Distribution-Level PMUs and their Applications
Date: Monday, May 24 Time: –
Abstract: The visibility of the transmission grid have been transformed over the past decade with the deployment of phasor measurement units (PMUs). Similar new information sources are now becoming available at the distribution grid, by using distribution-level PMUs (D-PMUs), also called micro-PMUs. D-PMUs provide voltage and current measurements at higher resolution and precision to facilitate a level of visibility into the distribution grid that was previously not achievable. In this tutorial we will discuss the latest advancements, industry applications, and standardization efforts in the area of synchrophasor measurements in power distribution systems. The tutorial will take 2.5 hours. It will be presented by four speakers. The presentations will discuss the following subjects: 1) data-driven analysis of events in power distribution synchrophasors; 2) D-PMU-based situational awareness systems for the monitoring, protection and control of active distribution networks; 3) Field Implementation of micro-PMU and deep graph learning for real-time event identification; and 4) performance requirements for Distribution systems. Several examples based on real-world field implementations of D-PMus will be discussed.
Name and title of the organizer: Professor Hamed Mohsenian-Rad
Organisation: University of California, Riverside, USA
Name: Hamed Mohsenian-Rad
Organisation: University of California, Riverside, USA
Title: Data-Driven Analysis of Events in Power Distribution Synchrophasors
Abstract: Synchrophasor measurements offer an unprecedented level of visibility in power distribution infrastructure. These are time-synchronized single-phase or three-phase voltage and current phasor measurements on medium and low voltage distribution circuits. However, data availability alone is not enough to enhance operational intelligence. In this talk, we make the case that the analysis of “events” is a key to translate the data from distribution synchrophasors into useful high-level information. An event in this study is defined rather broadly to include any major change in any component across the distribution feeder. The real data that is used in this study is obtained from a pilot distribution feeder in Riverside, CA. The goal is to enhance situational awareness in distribution grid by keeping track of the operation (or misoperation) of various grid equipment, assets, distribution energy resources, loads, etc. A combination of data-driven machine learning tools and hybrid model-based methodologies are discussed to automatically (and often remotely) detect, classify, and identify the causes of events and their characteristics in power distribution systems. Use cases are diverse and may include asset monitoring, non intrusive load modeling, analysis of system dynamics, cybersecurity, etc.
Short biography of the prezenter: Dr. Hamed Mohsenian-Rad is a Professor of Electrical and Computer Engineering and a Bourns Family Faculty Fellow at the University of California, Riverside. His research interests include developing datadriven and model-based techniques for monitoring, control, and optimization of power systems and smart grids. He has received the NSF CAREER Award, a Best Paper Award from the IEEE Power and Energy Society General Meeting, and a Best Paper Award from the IEEE Conference on Smart Grid Communications. Two of his papers are currently ranked as the two most cited articles in the IEEE Transactions on Smart Grid. Dr. Mohsenian-Rad is the Director of the UC-National Lab Center for Power Distribution Cyber Security, a cyber-security research initiative across four University of California campuses and two DoE National Labs. He also serves as the Associate Director of the Winston Chung Global Energy Center, an endowed research center in the area of energy and sustainability at UC Riverside. He has served as the PI for over $10 million smart grid research projects. He received his Ph.D. in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada in 2008. Dr. Mohsenian-Rad is a Fellow of the IEEE
Name: : Mario Paolone
Organisation: École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Title: PMU-based situational awareness systems for the monitoring, protection and control of active distribution networks
Abstract: : In the operation of power transmission systems, the knowledge of the system state, or state estimation (SE), is required by several fundamental functions, such as security assessment, voltage control and stability analysis. Traditionally, the SE has been performed at a relatively low refresh rate of a few minutes, dictated by the time requirements of the related functions together with the low measurement acquisition rate of remote terminal units (RTUs). Nowadays, the emerging availability of phasor measurement units (PMUs) allows to acquire accurate and time-aligned phasors, known as synchrophasors, with typical streaming rates in the order of tens of measurements per second. This technology is experiencing a fast evolution, which is triggered by an increasing number of power system applications that can benefit from the use of synchrophasors. SE processes can exploit the availability of synchrophasor measurements to achieve better accuracy performance and higher refresh rate (subsecond). PMUs already compose the backbone of wide area monitoring systems in the context of power transmission networks to which several real-time functionalities are connected, such as inter-area oscillations, relaying, fault location and real-time SE. However, PMU-driven situational awareness systems may represent a fundamental monitoring tool even in the context of distribution networks for applications such as: SE, grid-aware optimal power flow controls, fault identification and location, synchronous islanded operation. In this respect, the lecture illustrates fundamental methodological aspects for the development of PMU-based situational awareness systems for the monitoring, protection and control of active distribution networks.
