Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAn improved load flow method for MV networks based on LV load measurements and estimations
Anno di pubblicazione2019
Formato
  • Elettronico
  • Cartaceo
Autore/iA. Cataliotti; C. Cervellera; V. Cosentino; D. Di Cara; M. Gaggero; D. Macciò; G. Marsala; A. Ragusa; G. Tinè
Affiliazioni autori1. Department of Energy, Information Engineering and Mathematical Models, University of Palermo, 90128 Palermo, Italy 2. Institute of Marine Engineering, National Research Council of Italy, 16149 Genoa, Italy 3. Department of Energy, Information Engineering and Mathematical Models, University of Palermo, 90128 Palermo, Italy 4. Institute of Marine Engineering, National Research Council of Italy, 90146 Palermo, Italy 5. Institute of Marine Engineering, National Research Council of Italy, 16149 Genoa, Italy 6. Institute of Marine Engineering, National Research Council of Italy, 16149 Genoa, Italy 7. Institute of Marine Engineering, National Research Council of Italy, 90146 Palermo, Italy 8. Institute of Marine Engineering, National Research Council of Italy, 90146 Palermo, Italy 9. Institute of Marine Engineering, National Research Council of Italy, 90146 Palermo, Italy
Autori CNR e affiliazioni
  • GIOVANNI TINE'
  • CRISTIANO CERVELLERA
  • ANTONELLA RAGUSA
  • GIUSEPPE MARSALA
  • DANILO MACCIO'
  • MAURO GAGGERO
  • DARIO DI CARA
Lingua/e
  • inglese
AbstractA novel measurement approach for power-flow analysis in medium-voltage (MV) networks, based on load power measurements at low-voltage level in each secondary substation (SS) and only one voltage measurement at the MV level at primary substation busbars, was proposed by the authors in previous works. In this paper, the method is improved to cover the case of temporary unavailability of load power measurements in some SSs. In particular, a new load power estimation method based on artificial neural networks (ANNs) is proposed. The method uses historical data to train the ANNs and the real-time available measurements to obtain the load estimations. The load-flow algorithm is applied with the estimated load powers, and the MV network state variables are obtained. The proposed method is validated for the real MV distribution network of the island of Ustica. The loads of selected SSs are estimated for two full days of different seasons. In comparison with previous works, satisfactory results are obtained in terms of uncertainty in the calculated power flows, thus suggesting the applicability of the proposed method for real-time monitoring of MV distribution networks.
Lingua abstractinglese
Altro abstract-
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Pagine da430
Pagine a438
Pagine totali9
RivistaIEEE transactions on instrumentation and measurement
Attiva dal 1963
Editore: Institute of Electrical and Electronics Engineers. - New York,
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 0018-9456
Titolo chiave: IEEE transactions on instrumentation and measurement
Titolo proprio: IEEE transactions on instrumentation and measurement.
Titolo abbreviato: IEEE trans. instrum. meas.
Titoli alternativi:
  • Transactions on instrumentation and measurement
  • Instrumentation and measurement
Numero volume della rivista68
Fascicolo della rivista2
DOI10.1109/TIM.2018.2847818
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-85049459857)
  • ISI Web of Science (WOS) (Codice:000454332000012)
Parole chiaveArtificial neural networks, load flow, power measurement, power system management, power system measurements, smart grids, state estimation
Link (URL, URI)-
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Note/Altre informazioni-
Strutture CNR
  • INM — Istituto di iNgegneria del Mare
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Allegati
An improved load flow method for MV networks based on LV load measurements and estimations (documento privato )
Descrizione: VoR Version of Record - versione finale pubblicata
Tipo documento: application/pdf
An improved load flow method for MV networks based on LV load measurements and estimations (documento privato )
Descrizione: AAM - Accepted Version (postprint)
Tipo documento: application/pdf