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Day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting

A technology of meteorological factors and forecasting methods, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as power system operation and scheduling impact, and achieve the effect of improving forecasting accuracy

Inactive Publication Date: 2020-12-11
TIANJIN UNIV
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Problems solved by technology

However, due to the characteristics of randomness, volatility, and intermittent nature of photovoltaic power generation, the connection of large-scale photovoltaic power generation to the grid will have a greater impact on the operation and scheduling of the power system, which has become the biggest problem in the utilization of solar photovoltaic power generation.

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  • Day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting
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  • Day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting

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[0049] In order to further understand the invention content, characteristics and effects of the present invention, the following embodiments are enumerated hereby, and detailed descriptions are as follows in conjunction with the accompanying drawings:

[0050] See figure 1 , a day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting, including the following steps:

[0051] Step 1, divide the historical database of photovoltaic power plants into multiple historical data sets according to the season type and weather pattern;

[0052] Step 2: Determine and obtain the eigenvectors of daily meteorological factors on the forecast day, and use the clustering method to select historical data of photovoltaic power plants that are similar to the eigenvectors of daily meteorological factors on the forecast day from the historical data set that conforms to the seasonal type and weather pattern of the forecast day , and make a training ...

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Abstract

The invention discloses a day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting. The method comprises the steps of determining and obtaining a day meteorological factor feature vector of a prediction day, and employing a clustering method to screen out photovoltaic power station historical data similar to the prediction day from a historicaldata set according with the season type and weather mode of the prediction day, and making a similar day training sample set; establishing an optical power prediction model based on an Elman neural network; determining input and output factors of the model; calculating a Pearson correlation coefficient of each meteorological factor sequence and the solar photovoltaic power sequence in each similarday training sample, weighting an input factor of the training sample based on the Pearson correlation coefficient, and training an optical power prediction model; and obtaining meteorological prediction data of the prediction day, and predicting the predicted solar photovoltaic power by using the trained optical power prediction model. The method can predict the day-ahead power of the photovoltaic power station, and is suitable for the built photovoltaic power station.

Description

technical field [0001] The invention relates to an optical power prediction method in the technical field of photovoltaic power generation, in particular to a day-ahead optical power prediction method based on similar day clustering and meteorological factor weighting. Background technique [0002] Currently, solar energy, as the most promising clean and renewable energy, has been widely developed and applied in view of alleviating the fossil energy crisis and increasing energy and emission reduction demands. However, due to the characteristics of randomness, volatility, and intermittent nature of photovoltaic power generation, the connection of large-scale photovoltaic power generation to the grid will have a great impact on the operation and scheduling of the power system, which has become the biggest problem in the utilization of solar photovoltaic power. In recent years, in order to improve the stability of photovoltaic power generation and the acceptance rate of the gri...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06Q10/06
CPCG06Q10/04G06Q50/06G06Q10/067
Inventor 马超杨阳庞秀岚
Owner TIANJIN UNIV
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