Modeling Electricity Consumption and Production in Smart Homes using LSTM Networks-Reference-Cited by-同舟云学术

Modeling Electricity Consumption and Production in Smart Homes using LSTM Networks

Published:2020-12-01 Issue:1 Volume:10 Page:80-89
ISSN:2067-354X
Container-title:International Journal of Advanced Statistics and IT&C for Economics and Life Sciences
language:en
Short-container-title:

Author:

Bachici Miroslav-Andrei¹,Gellert Arpad¹

Affiliation:

1. Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering , “Lucian Blaga” University of Sibiu , Romania

Abstract

Abstract This paper presents a forecasting method of the electricity consumption and production in a household equipped with photovoltaic panels and a smart energy management system. The prediction is performed with a Long Short-Term Memory recurrent neural network. The datasets collected during five months in a household are used for the evaluations. The recurrent neural network is configured optimally to reduce the forecasting errors. The results show that the proposed method outperforms an earlier developed Multi-Layer Perceptron, as well as the Autoregressive Integrated Moving Average statistical forecasting algorithm.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/ijasitels-2020-0009

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