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Wind Energy Simulation in China: 

Wind Energy Simulation in China Zhang De Center For Wind And Solar Energy Resources Assessment, CMA zhangde@cma.gov.cn

Fast Development of global wind power: 

Fast Development of global wind power Increasing capacity installed For the last five years, installed capacity of global wind power has been rapidly growing with an average rate of 26.3%. Global installed capacity (10MW) and market share by 2005

Fast Development of Wind Power in China: 

Fast Development of Wind Power in China By the end of 2005, 61 wind farms are built with 1864 wind turbines and 1266 MW of capacity installed. Installed wind power capacity takes the eighth globally, and second in Asia (following India), the scale of installed capacity reaches a new milestone.

Slide4: 

Up to 2020 The installed capacity of wind power will reach 30,000MW. Twenty large wind farms with installed capacity of 10 MW in plan.

Slide5: 

The wind resources assessment based on meteorological observation at height of 10m do not meet the needs of scale-up development of wind power. The high resolution assessment combined meteorological tower observation and numerical simulation become pressing.

The WEST Application in China : 

The WEST Application in China In 2005, China Meteorological Administration (CMA) and Meteorological Service of Canada (MSC) have agreed to cooperate in wind resource simulation. Both sides will make effort to improve Wind Energy Simulation Toolkit（WEST）, and complete the wind energy atlas of China and the new atlas of Canada.

Outline: 

Outline 1. Wind Energy Simulation Toolkit（WEST） 2. The WEST Application in China 3. Conclusion and Discussions

1. Wind Energy Simulation Toolkit (WEST): 

1. Wind Energy Simulation Toolkit (WEST) Methodology: Statistical dynamical downscaling approach Components: 1 Classification of long term climate data (NCAR/NCEP reanalysis) 1.2 Mesoscale Model of basic atmospheric flow (MC2) 1.3 Statistical Output of wind atlas

1. Wind Energy Simulation Toolkit (WEST): 

A set of basic weather situations is defined, using long-term global-dataset. Numerical simulations of these situations are performed with high resolution terrain data to calculate the wind energy atlas. 1. Wind Energy Simulation Toolkit (WEST) Global simulation Mesoscale Model resolution: 250 km resolution : 5 km

1.1 Classification Module of WEST: 

1.1 Classification Module of WEST NCEP / NCAR reanalyses ~40 years / 6 hr Cell-wise time series (250 km) Classification Parameters: Geostrophic wind speed (x14) Geostrophic wind direction (x16) Vertical shear of speed between 1500 and 0 m AGL (x2) Standardize “climate states” (14×16×2=432 possible climate states ) Result: frequency of occurrence tables

1.1 Classification Module of WEST: 

1.1 Classification Module of WEST Classification results examples (Latitude: 52.467 Longitude: 128.352) Every tables contains :

1.2 Mesoscale Module of WEST: 

1.2 Mesoscale Module of WEST The Mesoscale Compressible Community Model (MC2) is used for mesoscale model within the WEST procedure. The control equation of MC2 is fully elastic compressible non-hydrostatic and limited area Euler equation . It’s numerical scheme is the semi-implicit semi-Lagrangian (SISL) time scheme.

1.2 Mesoscale Module of WEST: 

Wind speed at 50 m Topography Roughness 1.2 Mesoscale Module of WEST Input: - Topography data - Roughness data - Frequency distribution as function of wind speed and direction sector Repeat simulation for each “climate states”

1.3 Statistical Module of WEST: 

1.3 Statistical Module of WEST After mesoscale modeling, the simulated results for each class are weighted with their occurrence frequency to build a database of statistics.

2. The WEST Application in China: 

2. The WEST Application in China For complete china wind atlas, this work divided the whole China into 52 domains for WEST simulation. WEST was set up at a grid spacing of 5 km to every domain. There are 175×175 grid-points and 28 vertical levels in every damians. The terrain information (elevation, land use, etc.) is from the USGS 1-km database.

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IBM cluster 1600 - IBM supercomputer in operation at CMA - Speed :215×1012 time/second - 4000 CPU Storage Space: 16 620 MC2 simulations Every simulations need 4 hours on IBM1600 1.8 Terabit data (1.8×1012) 2. The WEST Application in China

2. The WEST Application in China: Simulated Results : 

2. The WEST Application in China: Simulated Results Finally, China wind atlas is completed by merging the simulation results of the 52 domains. Mean wind-speed in China at 80m produced by WEST

The WEST Application in China Simulated Result : 

The WEST Application in China Simulated Result The areas with high wind-speed are the northern of Xinjiang, Inner Mongolia and the northwestward of Gansu province, where wind resources are just rich in China. The following is the southeast costal areas of China where the mean wind-speed is over 7m/s, especially the coast of Zhejiang and Fujian province. The WEST results are similar to the China atlas made by the data from more than 600 meteorological stations. China atlas made produced by WEST China atlas made by the meteorological stations data

The WEST Application in China Results Analysis : 

The WEST Application in China Results Analysis The simulated results are compared with the data at a height of 10 m AGL, which come from 683 meteorological stations in China. The mean absolute difference between the observed and simulated sets of wind data is 0.95 m /s. The correlation coefficient is about 0.43. Correlation coefficient of the mean wind-speed between the simulations and observations

The WEST Application in China Results Analysis: 

The WEST Application in China Results Analysis The number of stations which the relative error less than 20% is 239, it’s about one third of all the 683 stations. Among these stations, there are 148 stations with relative error less than 10%. It can be see that the stations which simulation result is much better are mostly located in the eastern and the costal area of China. In those areas, there are many extensive plain, where averaged elevations are lower than 500 m ASL. red point < 10% black point < 20% Stations which relative error less than 20%

The WEST Application in China Results Analysis: 

The WEST Application in China Results Analysis The number of stations which the relative error lager than 60% is 222, it’s also about one third of all the stations. Among these stations, there are 144 stations with relative error lager than 100% . The stations with large errors are mostly located in the western of China, where has many extensive mountains, hills, and highlands cover plain. Especially in the verge of Qingzang plateau, the result does not satisfy. B: Stations which relative error lager than 60%: black point > 60% red point > 100%

The WEST Application in ChinaResults Analysis: 

The WEST Application in China Results Analysis A : The annual wind energy density in Liaoning province produced by WEST. B: The annual wind energy density complete with meteorological stations, tower observations and modeling results in the third Liaoning wind energy investigation. Compare two of them, WEST has good ability to simulate the wind power distribution in Liaoning and can present the rich areas and the poor areas. A: The WEST results in Liaoning B: The third wind energy investigate results in Liaoning

The WEST Application in China Results Analysis: 

The WEST Application in China Results Analysis The simulation results are evaluated with data at a height of 10 m ASL, which come from 56 meteorological stations. The mean absolute difference between the observed and simulated data is 0.477 m /s. The correlation coefficient is about 0.773, the relative error is about 19.4%

3. CONCLUSIONS: 

3. CONCLUSIONS I The WEST has good ability to simulate the wind power distribution by comparing with observed result in mid-east China at low altitude areas, but the simulating ability is not very good in complex terrain and high-altitude, especially in mountain areas, so it’s needed to modify. II WEST may be improved the classification scheme. The climate states can be classified according to the geostrophic wind direction and speed, the vertical shear of wind speed, temperature and buoyancy. III The parameter schemes in the atmosphere boundary-layer also needed to be improved, so that WEST can be suitable to wind energy resource assessment in China.