Voltage management in the presence of Distributed Energy Resources - Field implementation of a robust Distribution State Estimator with errors in sensor data

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Paper number
598
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
KAMGA, Keddy, EDF R&D, France
Carré, Olivier, Enedis, France
Bouzigon , Benoît , Enedis, France
Abstract
The deployment of Distributed Energy Resources (DER) complicates voltage management on existing MV networks and requires dynamic centralized setting of On Load Tap Changer (OLTC) set point to optimize the network DER hosting capacity. In this frame, Enedis (the French DSO) has been experimenting a Weighted Least Square (WLS) Distribution State Estimator (DSE) in VENTEEA and Smart Grid Vendée (SGV) demonstrators. This algorithm uses sensor-based measurements and pseudo-measurements to determine the state of a network at any time and to allow the OLTC dynamic management.  The VENTEEA experimentation showed that the DSE behaviour can be strongly affected by sensor outliers. These bad data could be due to many reasons such as sensor misuse or failure. As the occurrences of this bad data are not negligible, the accuracy of the DSE becomes inacceptable to Enedis and a way to improve the DSE algorithm had to be found. This paper deals with improving the robustness of the DSE against sensor errors and failures.EDF R&D and Enedis studied, then implemented an M-estimator running alongside the operational WLS estimator on a substation MV networks of the Smart Grid Vendée demonstrator. This paper introduces the M-estimator principle, the way it deals with measurements errors, how to set it up, and the outcomes achieved by both simulation and field tests. It also compares the results of the M-estimator against the WLS state estimator.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/79
http://dx.doi.org/10.34890/155
ISSN
2032-9644
ISBN
978-2-9602415-0-1