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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72449
Title: 
A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty
Author(s): 
Institution: 
  • Universidade Estadual Paulista (UNESP)
  • Efficient Energy Management Research Group (GIMEL)
Abstract: 
Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.
Issue Date: 
31-May-2011
Citation: 
2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 257-262.
Time Duration: 
257-262
Keywords: 
  • Distributed generation
  • Evolutionary multi-objective programming
  • Power losses
  • Analysis tools
  • DG technology
  • DG unit
  • Distributed Generation
  • Distributed generations
  • Distribution systems
  • Multiobjective programming
  • Operation cost
  • Optimal operation
  • Potential benefits
  • Power-losses
  • Renewable resource
  • Stochasticity
  • Test systems
  • Distributed power generation
  • Multiobjective optimization
  • Distributed computer systems
Source: 
http://dx.doi.org/10.1109/TDC-LA.2010.5762891
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/72449
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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