Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1419
Título: Genetic algorithm methodology applied to intelligent house control
Autor: Fernandes, Filipe
Sousa, Tiago
Silva, Marco
Morais, H.
Vale, Zita
Faria, Pedro
Palavras-chave: Artificial intelligence
Genetic algorithm
Mixed- integer non-linear programming
SCADA
Smart grid
Data: 2011
Editora: IEEE
Resumo: In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.
URI: http://hdl.handle.net/10400.22/1419
ISBN: 978-1-4244-9893-2
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5953341
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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