Utilization of transmission system data for enhancement and preservation of its secure operation
Date: Tuesday, May 24 Time: 1:30 pm – 3:00 pm (CEST)
Organization: Zurich University of Applied Sciences ZHAW, Switzerland
Short biography of the chair: Rafael Segundo received the PhD degree from Imperial College London, United Kingdom in 2013. From 2007 to 2008, he worked in the Automation and Control group in the Corporate Research Centre of ABB, in Switzerland. From January 2013 to July 2014, Dr Segundo was a postdoctoral research fellow at the school of electrical engineering of the KTH Royal Institute of Technology in Stockholm, Sweden. Since 2014, he is research associate in the Electric Power Systems and Smart Grid Lab at the Zurich University of Applied Sciences in Switzerland. Dr. Segundo is Senior Member of the IEEE, chair of the IEEE Task Force ” Application of Big Data Analytic on Transmission System Dynamic Security Assessment” and chair of the international annual workshop DynPOWER. He is the principal investigator of different projects funded by the Swiss National Science Foundation, the Swiss Federal Office of Energy, Innosuisse and the European Commission. His areas of interest include dynamic stability and control of power systems with low inertia and application of data-driven techniques for transmission system phenomena.
Panel Abstract: Electrical power systems are evolving into low-inertia networks where utilities are staring to face challenges associated to the dramatic increase of inverter connected devices. To support the decision making and consequently reinforce the security of the system, utilities rely more than ever on monitoring infrastructure in order to gain a higher degree of observability in the network. Consequently, the increasing use of high frequency synchronized devices such as Phasor Measurement Units (PMUs) on transmission systems is not only contributing to a more reliable dynamic security assessment but also to introduce additional challenges such as data storage, visualization and data handling. Motivated by this issues, the objective of the panel is to open a forum of discussions associated to alternative solutions in relation to the accuracy of these measurements, incorporation of innovative compression methods, artificial intelligence based solutions for real time implementation, visualization tools to gain situational awareness and emphasize the relevance that the location of the inertia plays with respect to frequency response
Organization: University of Cagliari, Italy
Short biography: Sara Sulis received the M.S. degree in electrical engineering and the Ph.D. degree in industrial engineering from the University of Cagliari, Cagliari, Italy, in 2002 and 2006, respectively. She is currently an Associate Professor of electrical and electronic measurements with the University of Cagliari. She has authored or coauthored more than 100 scientific articles. Her current research interests include distributed measurement systems designed to perform state estimation and harmonic sources estimation of distribution networks. She is an Associate Editor of the IEEE Transactions on Instrumentation and Measurement
Title of presentation: Measurement challenges in low inertia power grids
Abstract: Measurements can be an enabling technology for Smart Grids. For this to happen, the entire measurement chain must guarantee measurements with given accuracy performance also in the presence of dynamic signals. The challenge is therefore to describe the result of the measurement process with a properly evaluated accuracy even in the presence of complex architectures and frequent transients, which will be typical of low inertia power grids. Phasor Measurement Units (PMUs) and Smart Meters are new generation devices expected to spread worldwide for new designed monitoring systems. Nevertheless, the behaviour of these devices in the presence of dynamics must be carefully characterized, particularly if they are fed by traditional instrument transformers. For example, PMU compliance tests are described in the standards also considering dynamics, but the combination of realistic events can induce significantly degraded performance. The presentation will focus on these main aspects and aims at describing a measurement perspective and suggest possible design strategies for a new generation of effective monitoring system.
Organization: University of Santiago de Chile USACH
Short biography: Hector Chavez (Member, IEEE) received the Licenciado, Ingeniero Civil en Electricidad, and Magister degrees in electrical engineering from the University of Santiago, Santiago, Chile, in 2004, 2006, and 2006, respectively, and the Ph.D. degree in electrical engineering from The University of Texas at Austin, Austin, TX, USA, in 2013. In 2013, he was a Postdoctoral Fellow with the Department of Electric Power Systems, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden. From 2006 to 2009, he was an Instrumentation Engineer with WorleyParsons Minerals and Metals, Santiago. He is currently the head of the Department of Electrical Engineering, University of Santiago.
