Short-term power forecasting method of photovoltaic power station based on a Kmeans-GRA-Elman model

A photovoltaic power station and power forecasting technology, applied in forecasting, neural learning methods, biological neural network models, etc., can solve problems such as short-term power forecasting of photovoltaic power stations that have not yet been seen, and achieve the effect of improving precision and accuracy

Active Publication Date: 2018-12-14
FUZHOU UNIVERSITY
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Problems solved by technology

[0006] At present, there is no research on applying the hybrid improved Kmeans-GRA-Elman algorithm

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  • Short-term power forecasting method of photovoltaic power station based on a Kmeans-GRA-Elman model
  • Short-term power forecasting method of photovoltaic power station based on a Kmeans-GRA-Elman model
  • Short-term power forecasting method of photovoltaic power station based on a Kmeans-GRA-Elman model

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[0027] The present invention will be further described below in conjunction with the drawings and embodiments.

[0028] This embodiment provides a short-term power prediction method for photovoltaic power plants based on the hybrid improved Kmeans-GRA-Elman model. The flow chart is as follows figure 1 Shown. It includes the following steps:

[0029] Step S1: Collect the historical daily generation power of the photovoltaic power station and the meteorological parameters of the corresponding time period on the weather station every day. The meteorological parameters include meteorological factors such as light, ambient temperature, humidity, wind speed, etc., and combine to obtain a daily meteorological-power parameter sample combination;

[0030] Step S2: Preprocess the daily weather-power parameter sample combination, remove abnormal data and perform normalization processing;

[0031] Step S3: Use the six statistical indicators in the normalized statistical analysis combined with the...

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Abstract

The invention relates to a short-term power forecasting method of a photovoltaic power station based on a Kmeans-GRA-Elman model. The method includes the steps of: collecting the power generated everyday in the history of photovoltaic power station and the meteorological parameters of the corresponding time period on the meteorological station every day; preprocessing the data; using the six statistical indexes and the improved Kmeans algorithm to cluster the samples from the first day of the historical day to the day before the forecast day, and determining the number of categories accordingto the contour coefficient; calculating a center point of each clustering meteorological eigenvalue, and judging a category to which the forecast day belongs; determining the similarity date and thebest similarity date of the date to be forecasted; determining the parameters of an Elman neural network; obtaining the training model; inputting the parameters of the best similar day and the meteorological parameters of the day to be forecasted into the training model to forecast the power generation on the day to be forecasted. The invention can improve the accuracy and accuracy of short-term power prediction of the photovoltaic power station under different weather conditions in different seasons.

Description

technical field [0001] The invention belongs to short-term power prediction technology of photovoltaic power plants, in particular to a short-term power prediction method of photovoltaic power plants based on the Kmeans-GRA-Elman model. Background technique [0002] In recent years, with the development of social economy, the problems of energy shortage and environmental pollution have been highly valued by all walks of life. The development and utilization of renewable energy has become an important way to solve energy and environmental problems. In addition, with the growth of power demand and the continuous expansion of the power grid, the disadvantages of traditional large-scale and highly concentrated power generation, such as high investment costs and difficult operation, have become increasingly prominent. In this context, photovoltaic power generation has developed rapidly under the attention of countries all over the world. For the technical level of photovoltaic p...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/08
CPCG06N3/08G06Q10/04G06Q50/06G06F18/23213
Inventor 林培杰程树英赖云锋彭周宁陈志聪吴丽君郑茜颖章杰
Owner FUZHOU UNIVERSITY
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