Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5964
Título: Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids
Autor: Faria, Pedro
Soares, João
Vale, Zita
Palavras-chave: Demand response
Load shifting
Particle swarm optimization
Resources use optimization
Smart grids
Virtual power player
Data: 9-Dez-2014
Editora: IEEE
Relatório da Série N.º: CIASG;2014
Resumo: Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.
URI: http://hdl.handle.net/10400.22/5964
DOI: 10.1109/CIASG.2014.7011562
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7011562&queryText%3D10.1109%2FCIASG.2014.7011562
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
COM_PFaria_2014_GECAD.pdf4,22 MBAdobe PDFVer/Abrir    Acesso Restrito. Solicitar cópia ao autor!


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Degois 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.