A short-term prediction model to forecast power of photovoltaic based on MFA-Elman

Due to the low accuracy and reliability as well as slow prediction speed of photovoltaic (PV) power short-term prediction, a short-term PV power prediction method based on MFA-Elman neural network is proposed. K-means mean algorithm is employed firstly in this method to cluster the weather type, and...

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Main Authors: XinYu Ma, XiaoHong Zhang
Format: Article
Language:English
Published: Elsevier 2022-07-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S235248472200213X
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author XinYu Ma
XiaoHong Zhang
author_facet XinYu Ma
XiaoHong Zhang
author_sort XinYu Ma
collection DOAJ
description Due to the low accuracy and reliability as well as slow prediction speed of photovoltaic (PV) power short-term prediction, a short-term PV power prediction method based on MFA-Elman neural network is proposed. K-means mean algorithm is employed firstly in this method to cluster the weather type, and then EEDM is used to decompose the PV output power on the various data obtained by clustering. Finally, each decomposition subsequence is inputted into the MFA-optimized Elman neural network to predicting the PV output power, which solves the randomness of initial weight and threshold and slow training speed of Elman neural network. The simulation results show that the MFA-Elman model has smaller prediction error, higher prediction accuracy and reliability, faster prediction speed, which can reach the requirements of short-term prediction of PV power.
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spelling doaj.art-8a1b47bb629a48bc808770a92dd35af22022-12-22T02:52:29ZengElsevierEnergy Reports2352-48472022-07-018495507A short-term prediction model to forecast power of photovoltaic based on MFA-ElmanXinYu Ma0XiaoHong Zhang1Corresponding author.; Business school, Shanghai DianJi University, Shanghai 201306, ChinaBusiness school, Shanghai DianJi University, Shanghai 201306, ChinaDue to the low accuracy and reliability as well as slow prediction speed of photovoltaic (PV) power short-term prediction, a short-term PV power prediction method based on MFA-Elman neural network is proposed. K-means mean algorithm is employed firstly in this method to cluster the weather type, and then EEDM is used to decompose the PV output power on the various data obtained by clustering. Finally, each decomposition subsequence is inputted into the MFA-optimized Elman neural network to predicting the PV output power, which solves the randomness of initial weight and threshold and slow training speed of Elman neural network. The simulation results show that the MFA-Elman model has smaller prediction error, higher prediction accuracy and reliability, faster prediction speed, which can reach the requirements of short-term prediction of PV power.http://www.sciencedirect.com/science/article/pii/S235248472200213XPhotovoltaicsK-meansEEDMMFA-elmanShort-term prediction
spellingShingle XinYu Ma
XiaoHong Zhang
A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
Energy Reports
Photovoltaics
K-means
EEDM
MFA-elman
Short-term prediction
title A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
title_full A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
title_fullStr A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
title_full_unstemmed A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
title_short A short-term prediction model to forecast power of photovoltaic based on MFA-Elman
title_sort short term prediction model to forecast power of photovoltaic based on mfa elman
topic Photovoltaics
K-means
EEDM
MFA-elman
Short-term prediction
url http://www.sciencedirect.com/science/article/pii/S235248472200213X
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