A new photovoltaic power prediction method based on AFSA-Elman

A power prediction, photovoltaic technology, applied in prediction, computational model, biological model, etc., can solve the problems of power system paralysis, loss, power system security and stability impact, etc., to improve prediction accuracy and overcome randomness. Effect

Inactive Publication Date: 2019-01-08
JIANGSU UNIV
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Problems solved by technology

When the installed capacity of the grid-connected photovoltaic power station is large, the security and stability of the power system will be affected
Studies have shown that when the installed capacity of photovoltaic power plants accounts for more than 15% of the power system, its fluctuations may cause power system paralysis and bring immeasurable losses

Method used

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  • A new photovoltaic power prediction method based on AFSA-Elman
  • A new photovoltaic power prediction method based on AFSA-Elman
  • A new photovoltaic power prediction method based on AFSA-Elman

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Experimental program
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Effect test

Embodiment

[0093] First collect the original data and establish a data sample set: the original data set used in this experiment came from a photovoltaic power station in Zhejiang from March 1 to August 31, 2015. SCADA data with a resolution of 5 seconds was collected, which was divided into electrical data and meteorological data. There are two types of data. The electrical data is the current and voltage values ​​output by the inverter. The meteorological data comes from the weather station installed in the photovoltaic power station, including light intensity Q, power P, temperature T, humidity H, wind speed S, etc. Then do further preprocessing on the data, remove abnormal data, and then normalize the processed data by formula (1), and limit the model input value between [0,1]:

[0094]The Mallet fast algorithm of orthogonal transformation is used for the processed power sequence, and the power signal is decomposed into high-frequency detail signal d i (i=1,2,3,…n) and low frequency...

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Abstract

The invention discloses a new photovoltaic power prediction method based on AFSA-Elman. Firstly, the method decomposes the collected original power into low frequency trend component and high frequency detail component by wavelet decomposition, then forecasts the low frequency trend component and high frequency detail component with the collected weather data as the input of the model respectively, and finally reconstructs the corresponding forecasted value to obtain the final power forecasted value. An artificial fish swarm algorithm is used to optimize the weights and thresholds of Elman neural network, and the optimized Elman is applied to the short-term prediction of photovoltaic output power. The method can predict the output power of the next time according to the historical weatherand the output power of the photovoltaic station and the weather condition in a short period of time, and the prediction model can utilize the autocorrelation existing in the historical data without using a plurality of complex and tedious physical formulas for modeling.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic power generation, and in particular relates to a novel photovoltaic power prediction method based on AFSA-Elman. Background technique [0002] Solar energy is an intermittent energy source, which makes the power generation of photovoltaic power plants fluctuate and intermittent. When the installed capacity of grid-connected photovoltaic power plants is large, the security and stability of the power system will be affected. Studies have shown that when the installed capacity of photovoltaic power plants accounts for more than 15% of the power system, its fluctuations may cause power system paralysis and bring immeasurable losses. Therefore, it is necessary to accurately predict the power generation of photovoltaic power plants to cooperate with the power sector for reasonable planning and scheduling. [0003] Accurately predicting power generation and cooperating with power dispatching depar...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00G06N3/04
CPCG06N3/006G06N3/04G06Q10/04G06Q50/06
Inventor 纪棋彬谭伦农韩磊蒋俊峰
Owner JIANGSU UNIV
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