Short biography of the presenter: Prof. Dr. Mario Paolone received the M.Sc. (with Hons.) and Ph.D. degrees in electrical engineering from the University of Bologna, Italy, in 1998 and 2002, respectively. In 2005, he was appointed Assistant Professor in power systems with the University of Bologna, where he was with the power systems laboratory until 2011. In 2010, he received the Associate Professor eligibility from the Polytechnic of Milan, Italy. Since 2011, he joined the Swiss Federal Institute of Technology, Lausanne, Switzerland, where he is currently Full Professor, Chair of the Distributed Electrical Systems Laboratory, Head of the Swiss Competence Center for Energy Research Future Swiss Electrical infrastructure and Chair of the EPFL Energy Centre Directorate. He has authored or co-authored over 300 papers published in mainstream journals and international conferences in the area of energy and power systems. His research interests focus on power systems with particular reference to real-time monitoring and operation aspects, power system protections, dynamics and transients. Dr. Paolone was the founder Editor-in-Chief of the Elsevier journal Sustainable Energy, Grids and Networks.
Name: Ken Martin
Organisation: Electric Power Group, USA
Title: PMU standardization: performance requirements for Distribution systems
Abstract: : Phasor measurement system operation and performance has been standardized since 1995. The current standard for synchrophasor measurement unit (PMU) performance is IEC/IEEE 60255-118-1, jointly created by the IEC and the IEEE. It includes both steady-state and dynamic measurement aspects of phasors, frequency, and rate of change of frequency (ROCOF). Elements for this standard have been mostly drawn from transmission system applications, though the standard is not specifically targeted for transmission. PMU use in distribution systems is growing and there is concern that this standard does not adequately address the needs for distribution applications. This talk will review the current standard requirements and discuss the changes that may be needed and the impacts of these changes.
Short biography of the presenter: Ken Martin is a Synchrophasor Technology Leader and Senior Principal Engineer. Ken has over 30 years of experience in the electric utility industry. He has extensive experience with SCADA and timesynchronized phasor data collection and use, including collection, system communications, system architecture and design, and applications for protection, control, monitoring, data management and display. Ken’s work covers instrumentation and measurement systems for research, test, validation and controls.
Name: Zhaoyu Wang
Organisation: Iowa State University, USA
Title: Field Implementation of MicroPMU and Deep Graph Learning for Real-Time Event Identification
Abstract: This talk will introduce field implementation experience of microPMUs at an Iowa distribution utility, including the setup of sensors, communication, and data collection. Then we will discuss how to leverage PMU data to identify events. In particular, we will address PMU data quality issues using a spatial pyramid pooling (SPP)-aided convolutional neural network (CNN). Then we will present a deep graph learning-based event identification method using measurements from multiple PMUs. Unlike previous methods that rely on a single PMU and ignore the interactions between different PMUs, the new method performs data-driven interactive graph inference. Meanwhile, to ensure the optimality of the graph learning procedure, our method learns the interactive graph jointly with the event identification model. Moreover, instead of generating a single statistical graph to represent pair-wise relationships in different events, our approach produces event-specific graphs, which handles the uncertainty of event locations.
Short biography of the presenter: Dr. Zhaoyu Wang is the Harpole-Pentair Assistant Professor with Iowa State University. He received the B.S. and M.S. degrees in electrical engineering from Shanghai Jiaotong University in 2009 and 2012, respectively, and the M.S. and Ph.D. degrees in electrical and computer engineering from Georgia Institute of Technology in 2012 and 2015, respectively. He was a Research Aid at Argonne National Laboratory in 2013 and an Electrical Engineer Intern at Corning Inc. in 2014. His research interests include optimization and data analytics in power distribution systems and microgrids. He is the Principal Investigator for a multitude of projects focused on these topics and funded by the National Science Foundation, the Department of Energy, National Laboratories, PSERC, Iowa Energy Center, and Industry. Dr. Wang received the IEEE PES Outstanding Young Engineer Award in 2020, PES General Meeting Best Paper Award in 2017 and 2019, and the IEEE Industrial Application Society Prize Paper Award in 2016. Dr. Wang is the Secretary of IEEE Power and Energy Society (PES) Award Subcommittee, Co-Vice Chair of PES Distribution System Operation and Planning Subcommittee, and Vice Chair of PES Task Force on Advances in Natural Disaster Mitigation Methods. He is an editor of IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Open Access Journal of Power and Energy, IEEE PES Letters, and IET Smart Grid..