State estimation of medium voltage distribution networks using smart meter measurements

Al-Wakeel, Ali ORCID: https://orcid.org/0000-0003-4970-7309, Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602 and Jenkins, Nicholas ORCID: https://orcid.org/0000-0003-3082-6260 2016. State estimation of medium voltage distribution networks using smart meter measurements. Applied Energy 184 , pp. 207-218. 10.1016/j.apenergy.2016.10.010

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Abstract

Distributed generation and low carbon loads are already leading to some restrictions in the operation of distribution networks and higher penetrations of e.g. PV generation, heat pumps and electric vehicles will exacerbate such problems. In order to manage the distribution network effectively in this new situation, increased real-time monitoring and control will become necessary. In the future, distribution network operators will have smart meter measurements available to them to facilitate safe and cost-effective operation of distribution networks. This paper investigates the application of smart meter measurements to extend the observability of distribution networks. An integrated load and state estimation algorithm was developed and tested using residential smart metering measurements and an 11 kV residential distribution network. Simulation results show that smart meter measurements, both real-time and pseudo measurements derived from them, can be used together with state estimation to extend the observability of a distribution network. The integrated load and state estimation algorithm was shown to produce accurate voltage magnitudes and angles at each busbar of the network. As a result, the algorithm can be used to enhance distribution network monitoring and control

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords:	Cluster analysis; Smart meter measurements; Load estimation; State estimation
Publisher:	Elsevier
ISSN:	0306-2619
Date of First Compliant Deposit:	19 October 2016
Date of Acceptance:	1 October 2016
Last Modified:	05 May 2023 16:32
URI:	https://orca.cardiff.ac.uk/id/eprint/95446

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