Biography: Professor Om P. Malik has done pioneering work in the development of controllers for application in electric power systems and wind power generation over the past 45 years. After extensive testing, the adaptive controllers developed by his group are now employed on large generating units. His other interests include digital protection, control of renewable power generation and micro-grids, and AI applications in power system control. He has published over 700 papers including over 360 papers in international Journals and is the coauthor of two books. Professor Malik graduated in 1952 from Delhi Polytechnic. After working for nine years in electric utilities in India, he obtained a Master’s Degree from Roorkee University in 1962, a Ph.D. from London University and a DIC from the Imperial College, London in 1965. He was teaching and doing research in Canada from 1966 to 1997 and continues to do research as Professor Emeritus at the University of Calgary. Over 100, including 45 Ph.D., students have graduated under his supervision. Professor Malik is a Life Fellow of IEEE, and a Fellow of IET, the Engineering Institute of Canada, Canadian Academy of Engineering, Engineers Canada and World Innovation Foundation. He is a registered Professional Engineer in the Provinces of Alberta and Ontario, Canada, and has received many awards. He was Director, IEEE Region 7 and President, IEEE Canada during 2010-11 and President, Engineering Institute of Canada, 2014-2016.
Title of Speech: Embracing Emerging Technologies: The Key to Advances in Power Systems
Abstract: Starting from very humble beginnings in 1882, energy in the form of electric energy has become indispensable in the 21st. century. Its use has infiltrated every aspect of human activity, and it will be no exaggeration to say in the context of the present world that, if electricity were not available, every aspect of human activity will be adversely affected, if not come to a stop.
Keeping pace with the continued increase in the use and thus the demand of energy in the form of electrical energy has been accomplished by continued developments in power systems. This has led to big evolution in the development of power systems as power systems engineers have always kept pace by embracing new enabling technologies as they developed. Power systems still continue to evolve as the demand for electricity continues to grow.
After a brief review of the progress in power systems over the past 135 years, a quick discussion of the current status of the power system technology is provided.
With the power systems continuing to grow, more advances are imminent as is evident from the current buzz around the ‘smart grid’ concept. Areas that need more attention and are expected to draw significant attention over the near future include integration of advanced communications, information technologies, control and other enabling technologies. The way forward in the evolution of future power systems into smarter grids is outlined.
Biography: Dennis Lieu is a Professor of Mechanical Engineering and former Associate Dean of the College of Engineering at UC Berkeley. He received his BS, MS and D.Eng. in Mechanical Engineering from UC Berkeley in 1977, 1978 and 1982, respectively. After working for six years as a design engineer in industry, he returned to his alma mater and has been a member of its faculty for 30 years. He is the author or co-author of numerous articles on permanent magnet motor design and engineering graphics education, and is the lead author of Visualization, Modeling, and Graphics for Engineering Design (Cengage Publishers). His research interests are in the design of electro-mechanical devices and the design of sports equipment. He is a recipient of the UC Berkeley Distinguished Teaching Award. In 2008, he was awarded the Orthogonal Medal for his contributions to engineering graphics education. In 2015, he received the Distinguished Service Award from the Engineering Design Graphics Division of the ASEE. Prof. Lieu is currently engaged in the development of design courseware associated with the new Jacobs Design Institute at UC Berkeley.
Title of Speech: Kinetic Energy Storage and Recovery for Hybrid Vehicles
Abstract: The transportation sector accounts for 28 percent of American greenhouse gas emission, the most after power plants. Increased vehicle efficiency, both commercial and consumer, will almost certainly play a critical role. With increased fuel efficiency, transportation could reduce carbon dioxide emissions in the near future. Government regulations and federal policies have been an important driver in this change. The 2010 mandate requiring a doubling of new-car average fuel economy by 2025 has pushed industry to accelerate the development of more efficient cars. As governments realize the economic and societal needs for energy efficient automobiles, the adoption of new technologies depends on mainstream consumer acceptance. Consumer and commercial users are, for example, increasingly accepting fuel-efficient hybrid vehicles. Although these technologies offer a cleaner and more energy efficient alternative to traditional petroleum-fueled vehicles, general acceptance of these technologies is hindered by their premium price, limited travel range, and extended charging times, which are all consequences of current battery technologies. To address these problems, Kinetic Energy Recovery Systems (KERS) incorporates a mechanical flywheel energy storage system into PEVs and HEVs to increase overall system efficiency, extend battery life, and extend travel range. Ultimately, the increased appeal of PEVs and HEVs through the addition of KERS systems serves to accelerate general acceptance of cleaner and more energy efficient automobiles. This presentation will explore the short and long term markets for KERS in specific industries by geographic area.
