Multiobjective Optimal Reconfiguration of MV Networks with Different Earthing Systems

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Abstract

The paper deals with the traditional problem of multiobjective optimal reconfiguration applied to power distribution systems considering the safety issue in the formulation. The applications are devoted to the solution of the posed problem in networks in which coexist energy sources with unearthed neutral point and resonant earthed neutral point. After a brief review of the most recent papers on optimal reconfiguration, the paper outlines the safety problem and provides a solution to the multiobjective problem using the Non dominated Sorting Genetic Algorithm II aiming at: minimal power losses operation, safety check at distribution substations and load balancing among the HV/MV transformers. Finally test results on a large MV distribution network are reported and discussed and a comparison between the Non dominated Sorting Genetic Algorithm II and a Fuzzy Evolution Strategy Algorithm is presented.
Lingua originaleEnglish
Stato di pubblicazionePublished - 2010

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Electric grounding
Sorting
Genetic algorithms
Electric power distribution
Resource allocation

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology

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title = "Multiobjective Optimal Reconfiguration of MV Networks with Different Earthing Systems",
abstract = "The paper deals with the traditional problem of multiobjective optimal reconfiguration applied to power distribution systems considering the safety issue in the formulation. The applications are devoted to the solution of the posed problem in networks in which coexist energy sources with unearthed neutral point and resonant earthed neutral point. After a brief review of the most recent papers on optimal reconfiguration, the paper outlines the safety problem and provides a solution to the multiobjective problem using the Non dominated Sorting Genetic Algorithm II aiming at: minimal power losses operation, safety check at distribution substations and load balancing among the HV/MV transformers. Finally test results on a large MV distribution network are reported and discussed and a comparison between the Non dominated Sorting Genetic Algorithm II and a Fuzzy Evolution Strategy Algorithm is presented.",
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AU - Campoccia, Angelo

AU - Zizzo, Gaetano

AU - Riva Sanseverino, Eleonora

PY - 2010

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N2 - The paper deals with the traditional problem of multiobjective optimal reconfiguration applied to power distribution systems considering the safety issue in the formulation. The applications are devoted to the solution of the posed problem in networks in which coexist energy sources with unearthed neutral point and resonant earthed neutral point. After a brief review of the most recent papers on optimal reconfiguration, the paper outlines the safety problem and provides a solution to the multiobjective problem using the Non dominated Sorting Genetic Algorithm II aiming at: minimal power losses operation, safety check at distribution substations and load balancing among the HV/MV transformers. Finally test results on a large MV distribution network are reported and discussed and a comparison between the Non dominated Sorting Genetic Algorithm II and a Fuzzy Evolution Strategy Algorithm is presented.

AB - The paper deals with the traditional problem of multiobjective optimal reconfiguration applied to power distribution systems considering the safety issue in the formulation. The applications are devoted to the solution of the posed problem in networks in which coexist energy sources with unearthed neutral point and resonant earthed neutral point. After a brief review of the most recent papers on optimal reconfiguration, the paper outlines the safety problem and provides a solution to the multiobjective problem using the Non dominated Sorting Genetic Algorithm II aiming at: minimal power losses operation, safety check at distribution substations and load balancing among the HV/MV transformers. Finally test results on a large MV distribution network are reported and discussed and a comparison between the Non dominated Sorting Genetic Algorithm II and a Fuzzy Evolution Strategy Algorithm is presented.

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