Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1423
Título: ANN based support for distributed energy resources scheduling in smart grids
Autor: Vale, Zita
Morais, H.
Faria, Pedro
Palavras-chave: ANN based support
Distributed energy resources
Smart grids
MINLP
Data: 2011
Editora: International Federation of Automatic Control (IFAC)
Relatório da Série N.º: World Congress; Vol. 18, Part 1
Resumo: The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.
URI: http://hdl.handle.net/10400.22/1423
Versão do Editor: http://www.ifac-papersonline.net/Detailed/48691.html
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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