The increasing number of power transactions and the difficulties in re-powering electrical infrastructures is pushing Transmission System Operators in defining new loading policies aimed at increasing the exploitation of existing power components, especially overhead transmission lines. In this scenario one of most promising enabling technology is the assessment of the average conductor temperature by processing synchrophasor measurements, which will be largely available due to the increasing pervasion of Wide Area Measurement Systems. The adoption of this technology could allow the TSO to get a realistic picture of the actual thermal state of the power system, which is a strategic information useful to reliable exploit the actual power components loadability. On the other hand, the effectiveness of this thermal estimation process could be compromised by the data uncertainty affecting the synchrophasor measurements, which can led to erroneous estimation of the real conductor temperature. To address this issue, in this paper the authors propose a reliable computing framework based on Interval Mathematic, which allows to solve the thermal state estimation problem by explicitly considering the effect of measurement uncertainties. Detailed experimental results obtained on a real 400 kV transmission line are presented and discussed in order to demonstrate the effectiveness of the proposed framework in a realistic application domain.

An interval mathematic based methodology for reliable estimation of transmission line temperature / Coletta, G.; Vaccaro, A.; Villacci, D.. - 2018-:(2018), pp. 1-6. (Intervento presentato al convegno 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 tenutosi a usa nel 2017) [10.1109/PESGM.2017.8273731].

An interval mathematic based methodology for reliable estimation of transmission line temperature

Villacci, D.
2018

Abstract

The increasing number of power transactions and the difficulties in re-powering electrical infrastructures is pushing Transmission System Operators in defining new loading policies aimed at increasing the exploitation of existing power components, especially overhead transmission lines. In this scenario one of most promising enabling technology is the assessment of the average conductor temperature by processing synchrophasor measurements, which will be largely available due to the increasing pervasion of Wide Area Measurement Systems. The adoption of this technology could allow the TSO to get a realistic picture of the actual thermal state of the power system, which is a strategic information useful to reliable exploit the actual power components loadability. On the other hand, the effectiveness of this thermal estimation process could be compromised by the data uncertainty affecting the synchrophasor measurements, which can led to erroneous estimation of the real conductor temperature. To address this issue, in this paper the authors propose a reliable computing framework based on Interval Mathematic, which allows to solve the thermal state estimation problem by explicitly considering the effect of measurement uncertainties. Detailed experimental results obtained on a real 400 kV transmission line are presented and discussed in order to demonstrate the effectiveness of the proposed framework in a realistic application domain.
2018
9781538622124
An interval mathematic based methodology for reliable estimation of transmission line temperature / Coletta, G.; Vaccaro, A.; Villacci, D.. - 2018-:(2018), pp. 1-6. (Intervento presentato al convegno 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 tenutosi a usa nel 2017) [10.1109/PESGM.2017.8273731].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/11588/871207
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact