Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5928
Título: A Learning Algorithm and System Approach to Address Exceptional Events in Domestic Consumption Management
Autor: Gomes, Luis
Fernandes, Filipe
Vale, Zita
Faria, Pedro
Ramos, Carlos
Palavras-chave: Domestic consumption
Exceptional events
Intelligent load management
Machine learning
Smart Grid
Data: Dez-2014
Editora: IEEE
Relatório da Série N.º: CIASG;2014
Resumo: The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.
URI: http://hdl.handle.net/10400.22/5928
DOI: 10.1109/CIASG.2014.7011564
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7011564&queryText%3DA+Learning+Algorithm+and+System+Approach+to+Address+Exceptional+Events+in+Domestic+Consumption+Management
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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