## Abstract

Electrical models of power distribution grids are used in applications such as state estimation and Optimal Power Flow (OPF), the reliability of which depends on the accuracy of the model. This work presents an approach for estimating distribution line parameters from Remote Terminal Unit (RTU) measurements which are subject to measurement device tolerances and random noise. Building upon an earlier work which introduced a measurement tolerance compensation model, we aim to improve a) the robustness towards noisy data and b) the estimate of the parallel susceptance. For this purpose, we employ an Extended Kalman Filter (EKF) whose measurement

noise covariance matrix is modified in order to account for all noisy variables in the overdetermined system. Simulations confirm the advantages of the EKF over the previously used Least-Squares (LSQ) estimator. In the low random noise cases considered in this paper, the EKF yields a four-fold improvement over the LSQ for the parallel susceptance across all quantization ranges. For the highest levels of random and quantization noise, the EKF performs about 1.5 to 3 times better than the LSQ

for all line parameters. Furthermore, the EKF shows more consistent behavior when applied to data obtained from a laboratory distribution grid, which exhibits uncertainties that are not accounted for in the models.

noise covariance matrix is modified in order to account for all noisy variables in the overdetermined system. Simulations confirm the advantages of the EKF over the previously used Least-Squares (LSQ) estimator. In the low random noise cases considered in this paper, the EKF yields a four-fold improvement over the LSQ for the parallel susceptance across all quantization ranges. For the highest levels of random and quantization noise, the EKF performs about 1.5 to 3 times better than the LSQ

for all line parameters. Furthermore, the EKF shows more consistent behavior when applied to data obtained from a laboratory distribution grid, which exhibits uncertainties that are not accounted for in the models.

Original language | English |
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Title of host publication | Proceedings of 2016 IEEE Electrical Power and Energy Conference |

Number of pages | 6 |

Publisher | IEEE |

Publication date | 2016 |

ISBN (Print) | 978-1-5090-1919-9 |

Publication status | Published - 2016 |

Event | IEEE Electrical Power and Energy Conference 2016 - Ottawa, Canada Duration: 12 Oct 2016 → 14 Oct 2016 |

### Conference

Conference | IEEE Electrical Power and Energy Conference 2016 |
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Country | Canada |

City | Ottawa |

Period | 12/10/2016 → 14/10/2016 |