Short-term wind speed and wind power prediction method
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A wind speed prediction and wind speed technology, applied in fluid velocity measurement, velocity/acceleration/impact measurement, power measurement, etc., can solve problems such as programming, no visual interface, complex physical model, etc.
Inactive Publication Date: 2012-10-24
LANZHOU JIAOTONG UNIV
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There are many parameter requirements and the physical model is complex
[0008] Statistical methods (mainly neural network) forecasting models are complex to build, without a visual interface, and programming is required
For prediction models with more than two input variables, the network convergence speed is slow, and it is not suitable for ultra-short-term wind power prediction
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Embodiment 1
[0047] The wind speed prediction method of optimizing the GM(1,1) model is as follows:
[0048] Step 1: Use the actual wind speed measured by the wind tower or anemometer as the actual input value of the prediction model.
[0049] Step 2: Optimizing the traditional gray forecasting model by using the numerical approximation principle.
[0050] 1. Wind speed prediction model optimization scheme
[0051] The improvement of wind speed prediction model is mainly to provide high-precision wind speed prediction input value for wind power prediction. Only when the accuracy of wind speed prediction value is improved, wind power prediction can be accurate. For this reason, the present invention first uses the principle of numerical approximation to improve the existing gray GM (1, 1) prediction model. Specific steps are as follows:
[0052] 1.1 Basic principles of traditional gray GM (1, 1) model for predicting wind speed
[0053] Using the traditional GM(1,1) model before optimiza...
Embodiment 2
[0104] Example 2 Time Series Dynamic Neural Network Forecasting Wind Power
[0105] Due to the short-term correlation of wind speed, it is not necessary to establish a specific mathematical model of the time series when using the dynamic neural network to predict the time series. Compared with other neural network prediction models, the dynamic neural network has better prediction accuracy for the one-dimensional time series prediction, which provides a realistic basis for the selection of time series dynamic neural network for wind power prediction.
[0106] 2.1 Wind Power Prediction Method
[0107] Taking the above predicted wind speed as input and fan power as output, a single-input and single-output network is constructed, and the transfer function adopts the hyperbolic tangent function:
[0108]
[0109]
[0110] In formula (14), x is the neuron input, to transfer the function value.
[0111] The error correction adopts the "instantaneous backpropagation algorit...
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Abstract
The invention discloses a short-term wind speed prediction method. The short-term wind speed prediction method includes a first step, using wind speeds actually measured by anemometer tower or an anemometer as actual input values of a prediction model; a second step, optimizing the traditional grey prediction model by a numerical approximation principle; a third step, inputting the wind speeds measured by the anemometer tower or the anemometer into an optimized prediction model to predict the wind speed; and a fourth step, inputting a wind speed value obtained from the prediction model into a wind speed prediction model to carry out rolling prediction. Future prediction time can be prolonged. The short-term wind speed and wind power prediction method has the advantages that required prediction parameters include only 144 actual wind speed values which are respectively measured at 10-minute intervals within 24 hours, and parameters including wind direction, atmospheric temperature, atmospheric pressure, temperature, humidity and the like are not required. Besides, the actual wind speed values can be obtained by the anemometer or the anemometer tower instead of being provided by a numerical weather forecast department, and the short-term wind speed and wind power prediction method is economical and is low in cost.
Description
technical field [0001] The invention relates to a short-term wind speed and wind power prediction method. Background technique [0002] With the rapid increase of my country's wind power grid-connected capacity, wind speed fluctuations make the power of wind turbines unstable, which brings difficulties to power dispatch and maintenance of wind turbines. my country's terrain and landforms are relatively complex, and the wind speed is more random and fluctuating than that of the European continent. Some foreign prediction methods are not very effective in some wind farms in my country. At present, there are mainly three types of wind speed-wind power prediction methods at home and abroad: numerical weather prediction method, statistical method and physical method, but the prediction effect is still not satisfactory. Although there are many methods for medium and long-term wind speed prediction, they are not necessarily suitable for short-term and ultra-short-term wind speed p...
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