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A Wind Power Prediction Method Considering Wind Power Uncertainty Risk

A wind power prediction and uncertainty technology, applied in the direction of prediction, data processing application, system integration technology, etc., can solve the problems affecting system economy, improvement, forecast uncertainty tail distribution modeling, etc., to improve the power generation economy sexual effect

Active Publication Date: 2021-08-06
STATE GRID SHANDONG ELECTRIC POWER +1
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Problems solved by technology

However, in the uncertainty modeling process, the fact that the wind power forecast uncertainty tail distribution (high error interval) has a much greater impact on the economics of day-ahead power generation planning than the head distribution (error low value interval) is not considered. , there is no targeted modeling of the tail distribution of forecast uncertainty, which affects the further improvement of system economy

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  • A Wind Power Prediction Method Considering Wind Power Uncertainty Risk
  • A Wind Power Prediction Method Considering Wind Power Uncertainty Risk
  • A Wind Power Prediction Method Considering Wind Power Uncertainty Risk

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Embodiment Construction

[0037] The present invention provides a wind power prediction method considering the risk of wind power uncertainty, such as figure 1 shown, including the following steps:

[0038] Step 1: Extract data containing different feature information from historical observation data to form a training set S;

[0039] Specifically: form a training set based on historical data, including: N sample pairs, namely q N is the empirical distribution probability obtained from the statistics of the measured values, is the Nth wind power prediction error sample, including M measured wind power prediction error values. is the weight vector for N sample pairs, where the weight of the j sample sets for the i-th cycle and repeated learning is denoted as i∈[1,T], j∈[1,N], by assigning higher weights to larger error samples, repeated learning of larger error samples can be achieved to gain richer experience and achieve the effect of improving modeling accuracy , The expression is:

[0040...

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Abstract

The invention provides a wind power prediction method considering the uncertainty risk of wind power. On the basis of the mixed distribution model, an adaptive mixed uncertainty probability modeling method with the risk value VaR as the training target is proposed. The method first adopts the historical The wind power data generates a training set, and then uses the value at risk VaR as the training target to update the training samples. Finally, through multiple rounds of learning, a high-precision mixed probability model of wind power forecast error is generated, which can effectively improve the economics of power generation.

Description

technical field [0001] The invention relates to the field of power generation, in particular to a wind power prediction method considering the risk of wind power uncertainty. Background technique [0002] After long-term engineering practice and national "blowout" development, wind power generation has been proven to be a reliable clean energy that can be developed and utilized on a large scale. However, with the further increase of wind power generation power penetration rate, the volatility and randomness of wind energy itself bring challenges to the accurate formulation of power generation plans. Under the background that the current forecast error of wind power is generally as high as 10%-20%, on the one hand, the high penetration of wind power sources forces the dispatching organization to purchase a large amount of power generation backup in the day-ahead power generation planning stage to maintain the power balance of the grid operation during the day, and on the othe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02E40/70Y04S10/50
Inventor 杨佳俊武奕彤王志峰魏延彬黄兴刘洋马骁旭张洪帅尚新宇张培杰董金龙段美琪任新伟王睿
Owner STATE GRID SHANDONG ELECTRIC POWER
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