Title of presentation: Power system data-driven, reduced-order models for look ahead frequency analysis
Abstract: The reduction in system inertia and frequency response has increased the need for real time tools to increase control room situation awareness. This talk exposes how data-driven reduced-order models can help real time operation by performing fast frequency stability assessments based on historical data and parameter identification frameworks.
Organization: TU Delft, Netherlands
Short biography: Jochen Cremer is Co-Director of the Delft AI Energy Lab and Assistant Professor Intelligent Electrical power Grids at the Technical University of Delft. His expertise is on AI and ML technology for use cases in energy systems, ranging from demand response, distributed real-time control over centralised coordinated operations in real-time. His novel algorithms can process very large amounts of data and advance energy systems operations from societal, sustainable, and economic perspectives. Before he worked on Machine Learning technology at Imperial College London, control theory at Carnegie Mellon and MIT. He worked in the chemical and energy industry, in China and Germany. He holds an M.Sc. in Chemical Engineering, a B.Sc. in Electrical Engineering, and a B.Sc. in Mechanical Engineering from RWTH Aachen University, Germany. He is member of the IEEE PES Taskforces for Big data processing, members of CIGRE C2 working groups.
Title of presentation: On Dynamics and Artificial Intelligence for Power Systems
Abstract: Power systems must undertake a significant shift toward considering shorter dynamics in operations. Interestingly, the intersection of modelling dynamical systems and AI has experienced significantly progresses in recent years showing interesting synergies. In a bidirectional way, AI can be used to study data from dynamical systems and the theory of dynamical systems can be used to investigate AI. My talk will investigate these synergies and show whether AI becomes more or less suitable with the increase of power-interfaced dynamics introducing coupling effects with very short-time dynamics. I then introduce a method based on artificial neural networks to predict the dynamics with maximized accuracy, suitable for real-time predictions of power system dynamics analyzing PMU data for contingencies
Organization: Norwegian University of Science and Technology, Norway
Short biography: Kjetil Uhlen received the master’s and Ph.D. degrees in control engineering in 1986 and 1994, respectively. He is currently a Professor of power systems with the Norwegian University of Science and Technology, Trondheim, Norway, and a Special Adviser with STATNETT (the Norwegian TSO), Oslo, Norway. His main research and education interests include within control and operation of power systems, grid integration of renewable energy, and power system dynamics.
Title of presentation: Methods for monitoring and presenting modal information in a power system
Abstract: Various methods have been proposed, tested and implemented for identification and characterization of low damped electro-mechanical modes in power systems. This presentation will discuss some of these methods that are mostly based on streaming data from Phasor Measurement Units (PMUs). When critical modes are identified, it is further important how the information is presented to operators. The presentation aims at comparing what information is obtained from different methods and how this information can be visualized and presented to gain situational awareness in an operational setting.
Email:Imperial College London, United Kingdom
Short biography: Dr Luis Badesa is a Research Associate with the Department of Electrical and Electronic Engineering at Imperial College London. His research aims to facilitate a cost-effective integration of renewable energies, developing mathematical models to operate electricity grids and markets efficiently. His main body of work is focused on the economics and stability of low-inertia power grids.
Title of presentation: Regional stability needs in low-inertia power grids
Abstract: As renewable generation replaces thermal plants, system inertia is increasingly scarce. Furthermore, the typically remote location of the best renewable resources creates a non-uniform distribution of inertia across the grid. This effect leads to inter-area oscillations in frequency following a generation outage, therefore frequency can no longer be consider as a system-wide magnitude. In this work we demonstrate that the location of inertia and frequency response is key to guarantee frequency stability. We also highlight the need to move to a regional N-1 reliability requirement, rather than the current practice of system-wide N-1 reliability. This talk is based on a two-part paper recently published in IEEE Transactions on Power Systems