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Industrial Facility Electricity Consumption Forecast Using Artificial Neural Networks and Incremental Learning
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Orientador(es)
Resumo(s)
Society’s concerns with electricity consumption have motivated researchers to improve on the way that energy consumption management is done. The reduction of energy consumption and the optimization of energy management are, therefore, two major aspects to be considered. Additionally, load forecast provides relevant information with the support of historical data allowing an enhanced energy management, allowing energy costs reduction. In this paper, the proposed consumption forecast methodology uses an Artificial Neural Network (ANN) and incremental learning to increase the forecast accuracy. The ANN is retrained daily, providing an updated forecasting model. The case study uses 16 months of data, split in 5-min periods, from a real industrial facility. The advantages of using the proposed method are illustrated with the numerical results
Descrição
This article belongs to the Special Issue Time Series Forecasting for Energy Consumption
Palavras-chave
Artificial neural networks Electricity consumption Machine learning Load forecast Industrial facility
Contexto Educativo
Citação
Editora
MDPI