Effect of Smart Meter Measurements Data On Distribution State Estimation

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Smart distribution grids with renewable energy based generators and demand response resources (DRR) requires accurate state estimators for real time control. Distribution grid state estimators are normally based on accumulated smart meter measurements. However, increase of measurements in the physical grid can enforce significant stress not only on the communication infrastructure but also in the control algorithms. This paper aims to propose a methodology to analyze needed real time smart meter data from low voltage distribution grids and their applicability in distribution state estimation. Different scenarios are created to observe the algorithm performance and effects on the estimation quality. The CIGRE benchmark network for low voltage distribution grids is used for simulation and analysis. This work also investigates the necessity of proper load modelling to reduce the stress due to huge amount of measurement data by utilizing them smartly via state estimation.
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Details

Smart distribution grids with renewable energy based generators and demand response resources (DRR) requires accurate state estimators for real time control. Distribution grid state estimators are normally based on accumulated smart meter measurements. However, increase of measurements in the physical grid can enforce significant stress not only on the communication infrastructure but also in the control algorithms. This paper aims to propose a methodology to analyze needed real time smart meter data from low voltage distribution grids and their applicability in distribution state estimation. Different scenarios are created to observe the algorithm performance and effects on the estimation quality. The CIGRE benchmark network for low voltage distribution grids is used for simulation and analysis. This work also investigates the necessity of proper load modelling to reduce the stress due to huge amount of measurement data by utilizing them smartly via state estimation.
Original languageEnglish
Title of host publicationProceedings of the 19th IEEE International Conference on Industrial Technology (ICIT 2018)
Number of pages6
PublisherIEEE Press
Publication dateFeb 2018
Pages1207-1212
ISBN (Electronic)978-1-5090-5949-2
DOI
Publication statusPublished - Feb 2018
Publication categoryResearch
Peer-reviewedYes
Event19th IEEE International Conference on Industrial Technology (ICIT 2018) - Lyon, France
Duration: 20 Feb 201822 Feb 2018

Conference

Conference19th IEEE International Conference on Industrial Technology (ICIT 2018)
LandFrance
ByLyon
Periode20/02/201822/02/2018

    Research areas

  • Smart meter measurements, Active distribution grid, State estimation, Observability

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