Ultra-short-term wind power prediction method according to off-line track characteristic optimization and real-time extrapolation model matching

An ultra-short-term forecasting and offline optimization technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as the inability to fully reflect the statistical characteristics of wind power sequences or dynamic changes of wind speed sequences, and improve the accuracy of ultra-short-term forecasting and forecasting. , the effect of improving forecasting efficiency

Active Publication Date: 2013-12-25
STATE GRID ELECTRIC POWER RES INST +1
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcomings of traditional wind power forecasting methods that cannot fully reflect the dynamic changes of wind power sequences or wind speed sequences and the statistical characteristics of different time periods, a

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  • Ultra-short-term wind power prediction method according to off-line track characteristic optimization and real-time extrapolation model matching
  • Ultra-short-term wind power prediction method according to off-line track characteristic optimization and real-time extrapolation model matching
  • Ultra-short-term wind power prediction method according to off-line track characteristic optimization and real-time extrapolation model matching

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Embodiment Construction

[0021] The present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0022] figure 1 Step 1 describes the construction of wind power or wind speed trajectory: the trajectory is composed of time-series historical data of wind power or wind speed, and the time interval between two adjacent points on the trajectory is the sampling period of the historical data.

[0023] figure 1 In step 2, combined with the characteristics of the wind farm and the attributes of the wind power or wind speed trajectory, the feature quantity used to divide the trajectory shape is selected, denoted as C s1 , C s2 ,...,C sp , C v1 , C v2 ,...,C vq , where the subscript s indicates that the feature quantity is a statistical feature quantity including statistical indicators such as mean value, maximum value, minimum value, and variance, and the subscript v indicates that the feature quantity reflects sampling points including absolute v...

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Abstract

The invention discloses an ultra-short-term wind power prediction method according to offline track characteristic optimization and real-time extrapolation model matching, and belongs to the fields of development and utilization of renewable energy sources. The method comprises the following two steps: (1) establishing a model in an off-line mode and optimizing parameters, namely dividing a track formed by historical data of a wind power time sequence or a wind speed time sequence into different forms according to the given characteristic quantity, respectively establishing a prediction model for each form, and optimizing the parameters; (2) performing real-time prediction, namely calling a corresponding prediction model according to the forms of the track of latest measured data. According to the method, the time-varying characteristics of the wind power sequence are fully measured, and the statistical characteristics and change rules of a wind power sequence at different time intervals are reflected. The defect that dynamic change of the wind power sequence and statistical characteristics of the wind power sequence at the different time intervals can not be comprehensively reflected in a traditional wind power prediction method is overcome. The coordinative optimization among prediction models (or algorithms) is realized. Therefore, the prediction accuracy is improved, and the prediction efficiency is also improved.

Description

technical field [0001] The invention belongs to the field of renewable energy development and utilization. More precisely, the invention relates to an ultra-short-term prediction method of wind power or wind speed. Background technique [0002] Vigorously developing clean energy technologies such as wind power plays a very positive role in improving the energy structure and reducing greenhouse gas emissions. However, compared with conventional power sources, the output power of wind farms has the characteristics of volatility, intermittent and randomness. The centralized grid connection of a large number of wind farms will affect the safety, stability, and economic operation of the grid, and become a limit for grid acceptance. One of the major hurdles for wind power. [0003] Predicting the output power of wind farms is one of the most effective and economical means to improve the peak-shaving capability of the power grid, enhance the ability of the power grid to accept win...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCY02E40/70Y04S10/50
Inventor 薛禹胜郁琛
Owner STATE GRID ELECTRIC POWER RES INST
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