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Short-term wind speed hybrid prediction method based on recursive quantitative analysis

A technology of quantitative analysis and hybrid prediction, applied in prediction, neural learning method, biological neural network model, etc., can solve the problem that the accuracy of wind speed prediction needs to be further improved.

Inactive Publication Date: 2018-10-02
NORTHEAST DIANLI UNIVERSITY
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Problems solved by technology

However, the existing wind speed prediction technology still has a lot of room for improvement, and the accuracy of wind speed prediction needs to be further improved

Method used

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  • Short-term wind speed hybrid prediction method based on recursive quantitative analysis
  • Short-term wind speed hybrid prediction method based on recursive quantitative analysis
  • Short-term wind speed hybrid prediction method based on recursive quantitative analysis

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Embodiment Construction

[0069] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0070] A short-term wind speed hybrid prediction method based on recursive quantitative analysis of the present invention includes the following contents:

[0071] A short-term wind speed hybrid forecasting method based on recursive quantitative analysis is characterized in that it includes the following contents:

[0072] 1) Quantitative evaluation of predictability of wind speed series

[0073] The actual wind speed has certain volatility and uncertainty. In order to reveal the fluctuation law and correlation characteristics contained in the wind speed sequence, the chaotic characteristics of the wind speed sequence are analyzed based on the maximum Lyapunov exponent to determine whether the wind speed sequence information meets the requirements of phase space reconstruction. On this basis, the phase space reconstruction of the wind speed series is car...

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Abstract

The invention provides a short-term wind speed hybrid prediction method based on recursive quantitative analysis, which starts from two aspects such as prediction model input sets and prediction modelkey parameters in allusion to the fluctuation and uncertainty of a wind speed series. The embedding dimension and delay time when the predictability of the wind speed series is the highest are optimized by using a combined index formed by the recursion rate and the certainty, the optimal input set is obtained through phase-space reconstruction, prediction is performed on data to be predicted by applying a COA-SVR prediction model trained by the optimal input set, and the predicted result is compared with prediction results of other algorithms. The result shows that the provided hybrid prediction method can better improve the wind speed prediction accuracy and has certain theoretical values and engineering significance.

Description

technical field [0001] The invention is a short-term wind speed mixed prediction method based on recursive quantitative analysis, which is applied to accurately predict short-term wind speed to reduce the impact of wind power output on the system and ensure the stable operation of large-scale wind power grid-connected systems. Background technique [0002] With the massive consumption of global fossil energy, the energy crisis and environmental pollution have become important factors restricting social and economic development. The large-scale development of wind power can relieve the dual pressure of energy shortage and environmental pollution to a large extent, but the wind speed has significant fluctuations. With the continuous increase of wind power grid-connected scale, the impact of wind power output on the system is becoming more and more serious, making it more difficult to formulate dispatching plans, which is not conducive to the stable operation of the system. Acc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00G06N3/08
CPCG06N3/006G06N3/084G06Q10/04G06Q50/06
Inventor 潘超谭启德王楠蔡国伟
Owner NORTHEAST DIANLI UNIVERSITY