Alocação de Medidores de Qualidade de Energia para Sistemas de Distribuição Utilizando Algoritmos Genéticos

  • Júlia O. Fernandes Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba, MG
  • João V. G. Araújo Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba, MG
  • Cleiton Sudré Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba, MG
  • Jáder F. D. Breda Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba, MG
  • José C. M. Vieira Jr. Departamento de Engenharia Elétrica e de Computação, Escola de Engenharia de São Carlos, Universidade de São Paulo, SP
Keywords: Meters Allocation, Distribution System, Genetic Algorithms, Singular Value Decomposition, Power Quality

Abstract

Considering the current energy scenario, technological developments and, especially, the global economic context, it is necessary that the power quality supplied by utilities is constantly monitored, since disturbances of the most diverse classes and orders affect the power distribution system. Therefore, the allocation of power quality meters in distribution system has been increasingly adopted to prevent and even impede major losses to consumers and the utilities itself. In addition, every system has locations where power quality measurement is even more relevant and which can be considered as strategic measurement points. Thus, this work proposes a method of allocation of power quality meters for power distribution systems through genetic algorithms in conjunction with the singular value decomposition technique, which establishes the position, quantity and type of meter to be allocated, be it voltage or current, in order to guarantee, in a more economical way, the total observability of the system. The methodology was validated through tests using the IEEE 34-bus distribution system through two different scenarios taking into account the strategic points of this system. In comparison with other related works used the same system scenarios for testing, the algorithm proved to be more effective by reducing the number of equipment to be installed to ensure total system observability.
Published
2022-11-30
Section
Articles