Deep RNN-Based Photovoltaic Power Short-Term Forecast Using Power IoT Sensors

Photovoltaic (PV) power fluctuations caused by weather changes can lead to short-term mismatches in power demand and supply. Therefore, to operate the power grid efficiently and reliably, short-term PV power forecasts are required against these fluctuations. In this paper, we propose a deep RNN-base...

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Vydané v:	Energies (Basel) Ročník 14; číslo 2; s. 436
Hlavní autori:	Ahn, Hyung Keun, Park, Neungsoo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.01.2021
Predmet:	Accuracy Algorithms Alternative energy sources Correlation analysis Electricity distribution Experiments Humidity Internet of Things Internet of Things (IoT) Neural networks Onsite photovoltaic power forecasting algorithm recurrent neural networks (RNN) Renewable resources Sensors Solar energy Wavelet transforms Weather Weather forecasting
ISSN:	1996-1073, 1996-1073
On-line prístup:	Získať plný text
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