Biography: A. R. Al-Ali (SM IEEE) received his Ph.D. in electrical engineering and a minor in computer science from Vanderbilt University, Nashville, TN, USA, 1990; Master degree from Polytechnic Institute of New York, USA, 1986 and B.Sc.EE from Aleppo University, Syria, 1979. From 1991–2000, he worked as an associate/assistant professor in KFUPM, Saudi Arabia. Since 2000 and till now, he has been a professor of computer science and engineering at the American University of Sharjah, UAE. His research and teaching interests include: embedded systems hardware and software architectures, smart homes automations, smart grid evolutions and development, smart factories and cities. Dr. Al-Ali has more than 100 conference and journal publications including two USA and European Patents. Professor Al-Ali has been invited to deliver keynote speeches on the recent evolution and development in internet of things, cyber physical systems, smart grid and smart cities in several local and international conferences (Https://Www.Aus.Edu/Faculty/Dr-Abdulrahman-Al-Ali)
Title of Speech: Smart Manufacturing Enabling Technologies in Smart City
Abstract: Nowadays, the smart city concept is rolling from conceptual model to real-time deployment in many applications such as smart energy, smart grid, smart health, smart transportation, smart buildings, smart manufacturing and smart factories. All these applications consist of physical objects, products, systems, processes and/or services that are interconnected and exchanged data via the internet. Digital twin’s and virtual twin’s concepts have emerged as a smart city applications enabling technologies that complements its physical object, product and services.
A smart object, product, system and/or process consists of a physical part, and its complementing counterpart digital part as well as its virtual part (model). Digital twin collects its physical object/product real-time parameters status along with the surrounding environment parameters. Those collected data are transmitted via communication networks to the virtual model that can be managed by data analytics software tools that are hosted in a cloud-based or enterprise computing centers for data processing and decisions. The decisions are made based on the aggregated parameters that are stored in the product virtual model. The product’s aggregated parameters may consist of its bill of material, 2D and 3D models, the historical data that were already stored in virtual model. Data processing, analyzing and mining algorithms are implemented for the purposes of early warning, schedules and predictions, dynamic optimization, visualization and action on the physical object.
This talk will present the smart manufacturing enabling technologies including digital and virtual twins’ conceptual model, their benefits and applications in consumers and industrial services.
Biography: Anurag K. Srivastava is an associate professor of electric power engineering at Washington State University and the director of the Smart Grid Demonstration and Research Investigation Lab (SGDRIL) within the Energy System Innovation Center (ESIC). He received his Ph.D. degree in electrical engineering from the Illinois Institute of Technology in 2005. In past years, he has worked in different capacity at the Réseau de transport d´électricité in France; RWTH Aachen University in Germany; PEAK RC, Idaho National Laboratory, Pacific Northwest National Lab, PJM Interconnection, Schweitzer Engineering Lab (SEL), GE Grid Solutions, Massachusetts Institute of Technology and Mississippi State University in USA; Indian Institute of Technology Kanpur in India; as well as at Asian Institute of Technology in Thailand. His research interest includes data-driven algorithms for power system operation and control including resiliency analysis. Dr. Srivastava high impact research projects resulted in tools installed at the utility control center supported for more than $50M by US Department of Energy, National Science Foundation, Siemens Corporate Research, Electric Power Research Institute, Schweitzer Engineering Lab, Power System Engineering Research Center, Office of Naval Research and several National Labs. He is a senior member of the IEEE, vice-chair of the IEEE Power & Energy Society’s (PES) PEEC committee, co-chair of the microgrid working group, secretary of power system operation SC, chair of PES voltage stability working group, and chair of PES synchrophasors applications working group. He organized NSF sponsored “Data analytics workshop for the power grid resiliency” in 2018, Siemens sponsored “data analytics for the smart grid” workshop in 2017, North American Power Symposium in 2014, and IEEE sponsored workshop on Testing and validation of synchrophasor devices and applications in 2012. Dr. Srivastava is an editor of the IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, IEEE Transactions on Industry Applications, and Elsevier Sustainable Computing. He is an IEEE distinguished lecturer and has delivered 30+ keynotes/ tutorials around the world. He is author of more than 300 technical publications including a book on power system security and 3 patents.
Title of Speech: Data-Driven Resilient Operation and Control of the Cyber-Physical Electric Grid
Abstract: Keeping the power on especially to the critical facilities such as hospitals and fire department during extreme adverse operating scenarios is essential. Recent events such as Ukraine attack and Hurricane Maria has exposed the vulnerabilities of the cyber-physical electric grid against extreme events. There is a need for a flexible and resilient grid to minimize the impact of component failures given adverse events. Data from massive sensors deployment and availability of distributed resources enables new monitoring and control strategies such as early alarm and diagnosis, event classifications, predicative analysis, distributed and decentralized control, flexible and adaptive control for restoration. Phasor measurement units (PMUs) provide enhanced situational awareness and decision support in transmission systems. Distribution automation, microPMU and smart meters enables advanced visibility of distribution network. Big data is generated and monitored ubiquitously in the cyber-physical electric grids, but largely unexploited in discovering knowledge and new solutions for critical power grid applications. Robust data analytics solutions including data science and machine learning are critical towards the optimized operation to enhance the resiliency of the electric grid. Availability of additional sensor data brings its own challenges including data anomalies, real time processing and cyber-security management. This talk will focus on real time data analytics to enhance situational awareness and decision support for enabling resiliency of the cyber-physical electric power grid and associated challenges and opportunities.