using Global Mapper V20.1.In this study,the Wind Atlas Analysis and Application Program tool was used to estimate wind resources.The wind resource map was developed at an altitude of 80 m above ground level,and a horizontal axis type wind generator called(i.e.,GridStreamer Vestas V1001.8 MW)was selected from the Wind Atlas Analysis and Application Program catalog to mimic the wind farm.The results obtained from the analysis of actual wind data showed that the minimum wind speed was 0.12083 m/s while the maximum wind speed was 9.96389 m/s.At a height of 10 m a.g.l.,the mean wind speed and wind power density were 1.8 m/s and 9 w/m2,respectively.The most common wind direction was also discovered to be 210 degrees.The maximum wind speed and capacity factor were available around hills,according to the wind resource map,and the net annual energy output of the Dangla wind farm at a turbine height of 80 m a.g.l.was found to be 282.726 GWh(or,32.27 MW).The farm’s capacity factor was also discovered to be 9.54 percent,indicating that the site is rated as low potential.

Wind Shear Investigation for Site-Specific Wind Turbine Performance Assessment

The wind energy assessment studies are generally performed referring to neutral stability conditions for the atmosphere; this is considered a good hypothesis because neutral conditions characterize the high wind situations. However the increasing size of modem multi megawatt wind turbines allows to produce energy even in low wind regimes and non-neutral conditions can involve significant production period. In such situations the variations of the vertical wind shear can affect the energy production in a sensible way and it could be fundamental to investigate how atmospheric stability and orography can affect the wind profile and the power conversion. In this paper meso-scale numerical data, CFD modeling and remote sensed wind data were used in order to analyze such behavior and to understand how wind shear influences the energy content and the discussion about how to adjust the power curve to the site specific conditions.

Assessment of wind energy potential in China

China wind atlas was made by numerical simulation and the wind energy potential in China was calculated. The model system for wind energy resource assessment was set up based on Canadian Wind Energy Simulating Toolkit (WEST) and the simulating method was as follows. First, the weather classes were obtained depend on meteorological data of 30 years. Then, driven by the initial meteorological field produced by each weather class, the meso-scale model ran for the distribution of wind energy resources according each weather class condition one by one. Finally, averaging all the modeling output weighted by the occurrence frequency of each weather class, the annual mean distribution of wind energy resources was worked out. Compared the simulated wind energy potential with other results from several activities and studies for wind energy resource assessment, it is found that the simulated wind energy potential in mainland of China is 3 times that from the second and the third investigations for wind energy resources by CMA, and is similar to the wind energy potential obtained by NREL in Solar and Wind Energy Resource Assessment(SWERA) project. The simulated offshore wind energy potential of China seems smaller than the true value. According to the simulated results of CMA and considering lots of limited factors to wind energy development, the final conclusion can be obtained that the wind energy availability in China is 700～1 200 GW, in which 600～1 000 GW is in mainland and 100～200 GW is on offshore, and wind power will become the important part of energy composition in future.

Analysis of Offshore Wind Power： Application to Southern Thailand

This paper presents an analysis of a pre-feasibility study of a 10 MW offshore wind power project in Nakhon Si Thammarat province, southern Thailand. The wind speeds at the hub heights of large scale wind turbine generators （WTG）, i.e. 80-100 m, were extrapolated using monthly mean wind shear coefficients and the l/7th exponent. Using WAsP 9.0, the annual energy production from several models of offshore wind farms using different WTG was analyzed. The capacity factor and the cost of energy were then computed. Using best available estimates, the analysis shows that the estimated annual mean offshore wind speeds at 80-100 m were in the range of 6.4 and 8.3 m/s. The annual energy production by the wind farm from nine models of wind turbine generators were in the range of 20-39 GWh/year, corresponding to a capacity factor in the range of 26-46%, while the cost of energy was 12-15 US cent/kWh.

Characteristics of Wind Speed Profiles under Complex Terrain Conditions in Loess Plateau

To reveal the changing characteristics of wind speed with altitude in under complex terrain conditions in Loess Plateau in Northern Shaanxi, based on the complete data of wind speed profiles of six wind towers in the region in a year, the diurnal, monthly, and seasonal variations of wind shear index of the wind towers as well as the changes of wind shear index with wind speed under complex terrain conditions were studied. The results showed that the wind shear index of each wind tower was positive, showing that wind speed tended to increase with the rising of altitude in most areas of Loess Plateau in Northern Shaanxi; terrain had obvious effects on wind speed profiles. The wind shear index of the wind towers was small during the day and large at night; the differences between day and night in the wind shear index of various wind towers were different; there were obvious seasonal variations in the wind shear index of the wind towers under different terrain conditions. With the increase of wind speed, the wind shear index of each wind tower increased firstly and then decreased, but the peaks of wind shear index of various wind towers ap- peared in different wind speed ranges. When wind speed varied from 3 to 12 m/s, wind shear index was larger than the comprehensive wind shear index of the wind towers, which is beneficial to the improvement of power generation of a wind power plant. Wind shear index can be used to assess wind resources of a wind power plant.

Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density to assess wind resource.The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China.The air density at 100 m height is accurately calculated by using air temperature,pressure,and humidity.The spatial-temporal variation features of air density are firstly analyzed.Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,respectively.Usingρstoverestimates the annual wind energy production(AEP)in 93.6%of the study area.Humidity significantly affects AEP in central and southern China areas.In more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated.Usingρsitesignificantly reduces the estimation error in AEP.But AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in winter.Except for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρsite.Usingρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as well.The impacts of air density on assessing wind resource are almost independent of the wind turbine types.