TY - JOUR
T1 - Cyber-enabled grids
T2 - Shaping future energy systems
AU - Pong, Philip W.T.
AU - Annaswamy, Anuradha M.
AU - Kroposki, Benjamin
AU - Zhang, Yingchen
AU - Rajagopal, Ram
AU - Zussman, Gil
AU - Poor, H. Vincent
N1 - Funding Information:
Prof. Gil Zussman: Gil Zussman received the B.Sc. degree in Industrial Engineering and Management and the B.A. degree in Economics (both summa cum laude) from the Technion – Israel Institute of Technology in 1995. He received the M.Sc. degree (summa cum laude) in Operations Research from Tel-Aviv University in 1999 and the Ph.D. degree in Electrical Engineering from the Technion – Israel Institute of Technology in 2004. Between 1995 and 1998, he served as an engineer in the Israel Defense Forces. Between 2004 and 2007 he was a Postdoctoral Associate in LIDS and CNRG at MIT. Since 2007 he has been with Columbia University where he is now a Professor of Electrical Engineering and Computer Science (affiliated faculty). Between 2014 and 2016 he was a Visiting Scientist in the School of Computer Science in Tel Aviv University. His-research interests are in the area of networking, and in particular in the areas of wireless, mobile, and resilient networks. He has been an associate editor of IEEE/ACM Transactions on Networking, IEEE Transactions on Control of Network Systems, IEEE Transactions on Wireless Communications, and Ad Hoc Networks, the Technical Program Committee (TPC) co-chair of ACM MobiHoc’15 and IFIP Performance 2011, and a member of a number of TPCs (including the INFOCOM, MobiCom, SIGMETRICS, and MobiHoc committees). Gil received the Knesset (Israeli Parliament) award for distinguished students, the Marie Curie Outgoing International Fellowship, the Fulbright Fellowship, the DTRA Young Investigator Award, the NSF CAREER Award, and the Marie Curie International Incoming Fellowship. He was the PI of a team that won the 1st place in the 2009 Vodafone Americas Foundation Wireless Innovation Project competition. He is a co-recipient of seven best paper awards, including the ACM SIGMETRICS / IFIP Performance’06 Best Paper Award, the 2011 IEEE Communications Society Award for Advances in Communication, and the ACM CoNEXT’16 Best Paper Award.
Funding Information:
Dr. Anuradha Annaswamy: Dr. Anuradha Annaswamy received her Ph.D. in Electrical Engineering from Yale University in 1985. She has been a member of the faculty at Yale, Boston University, and MIT where currently she is the director of the Active-Adaptive Control Laboratory and a Senior Research Scientist in the Department of Mechanical Engineering. Her research interests pertain to adaptive control theory and applications to aerospace, automotive, and propulsion systems, cyber physical systems science, and CPS applications to Smart Grids, Smart Cities, and Smart Infrastructures. She is the author of a hundred journal publications and numerous conference publications, co-author of a graduate textbook on adaptive control (2004), co-editor of several reports including “Systems & Control for the future of humanity, research agenda: Current and future roles, impact and grand challenges,” (Elsevier) “IEEE Vision for Smart Grid Control: 2030 and Beyond,” (IEEE Xplore) and Impact of Control Technology, (ieeecss.org/main/IoCT-report, ieeecss.org/general/IoCT2-report). Dr. Annaswamy has received several awards including the George Axelby and Control Systems Magazine best paper awards from the IEEE Control Systems Society (CSS), the Presidential Young Investigator award from NSF, the Hans Fisher Senior Fellowship from the Institute for Advanced Study at the Technische Universität München, the Donald Groen Julius Prize from the Institute of Mechanical Engineers, a Distinguished Member Award, and a Distinguished Lecturer Award from IEEE CSS. Dr. Annaswamy is a Fellow of the IEEE and IFAC. She has served as the Vice President for Conference Activities (2014–15), and is currently serving as the VP for Technical Activities (2017–18) in the Executive Committee of the IEEE CSS.
