Sara Sulis

University of Cagliari, Department of Electrical and Electronic Engineering - DIEE, Faculty Member

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Sara Sulis is Associate Professor of Electrical and Electronic Measurements at the Department of Electrical and Electronic Engineering of the University of Cagliari

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

Jesper Hoffmeyer

University of Copenhagen

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Papers by Sara Sulis

State Estimation and PMUs

Elsevier eBooks, 2016

Power systems are rapidly evolving, and correspondingly control and management systems require mo... more Power systems are rapidly evolving, and correspondingly control and management systems require more reliable and accurate information on the operating conditions of the grids, in order to manage them. This information can be acquired in several ways and can concern different types of data. The possibility of obtaining such information and its relevance is particularly connected to the smart grids (SGs) scenario, for which the knowledge of operating conditions is critical for secure and reliable supply and for full exploitation of the energy resources.

Bayesian approach for distribution system state estimation

Institution of Engineering and Technology eBooks, Oct 20, 2022

To deal with the increasing complexity of distribution networks that are experiencing important c... more To deal with the increasing complexity of distribution networks that are experiencing important changes, due to the widespread installation of distributed generation and the expected penetration of new energy resources, modern control applications must rely on an accurate picture of the grid status, given by the distribution system state estimation (DSSE). The DSSE is required to integrate all the available information on loads and generators power exchanges (pseudomeasurements) with the real-time measurements available from the field. In most cases, the statistical behavior of the measured and pseudomeasured quantities cannot be approximated by a Gaussian distribution. For this reason, it is necessary to design estimators that are able to use measurements and forecast data on power flows that can show a non-Gaussian behavior. In this paper, a DSSE algorithm based on Bayes's rule, conceived to perfectly match the uncertainty description of the available input information, is presented. The method is able to correctly handle the measurement uncertainty of conventional and synchronized measurements and to include possible correlation existing between the pseudomeasurements. Its applicability to medium voltage distribution networks and its advantages, in terms of accuracy of both estimated quantities and uncertainty intervals, are demonstrated.

Sara Sulis

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