Robust Distribution Network Reconfiguration in the Presence of Distributed Generation Under Uncertainty in Demand and Load Variations

In modern power systems, distributed generation (DG) plays an important role in energy losses reduction, but DG penetration in such networks is restricted by technical and investment limitations. Therefore, distribution network reconfiguration (DNR) and DG operation reduce power losses more efficien...

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Veröffentlicht in:IEEE transactions on power delivery 2023-10, Vol.38 (5), p.1-16
Hauptverfasser: Mahdavi, Meisam, Schmitt, Konrad, Jurado, Francisco
Format: Artikel
Sprache:eng
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Zusammenfassung:In modern power systems, distributed generation (DG) plays an important role in energy losses reduction, but DG penetration in such networks is restricted by technical and investment limitations. Therefore, distribution network reconfiguration (DNR) and DG operation reduce power losses more efficiently than when only DG is utilized. Also, network reconfiguration mitigates improper DG placement in such systems which are subjected to high penetration of variable loads and DG. On the other hand, electrical energy demand is estimated by load forecasting methods and therefore is a time-variant and uncertain parameter. Moreover, DG power generation is uncertain and depends on variable load power. Consequently, models presented for the reconfiguration problem should be adequately robust against load and generation uncertainties. Thus, the present paper proposes an effective robust model for reconfiguring distribution networks with load and generation uncertainties. The proposed model is sufficiently simple for implementation and is accurate enough to find the optimal solutions in acceptable computational times. The main features of the proposed model are its high robustness against uncertain parameters, in which proposed configurations are not changed easily by small variations in DG power and load amounts, and its effectiveness, which means that uncertain parameters may change the obtained solutions.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2023.3277816