Cao Xiao

September, 2013

Wind Power Forecasting

Disclaimer: The views expressed in this document are those of the author, and do not necessarily reflect the views and policies of the Asian Development Bank (ADB), its Board of Directors, or the governments they represent. ADB does not guarantee the accuracy of the data included in this document, and accept no responsibility for any consequence of their use. By making any designation or reference to a particular territory or geographical area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

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Current  situation of forecast technology

Key technology of forecast

Forecast principle of wind power

Development of forecast technology

Content

Cooperation with ADB

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1.The technology has a long history and higher level at abroad.

2.The forecast technology has not been studied in China until 2007 .

3.The major method :statistic & physical.

4.The monthly RMSE criterion : (short-term) less than 20%， (ultra-short term) less than 15%.

Current  situation of forecast technology

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Forecast principle of wind power

Wind Forecasting Model

Statistical & Physical method

AWS

Real-time Data

AWS

Historical Data

Mast

Real-time Data

Mast

Historical Data

Numerical Weather Prediction(NWP)

Wind Farm

Real-time Data

Wind Turbine

Historical Data

Human-computer Interface

Mast

Historical DataPower Forecasting Model

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Forecast principle of wind power

Statistic Method:building the relativity between weather element and power output.1 .The different mathematical models could be adopted.

2. The large amount of historical data is needed to conduct training.

3. The regular retraining for the model is needed.

Physical Method: calculate wind speed and direction at the hub height.

1.NWP, WT/WasP and so on could be adopted to calculate the wind speed and direction in the surface layer.

2.Boundary conditions are needed.

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Key technology of forecast

Technology of Real-time Weather Date AcquisitionWeather element : wind speed/direction, temperature, humidity, air pressure, radiation Height :10/30/70meters and hub height.

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Key technology of forecast

Numerical Weather Prediction:

1. Regard GFS (global forecasting system) as the background field.

2. Based on ADAS (ARPS Data Analysis System).

3. Combine large amount of locally actual measurement data.

4. Debug Mesoscale model WRF.

5. Adopt application technology

output 0-72 hours’ forecast value of wind speed and direction.

measurement data

ADAS

WRF

GFS

Forecast value

data processing  server

ApplicationTechnology

detailed forecast value

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Key technology of forecast

Technology of Forecast Modeling :1.Establish weather forecast model by the combination of statistic and physical methods.

2.Establish power forecast models in accordance with the conditions ( geography and climate features , type and distribution of wind turbine and so on).

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1、 The Diversity of Wind Power Forecast Result at Home and Abroad: (1) Distribution of wind power stations Large scale of collective distribution in China.More expansive and equal in Europe

(2)NWP level The weather stations are dense distribution in

the Europe . The geographic location Europe lies are

beneficial to NWP.Many commercialized weather service

companies in Europe.

Development of forecast technology

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Cooperation with ADB

Demand of China Demand of China Mission of ADBMission of ADB

Smart Grid &

Reduce CO2

emission

Smart Grid &

Reduce CO2

emission

Eliminating Poverty

&Environment Sustaining

Eliminating Poverty

&Environment Sustaining

TA7721-PRC: Developing Smart Grid for Efficient

Utilization of Renewable Energy

TA7721-PRC: Developing Smart Grid for Efficient

Utilization of Renewable Energy

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Integration Scheduling System of Smart Grid (D5000)

InformationOf Wind

Farm

Wind Power Forecast

Scheduling GCA Wind powerControl

AcceptableCapacity

Smart Grid Demonstration Project

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Wind Power Forecast Result

Date: 2011.11-2011.12

RMSE=8.1% MAE=5.82%

Corr=86.86% Rate=96.88%

WPF Result of NCGC

Error

Forecast the Weather Trend

Date: 2011.04-2011.05

RMSE=12.72% MAE=9.77%

Corr=74.71% Rate=87.44%

Significant improve !

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Case : Wind Forecasting

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Case : Wind Power Forecasting

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Thank you!

Cao XiaoAddress:No.8 Nanrui Road , Nanjing PRC 210003

TEL:+86 25 83092802 FAX:+86 25 83092877

Mobile:+86 13813889826

Email:caoxiao@sgepri.sgcc.com.cn