Abstract
| Original language | English |
|---|---|
| Title of host publication | 2015 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), 9-12 November 2015, Yokohama, Japan |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 00915-00920 |
| ISBN (Electronic) | 978-1-4799-1762-4 |
| DOIs | |
| Publication status | Published - 2015 |
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Voltage dip state estimation in distribution networks by applying Bayesian inference. / Ye, G.; Xiang, Y.; Cuk, V.; Cobben, J.F.G.
2015 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), 9-12 November 2015, Yokohama, Japan. Piscataway : Institute of Electrical and Electronics Engineers, 2015. p. 00915-00920.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Voltage dip state estimation in distribution networks by applying Bayesian inference
AU - Ye, G.
AU - Xiang, Y.
AU - Cuk, V.
AU - Cobben, J.F.G.
PY - 2015
Y1 - 2015
N2 - The performance of the system regarding voltage dips is commonly characterized with the SARFIx index, which gives the average frequency of voltage dips. Due to the limited number of measurement points, the actual residual voltages of many nodes are not taken into account when the index is calculated. As it's impossible to measure the dip level at every node of a feeder, the voltage dips occurring at nonmonitored nodes should be estimated from the values recorded at monitored nodes with the consideration of measurement accuracy. This paper proposes a voltage dip state estimation method based on Bayesian inference. The performance of the proposed method is assessed through case study applied in a typical distribution network. Monte Carlo simulation is used to obtain the statistic results. The proposed method shows the flexibility of different measurement quantities and the adequacy for the analysis of distribution networks.
AB - The performance of the system regarding voltage dips is commonly characterized with the SARFIx index, which gives the average frequency of voltage dips. Due to the limited number of measurement points, the actual residual voltages of many nodes are not taken into account when the index is calculated. As it's impossible to measure the dip level at every node of a feeder, the voltage dips occurring at nonmonitored nodes should be estimated from the values recorded at monitored nodes with the consideration of measurement accuracy. This paper proposes a voltage dip state estimation method based on Bayesian inference. The performance of the proposed method is assessed through case study applied in a typical distribution network. Monte Carlo simulation is used to obtain the statistic results. The proposed method shows the flexibility of different measurement quantities and the adequacy for the analysis of distribution networks.
U2 - 10.1109/IECON.2015.7392216
DO - 10.1109/IECON.2015.7392216
M3 - Conference contribution
SP - 915
EP - 920
BT - 2015 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), 9-12 November 2015, Yokohama, Japan
PB - Institute of Electrical and Electronics Engineers
CY - Piscataway
ER -