A method and system for ultra-short-term irradiance prediction of photovoltaic power plants
A technology for photovoltaic power plants and forecasting methods, applied in forecasting, data processing applications, instruments, etc., can solve the problems of inaccurate ultra-short-term irradiance forecasting of photovoltaic power plants, and achieve the effects of improving forecasting accuracy, compact data and reducing errors.
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Embodiment 1
[0044] Such as figure 1 and figure 2 As shown, a method for predicting ultra-short-term irradiance of a photovoltaic power plant in an embodiment of the present invention includes the following steps:
[0045] S1, using the read current time t 0 and the actual irradiance data of the photovoltaic power station in a certain period of time before training the support vector regression model to obtain the trained support vector regression model. At the same time, the trained model is used to predict the time t p The irradiance is predicted to obtain the first predicted irradiance;
[0046] In this embodiment 1, the current time t is read first 0 And the actual irradiance data of the photovoltaic power station for a certain period of time before, and then train the support vector regression model with the read data to obtain the trained support vector regression model, for example: read the current time 8:00, As well as the actual irradiance data of the photovoltaic power stat...
Embodiment 2
[0091] Such as image 3 As shown, this embodiment 2 also relates to a photovoltaic power plant ultra-short-term irradiance prediction system, which includes: training support vector regression model module, similarity calculation module, variance calculation module, weight calculation module, ultra-short-term irradiance Illumination prediction module;
[0092] The training support vector regression model module is used to utilize the read current moment t 0 and the actual irradiance data of the photovoltaic power station in a certain period of time before training the support vector regression model to obtain the trained support vector regression model. At the same time, the trained model is used to predict the time t p The irradiance is predicted to obtain the first predicted irradiance;
[0093] The similarity calculation module is used to read the predicted time t p The first data of the numerical weather forecast, the current time t 0 and the second data of the numeric...
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