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Ocenjevalnik stanja nizkonapetostnega razdelilnega omrežja
PODBREGAR, GREGA (Author), Pantoš, Miloš (Mentor) More about this mentor... This link opens in a new window

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Abstract
Izvedeno delo se nanaša na razvoj konceptnega modela ocenjevalnika stanja nizkonapetostnega razdelilnega omrežja. Namen naloge je bil izdelati preprost algoritem ocenjevalnika stanja, ki deluje na osnovi metode najmanjših uteženih kvadratov z uporabo simuliranih meritev pametnih števcev, ter preveriti njegovo delovanje na podlagi simulacij dogodkov, ki se lahko zgodijo v realnosti. Izbran in izveden s pomočjo Matlaba je bil matematični algoritem ocenjevalnika stanja, ki je bil preverjen na modelu nizkonapetostnega omrežja. Preizkusi so pokazali zadostno odpornost algoritma na naključne motnje v merjenih vrednostih, z deležem neustreznih meritev in uporabo psevdo merjenih vrednosti pa so bile preizkušene skrajne meje njegovega delovanja. Preprosta simulacija je pokazala možnost praktične uporabe algoritma pri odkrivanju mest nezakonitega odjema ali nepravilnega delovanja merilne naprave.

Language:Slovenian
Keywords:Nizkonapetostno razdelilno omrežje, ocenjevalnik stanja, uteženi najmanjši kvadrati
Work type:Master's thesis/paper (mb22)
Organization:FE - Faculty of Electrical Engineering
Year:2015
Views:602
Downloads:177
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Secondary language

Language:English
Title:Low-voltage distribution network state estimator
Abstract:
The thesis addresses development of a simple low-voltage distribution network state estimator. A goal was to create a state estimator model, based on a weighted least square algorithm, using simulated measurements of smart meters. Model’s performance was evaluated by the simulations of possible real-case scenarios. A proper mathematical algorithm was chosen and developed using Matlab. A simple low voltage network model was used to test the state estimator algorithm. The results of simulations confirmed the robustness of the algorithm in case of random noises in the measurements, the use of bad measurements and pseudo-measurements revealed the sensitivity of algorithm in case of bad data. This bad data was used to test the limits of the state estimator model. Possibility for detection and identification of electricity theft or instrumentation malfunction was shown using simple simulation.

Keywords:Low-voltage distribution network, state estimator, weighted least squares

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