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Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm

Journal Article


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Abstract


  • Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented.

UOW Authors


  •   Aghaei, Jamshid (external author)
  •   Muttaqi, Kashem
  •   Azizivahed, Ali (external author)
  •   Gitizadeh, Mohsen (external author)

Publication Date


  • 2014

Published In


Citation


  • J. Aghaei, K. M. Muttaqi, A. Azizivahed & M. Gitizadeh, "Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm," Energy, vol. 65, pp. 398-411, 2014.

Scopus Eid


  • 2-s2.0-84892963062

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=3903&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2894

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 398

End Page


  • 411

Volume


  • 65

Place Of Publication


  • United Kingdom

Abstract


  • Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented.

UOW Authors


  •   Aghaei, Jamshid (external author)
  •   Muttaqi, Kashem
  •   Azizivahed, Ali (external author)
  •   Gitizadeh, Mohsen (external author)

Publication Date


  • 2014

Published In


Citation


  • J. Aghaei, K. M. Muttaqi, A. Azizivahed & M. Gitizadeh, "Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm," Energy, vol. 65, pp. 398-411, 2014.

Scopus Eid


  • 2-s2.0-84892963062

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=3903&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2894

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 398

End Page


  • 411

Volume


  • 65

Place Of Publication


  • United Kingdom