Prediction model training method based on big data and photovoltaic power generation performance detection method

The embodiment of the invention discloses a prediction model training method based on big data and a photovoltaic power generation performance detection method. The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respe...

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Hauptverfasser: GUO JIANBO, ZHANG LEI, JIN ZHIBIN, LU LINGLING, ZHANG WEI, ZHANG QIANG, HE JIE, TAO YONGJING
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creator GUO JIANBO
ZHANG LEI
JIN ZHIBIN
LU LINGLING
ZHANG WEI
ZHANG QIANG
HE JIE
TAO YONGJING
description The embodiment of the invention discloses a prediction model training method based on big data and a photovoltaic power generation performance detection method. The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. According to the detection method, power generation power prediction detection is carried out based on a photovoltaic power generation power prediction model obtained through tra
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The training method comprises the following steps: carrying out model training on an LSTM common model based on a first training set, respectively training a plurality of LSTM independent models based on a plurality of second training sets, and judging, screening and determining an optimal model as a photovoltaic power generation power prediction model by utilizing a first loss function; and then, performing hyper-parameter training on the photovoltaic power generation power prediction model based on the test set, and performing prediction judgment by using a second loss function to obtain a photovoltaic power generation power prediction model with an optimal hyper-parameter. 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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
ELECTRICITY
GENERATION
GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRA-REDRADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, E.G. USINGPHOTOVOLTAIC [PV] MODULES
PHYSICS
title Prediction model training method based on big data and photovoltaic power generation performance detection method
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