Method and system for predicting ultra-short-term irradiance of photovoltaic power station

A photovoltaic power station and prediction method technology, applied in the direction of prediction, instrumentation, data processing applications, etc., can solve the problem of inaccurate ultra-short-term irradiance prediction of photovoltaic power stations, and achieve the goal of improving prediction accuracy, data accuracy, and measurement accuracy Effect

Active Publication Date: 2017-10-17
INNER MONGOLIA POWER GRP +1
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is: when the existing irradiance is predicted for the next few hours based on the historical value of the slope irradiance measurement, it fails to reflect the weather change factors for the next few hours, which leads to the ultra-short-term irradiance prediction of the photovoltaic power station. Inaccurate

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  • Method and system for predicting ultra-short-term irradiance of photovoltaic power station
  • Method and system for predicting ultra-short-term irradiance of photovoltaic power station
  • Method and system for predicting ultra-short-term irradiance of photovoltaic power station

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Embodiment 1

[0044] Such as figure 1 with 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 sta...

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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Abstract

The invention relates to a method and a system for predicting the ultra-short-term irradiance of a photovoltaic power station. The method comprises the steps of obtaining a predicted irradiance according to a trained support vector regression model; calculating similarity values and sorting historical numerical weather forecast data according to similarity values; calculating the variances of historical numerical weather forecast irradiances and an actual irradiance, and conducting the weighted accumulation of the variances; calculating the weight of the predicted irradiance of the numerical weather forecast and the weight of the predicted irradiance of the support vector regression model; calculating to obtain the ultra-short-term prediction irradiance of the photovoltaic power station at a predicted moment tp. The invention further relates to a prediction system. The prediction system comprises a training support vector regression model module, a similarity calculation module, a variance calculation module, a weight calculation module and an ultra-short-term irradiance prediction module. By means of the prediction method and the prediction system, the prediction precision can be obviously improved. Meanwhile, the calculation efficiency and the performance meet the requirements of prediction, and the real-time scheduling requirement of the photovoltaic power generation is completely met.

Description

technical field [0001] The invention belongs to the field of photovoltaic prediction, and in particular relates to a method and system for ultra-short-term irradiance prediction of a photovoltaic power station. Background technique [0002] As the most practical technology in the utilization of solar energy, solar photovoltaic power generation has become a hotspot of research and application all over the world. However, photovoltaic power generation is inherently highly dependent on weather conditions, random and volatile, and difficult to predict, which limits the large-scale application of photovoltaic power generation. [0003] The output power of photovoltaic power generation depends to a large extent on the amount of solar radiation received by photovoltaic panels, which is easily affected by weather factors. The irradiance on the slope of the photovoltaic panel measured by the environmental monitoring instrument installed in the photovoltaic power station cannot take ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 朱长胜蒿峰文志刚郭琦郭抒翔云峰海威贺旭伟牛新
Owner INNER MONGOLIA POWER GRP
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