Wind power ramp event prediction method by adopting SVM to select forecasting model

Abstract

The invention discloses a wind power ramp event prediction method by utilizing an SVM to select a forecasting model. The prediction method comprises the following steps: dividing a first sample set into local data segments according to window length; establishing short-period wind power forecasting models of the local data segments by utilizing the SVM, and obtaining a short-period wind power forecasting model library; carrying out cluster fusion on the models in the short-period wind power forecasting model library by utilizing a Ward clustering method, adopting an SVM classification model to express a forecasting model selection mechanism, and training the forecasting model selection mechanism by utilizing a second sample set; and obtaining short-period wind power forecast data according to the forecasting model selection mechanism, wherein the time-continuous short-period wind power forecast data forms long-period wind power forecast data, and carrying out ramp event prediction according to the long-period wind power forecast data. The wind power ramp event prediction method can ensure higher-precision wind power long-period forecast, and furthermore, ensures accuracy of the ramp event prediction.

Description

technical field [0001] The invention belongs to the technical field of wind power forecasting, and in particular relates to a forecasting method for wind power ramping events using SVM to select a forecasting model. Background technique [0002] In recent years, under the development trend of large-scale and highly concentrated wind farms in my country, the adverse effects of randomness and volatility of wind resources on the power system have become more and more obvious, among which the most harmful is the wind power ramp event , such as a large-scale power downhill event occurred in Texas, USA in 2008. Ramp events refer to a type of large-scale wind power change events that occur in a short period of time, and pose a potential threat to the security, stability and economic operation of the power system. In the future, when a large amount of wind power is injected into the power grid, in order to maintain the safety and stability of the power grid, it is necessary to reduc...

AI Technical Summary

Problems solved by technology

The prediction results obtained by NWP are very useful for grasping the long-term development trend of wind power, but they are insufficient for grasping the local characteristics of wind power.

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