Method and system for predicting hybrid wind power generation

Abstract

The invention discloses a method and system for predicting hybrid wind power generation. The method comprises the following steps: acquiring wind directions, wind speeds and historical data of corresponding wind power output power of a wind farm, sampling from the historical data to obtain sample data; conducting judgment and analysis on statistical features of the sample data, acquiring wind directions that are featured by an integrated wind frequency and have a wind power output power difference which reaches a difference threshold value, and based on the acquired wind directions and corresponding relations between the wind directions, and the wind speeds and the wind power output power, adopting the fuzzy hierarchy clustering method in dividing the sample data into three types; adopting the neural network algorithm in training each type of samples, correspondingly forming three types of specific wind generation prediction models, then conducting combination and processing, establishing a hybrid wind generation prediction model which is intended for predicting wind power generation capacity. Therefore, the method, through the implementation, can conduct model prediction on different wind directions and wind speeds in a specific manner and can increase precision of prediction the wind power generation power.

Description

Technical field [0001] The present invention relates to the technical field of wind power prediction, in particular to a prediction method and system for hybrid wind power generation. Background technique [0002] When wind power plants are generating wind power, wind power output is not only affected by wind speed, but wind direction is also a factor that cannot be ignored. However, due to atmospheric pressure, wind speed and direction will change at any time, so the output power of wind turbines is also fluctuating And randomness, this kind of power output volatility is not conducive to the stability and safety of the overall operation of the regional power grid. Therefore, it is necessary to make a reasonable forecast of the output power of wind power to facilitate effective dispatching by the power operation department. [0003] At present, in terms of short-term wind power generation forecasting, two methods are mainly used: physical model forecasting and statistical model fo...

AI Technical Summary

Problems solved by technology

[0007] However, for statistical model prediction, the data used is single, and the short-term or ultra-short-term wind power prediction results can meet the accuracy requirements

However, for longer-term predictions, the accuracy of the prediction results is often not enough, and it requires long-term measurement data, a large amount of data processing work and additional training.

In addition, it does not handle mutation information well, rare weather conditions rarely appear during the training phase, and it is difficult to predict accurately

Images