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Photovoltaic power supply power prediction method based on positive and negative error variable weights

A technology of photovoltaic power generation and prediction method, which is applied in prediction, data processing application, calculation and other directions, and can solve the problems of poor prediction effect and inability to meet the requirements of prediction accuracy.

Active Publication Date: 2015-12-30
STATE GRID GASU ELECTRIC POWER RES INST +3
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  • Abstract
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Problems solved by technology

[0004] The purpose of the present invention is to provide a photovoltaic power prediction method based on positive and negative error variable weights, which solves the problem that the prediction accuracy of the prediction method in the prior art cannot meet the requirements and the prediction effect is poor

Method used

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  • Photovoltaic power supply power prediction method based on positive and negative error variable weights
  • Photovoltaic power supply power prediction method based on positive and negative error variable weights
  • Photovoltaic power supply power prediction method based on positive and negative error variable weights

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Embodiment

[0090] Taking the actual data of a photovoltaic field in Gansu on October 15th as an example, the test data is predicted by using the selected optimal parameters. The gray prediction power changes with time, and the results can be seen as figure 2 shown. The overall prediction trend is very close to the actual power generation, but the accuracy needs to be improved when the power generation is zero.

[0091] Also use the historical data of a photovoltaic power station in Northwest China, and perform 2500 iterations by selecting different numbers of neurons. Depend on image 3 It can be seen that the error when the number of neurons is different, it can be seen that the prediction error of 16 neurons is the smallest, and the interference in the recursive network only exists in the expected output, the prediction accuracy of the network is higher than the interference variance, and the error is negligible. And with the increase of the network training rate, it has an inhibit...

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Abstract

The invention discloses a photovoltaic power supply power prediction method based on positive and negative error variable weights. The method specifically includes the following implementation steps that firstly, n optical power prediction models are set, N prediction time points exist, and y(t) is a true value of photovoltaic power generation power at the tth moment; then, a prediction result is subtracted with the true value, and the weight of the tth moment of the ith model is calculated; finally, a final prediction result is obtained through n prediction values. The method solves the problems that prediction precision of a prediction method in the prior art can not meet requirements, and the prediction effect is poor.

Description

technical field [0001] The invention belongs to the technical field of new energy photovoltaic power generation power forecasting, and in particular relates to a photovoltaic power generation power forecasting method based on positive and negative error variable weights. Background technique [0002] In recent years, with the large-scale construction of photovoltaic power generation systems, in order to avoid the impact of intermittent and uncontrollable factors such as the inherent intermittent and uncontrollable output power of grid-connected photovoltaic power generation systems on the grid, the quality of power when photovoltaic power Performance requirements, stability of grid-connected power plants and other issues need to be resolved urgently. The access of large-scale intermittent energy sources will have a huge impact on the security and stable operation of the power grid, and power prediction technology is imminent. As the researched systems become more and more p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
Inventor 赵耀赵炜马喜平韩旭杉胡殿刚王维洲秦睿刘秀良魏博郑伟范迪龙董开松李臻沈渭程姜梅王斌杨俊郑翔宇甄文喜张光儒闵占奎李志敏陈明忠雷俊汪红燕朱广明王文华李炜李军袁芳杨柯张娟刘璐陈志彤王娅君武广萍杨洁王政宏李小娟张鹏高世刚李涛孙明张卓毅何巍孟欢
Owner STATE GRID GASU ELECTRIC POWER RES INST
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