Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could not fit with the normal distribution typically considered in DSSE. For this reason, suitable approaches have to be designed both to model the pseudo-measurements uncertainty and to consider it in the DSSE process. This paper proposes a DSSE algorithm based on the Bayesian theory able to handle appropriately pseudo-measurements with any uncertainty distribution. The procedure used to cluster different categories of prosumers and to generate the pseudo-measurement parameters provided as input to the DSSE is also presented. Tests on a low voltage network show the applicability of the proposed approach and the associated benefits.

Bayesian distribution system state estimation in presence of non-Gaussian pseudo-measurements

MUSCAS, CARLO;SULIS, SARA;PEGORARO, PAOLO ATTILIO
2016

Abstract

Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could not fit with the normal distribution typically considered in DSSE. For this reason, suitable approaches have to be designed both to model the pseudo-measurements uncertainty and to consider it in the DSSE process. This paper proposes a DSSE algorithm based on the Bayesian theory able to handle appropriately pseudo-measurements with any uncertainty distribution. The procedure used to cluster different categories of prosumers and to generate the pseudo-measurement parameters provided as input to the DSSE is also presented. Tests on a low voltage network show the applicability of the proposed approach and the associated benefits.
Normal distribution; Power distribution; Power system state estimation; Bayesian distribution system state estimation; Bayesian theory; DSSE process; Historical behaviour; Low-voltage grid; Low-voltage network; Medium-voltage grid; Non-Gaussian pseudomeasurements; Power injection pseudomeasurement; Pseudomeasurement uncertainty; Smart management; Statistical behaviour; Uncertainty distribution; Bayes methods; Decision support systems; Estimation; Measurement uncertainty; Power measurement; Uncertainty; Voltage measurement; Bayesian Theory; Distribution grids; Non-Gaussian uncertainty; State estimation; Pseudo-measurements
File in questo prodotto:
File Dimensione Formato  
07602803_AMPS.pdf

Solo gestori archivio

Descrizione: File from proceedings
Tipologia: versione editoriale
Dimensione 294.09 kB
Formato Adobe PDF
294.09 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/191850
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 25
social impact