The first is to predict wind speed.
The first is to first predict the wind speed, and then obtain the corresponding wind power through the conversion of the power characteristic curve. The second is to collect various historical data needed for power forecasting, such as wind speed, wind direction, temperature, etc., and establish a mathematical model to reflect the relationship between these data and the wind energy.
Wind power refers to the actual energy of wind power acting on the wind blades. The power output from the generator is less than this because there is an efficiency problem in the conversion process. Wind energy density is the wind energy of the air flow passing vertically through a unit cross-sectional area in unit time.
The forecast time scale of theMedium-term wind energy is several weeks or months, and fluctuations in wind energy during this time scale are related to the maintenance plan of the wind farm or power grid. .
1. Wind power forecast classification
There are many classification methods for wind power forecasting. Generally speaking, there are the following classification methods:
1. According to the predicted physical quantities, they can be divided into: wind speed predicted output power and direct predicted output power.
2. According to mathematical models, it can be divided into: continuous prediction, time series model prediction, Kalman filter method and neural network intelligent method prediction.
3. According to the input data, they can be divided into: do not use the numerical weather prediction method and use the numerical weather prediction methodof numerical weather prediction.
4. According to the temporal dimension, it can be divided into: very short-term forecasting, short-term forecasting and medium and long-term forecasting. Among them, the classification by temporal magnitude is generally recognized by all and is the most used.
Among them, the very short term forecast, the short term forecast and the medium and long term forecast:
1. The very short-term time scale of wind energy. the power forecast is 0 to 4 hours, a rolling forecast is 15 minutes, and the time resolution is 15 minutes. Mainly used for real-time dispatching to solve power grid frequency regulation problems.
2. The short-term wind power forecast time scale is 0-72 hours, and the temporal resolution is 15 minutes. It is mainly used to reasonably organize the production planenergy of conventional units and solve the problem of. peak regulation of the electricity network.
3. The medium- and long-term wind power forecasting time scale is weeks or months. Fluctuations in wind energy over this time scale are linked to the maintenance plan of the wind farm or power grid.
2. Wind power forecasting methods
Wind power forecasting methods can be divided into: one method is to use physical methods to calculate the power output of the wind farm based on conditions digital weather. forecast data; the other is to calculate the power output of the wind farm using physical methods; a method is a statistical forecasting method based on the relationship between numerical weather prediction, wind farm energy production and online measured data.
TheComprehensive method refers to a method that uses both physical methods and statistical methods.