Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1391
Título: LMP based bid formation for virtual power players operating in smart grids
Autor: Vale, Zita
Morais, H.
Faria, Pedro
Canizes, Bruno
Sousa, Tiago
Palavras-chave: Artificial intelligence
Artificial neural networks
Energy resources management
Intelligent power systems
Locational Marginal Prices (LMP)
Particle swarm optimization
Data: 2011
Editora: IEEE
Resumo: Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.
URI: http://hdl.handle.net/10400.22/1391
ISBN: 978-1-4577-1000-1
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6039853
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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