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[43602] Artykuł:

Application of the evolutionary algorithm with memory at the population level for restoration service of electric power distribution networks

Czasopismo: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS   Tom: 63, Zeszyt: Complete, Strony: 695-704
ISSN:  0142-0615
Wydawca:  ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
Opublikowano: Grudzień 2014
Liczba arkuszy wydawniczych:  0.51
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Procent
udziału
Liczba
punktów
Jan Czesław StępieńWEAiIKatedra Elektrotechniki Przemysłowej i Automatyki**502.50  
Sylwester Filipiak orcid logoWEAiIKatedra Elektrotechniki Przemysłowej i Automatyki**502.50  

Grupa MNiSW:  Recenzowana publikacja w języku innym niż polski w zagranicznym czasopiśmie spoza listy
Punkty MNiSW: 5
Klasyfikacja Web of Science: Article


Pełny tekstPełny tekst     DOI LogoDOI     Web of Science Logo Web of Science     Web of Science LogoYADDA/CEON    
Keywords:

Distribution power networks  Restoration service  Evolutionary algorithms  Classifier systems 



Abstract:

The problem of optimising the configuration of electric power distribution networks during changing loadings and in malfunction conditions of the network is a task of multi-criteria optimisation. In the article is presented the co-evolutionary algorithm with memory at the population level, enabling the search for pareto-optimal solutions such as are in the analysed task of network configurations. The drawn up method is used in the organisation of evolutionary algorithm memory uses the theoretical bases of classifying systems. The method presented in the article enables effective search of optimal configurations of distribution networks for various network loadings and also network malfunction conditions. The application of a classification system to the analysed task also enables improvement of the effectiveness of the performance process of designating the scenario of the substitute network configurations. Improvement of the efficiency of the network configuration designation process is obtained using the sought information in the collections of classifiers.



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