### Abstract

The magnitudes of voltage dips on non-monitored buses can be estimated by applying Bayes's theorem with measured voltage dips on a limited number of monitored buses. Bayes's theorem is used to obtain the grid conditions, including the network impedance, load, distributed generation vector, and short-circuit location, from which the voltage magnitudes along the feeder can be calculated. In order to implement this approach effectively, it is necessary to understand which parameters among the grid conditions are more significant for the estimation performance and how the uncertainties associated with these parameters affect the estimation results. Moreover, since the measurement structure provides observations to calculate the posterior distribution from the prior distribution of the grid conditions. The measurement parameters, quantities, and accuracy levels are varied in simulations to obtain an optimum measurement structure balancing between the cost and the measurement performance. This paper presented the results of the sensitivity studies which have been done on the IEEE 13-Bus and 123-Bus test systems. The results shows the performance of the voltage dip state estimation approach is less sensitive to the uncertainty level of the load while more sensitive to those of the DG, the short-circuit power, the zero sequence impedance of the cable and the short-circuit resistance. The voltage measurement accuracy is more important than that of current and phase angles. The proposed method shows much stronger robustness compared to the conventional one and the estimation performance can be improved through several measures, e.g. adding more measurement points.

Language | English |
---|---|

Pages | 888-896 |

Number of pages | 9 |

Journal | International Journal of Electrical Power and Energy Systems |

Volume | 113 |

DOIs | |

State | Published - 1 Dec 2019 |

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### Keywords

- Bayesian inference
- Estimation
- Population Monte Carlo (PMC) sampling
- Sensitivity
- Voltage dip

### Cite this

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*International Journal of Electrical Power and Energy Systems*, vol. 113, pp. 888-896. DOI: 10.1016/j.ijepes.2019.06.005

**Incorporating network uncertainties in voltage dip state estimation.** / Ye, G. (Corresponding author); Nijhuis, M.; Cuk, V.; Cobben, J.F.G.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Incorporating network uncertainties in voltage dip state estimation

AU - Ye,G.

AU - Nijhuis,M.

AU - Cuk,V.

AU - Cobben,J.F.G.

PY - 2019/12/1

Y1 - 2019/12/1

N2 - The magnitudes of voltage dips on non-monitored buses can be estimated by applying Bayes's theorem with measured voltage dips on a limited number of monitored buses. Bayes's theorem is used to obtain the grid conditions, including the network impedance, load, distributed generation vector, and short-circuit location, from which the voltage magnitudes along the feeder can be calculated. In order to implement this approach effectively, it is necessary to understand which parameters among the grid conditions are more significant for the estimation performance and how the uncertainties associated with these parameters affect the estimation results. Moreover, since the measurement structure provides observations to calculate the posterior distribution from the prior distribution of the grid conditions. The measurement parameters, quantities, and accuracy levels are varied in simulations to obtain an optimum measurement structure balancing between the cost and the measurement performance. This paper presented the results of the sensitivity studies which have been done on the IEEE 13-Bus and 123-Bus test systems. The results shows the performance of the voltage dip state estimation approach is less sensitive to the uncertainty level of the load while more sensitive to those of the DG, the short-circuit power, the zero sequence impedance of the cable and the short-circuit resistance. The voltage measurement accuracy is more important than that of current and phase angles. The proposed method shows much stronger robustness compared to the conventional one and the estimation performance can be improved through several measures, e.g. adding more measurement points.

AB - The magnitudes of voltage dips on non-monitored buses can be estimated by applying Bayes's theorem with measured voltage dips on a limited number of monitored buses. Bayes's theorem is used to obtain the grid conditions, including the network impedance, load, distributed generation vector, and short-circuit location, from which the voltage magnitudes along the feeder can be calculated. In order to implement this approach effectively, it is necessary to understand which parameters among the grid conditions are more significant for the estimation performance and how the uncertainties associated with these parameters affect the estimation results. Moreover, since the measurement structure provides observations to calculate the posterior distribution from the prior distribution of the grid conditions. The measurement parameters, quantities, and accuracy levels are varied in simulations to obtain an optimum measurement structure balancing between the cost and the measurement performance. This paper presented the results of the sensitivity studies which have been done on the IEEE 13-Bus and 123-Bus test systems. The results shows the performance of the voltage dip state estimation approach is less sensitive to the uncertainty level of the load while more sensitive to those of the DG, the short-circuit power, the zero sequence impedance of the cable and the short-circuit resistance. The voltage measurement accuracy is more important than that of current and phase angles. The proposed method shows much stronger robustness compared to the conventional one and the estimation performance can be improved through several measures, e.g. adding more measurement points.

KW - Bayesian inference

KW - Estimation

KW - Population Monte Carlo (PMC) sampling

KW - Sensitivity

KW - Voltage dip

UR - http://www.scopus.com/inward/record.url?scp=85067400448&partnerID=8YFLogxK

U2 - 10.1016/j.ijepes.2019.06.005

DO - 10.1016/j.ijepes.2019.06.005

M3 - Article

VL - 113

SP - 888

EP - 896

JO - International Journal of Electrical Power and Energy Systems

T2 - International Journal of Electrical Power and Energy Systems

JF - International Journal of Electrical Power and Energy Systems

SN - 0142-0615

ER -