Szczegóły publikacji
Opis bibliograficzny
An improved method of busbar voltage reconstruction from signals of electric field sensors installed in an indoor MV substation / Dariusz BORKOWSKI // Metrology and Measurement Systems : quarterly of Polish Academy of Sciences ; ISSN 2080-9050. — Tytuł poprz.: Metrologia i Systemy Pomiarowe ; ISSN: 0860-8229. — 2018 — vol. 25 iss. 1, s. 71–86. — Bibliogr. s. 85–86, Abstr. — Publikacja dostępna online od: 2018-03-26
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 117619 |
|---|---|
| Data dodania do BaDAP | 2018-11-29 |
| Tekst źródłowy | URL |
| DOI | 10.24425/118155 |
| Rok publikacji | 2018 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Metrology and Measurement Systems |
Abstract
This paper presents an improved method for the reconstruction of busbar voltage waveforms from signals acquired by a system of electric field (EF) sensors located in an indoor medium voltage substation. In the previous work [8], the authors proposed the use of black-box models in the form of artificial neural networks (ANNs) for this task. In this paper it is shown that a parametric model of the system of EF sensors can reconstruct voltages with much lower errors, provided that it is accurately identified. The model identification is done by minimization of a nonlinear goal function, i.e. mean squared error (MSE) of voltage reconstruction. As a result of examining several optimization techniques, the method based on simulated annealing extended with a simplex search, is proposed. The performance of the model identified with this method is at least 8 times better in terms of MSE and at least 12 times better in terms of frequency domain errors than the best one of concurrent ANNs.