Funding Information:
We would like to acknowledge the support by the Seed Funding Program for Basic Research , the Seed Funding Program for Applied Research , and the Small Project Funding Program from The University of Hong Kong , the ITF Tier 3 Funding under Grant ITS/203/14 , Grant ITS/104/13 , and Grant ITS/214/14 , by RGC-GRF under Grant HKU 17204617 , and by the University Grants Committee of Hong Kong under Contract AoE/P-04/08 . HVP would like to acknowledge the support from the U.S. National Science Foundation (NSF) under Grants DMS-1736417 and ECCS-1824710 . AMA would like to acknowledge the support from the US NSF under the CPS grant 1932406. GZ's work was supported in part by the U.S. Department of Energy (DOE) EERE under the SETO ASSIST Initiative award number DE-EE0008769. This work was supported in part by the National Renewable Energy Laboratory , operated by Alliance for Sustainable Energy, LLC, for the U.S. DOE under Contract No. DE-AC36-08GO28308 . The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government.
Publisher Copyright:
© 2021
PY - 2021/2/23
Y1 - 2021/2/23
N2 - As the penetration of distributed energy resources based on renewable sources increases, several technical challenges are introduced into energy grids. These include real-time power balance, control of bi-directional energy flow, power quality, distributed optimization, state estimation and topology estimation in distribution grids, and multi-level electricity trading. To overcome these challenges and to create situational awareness in energy grids, pervasive sensing becomes essential. To overcome hurdles such as implementation and cost of such pervasive sensing, in addition to traditional contact-sensing methods, contactless sensors that can measure key variables in the grid needs to be leveraged. Contactless sensing enables measurement of process variables that may be hard to measure due to technological limitations of contact sensing, large measurement delays, or high costs. In addition to contactless sensing, pervasive sensing proves advantageous as it can leverage ongoing technological advances in Internet of Things (IoT), as they can lead to enhanced network connectivity between sensors as well as between the edge and the cloud. Finally, pervasive sensing proves even more attractive by integrating contactless sensing not only with wireless communication but also with shielding and energy harvesting. This paper reviews pervasive sensing techniques in power grids that encompass contactless sensing technologies, IoT connectivity, energy harvesting and shielding. In addition, we also explore how pervasive sensing in a Cyber-Enabled Grid (CEG) can contribute to the development roadmap of Autonomous Energy Grids (AEGs), a futuristic concept where the grid will be making automated operational decisions. The potential challenges and research opportunities in this pioneering research field such as data deluge, cybersecurity, and sensor fusion will be discussed. This review article, which addresses the role of pervasive sensing in CEGs, is a first of its kind. It will help engineers and scientists to understand its significant potential to shape future energy systems.
AB - As the penetration of distributed energy resources based on renewable sources increases, several technical challenges are introduced into energy grids. These include real-time power balance, control of bi-directional energy flow, power quality, distributed optimization, state estimation and topology estimation in distribution grids, and multi-level electricity trading. To overcome these challenges and to create situational awareness in energy grids, pervasive sensing becomes essential. To overcome hurdles such as implementation and cost of such pervasive sensing, in addition to traditional contact-sensing methods, contactless sensors that can measure key variables in the grid needs to be leveraged. Contactless sensing enables measurement of process variables that may be hard to measure due to technological limitations of contact sensing, large measurement delays, or high costs. In addition to contactless sensing, pervasive sensing proves advantageous as it can leverage ongoing technological advances in Internet of Things (IoT), as they can lead to enhanced network connectivity between sensors as well as between the edge and the cloud. Finally, pervasive sensing proves even more attractive by integrating contactless sensing not only with wireless communication but also with shielding and energy harvesting. This paper reviews pervasive sensing techniques in power grids that encompass contactless sensing technologies, IoT connectivity, energy harvesting and shielding. In addition, we also explore how pervasive sensing in a Cyber-Enabled Grid (CEG) can contribute to the development roadmap of Autonomous Energy Grids (AEGs), a futuristic concept where the grid will be making automated operational decisions. The potential challenges and research opportunities in this pioneering research field such as data deluge, cybersecurity, and sensor fusion will be discussed. This review article, which addresses the role of pervasive sensing in CEGs, is a first of its kind. It will help engineers and scientists to understand its significant potential to shape future energy systems.
KW - Contactless sensing
KW - Cyber-enabled grid
KW - Energy grid
KW - Energy harvesting
KW - Internet of things
KW - Pervasive sensing
KW - Shielding
UR - http://www.scopus.com/inward/record.url?scp=85106658164&partnerID=8YFLogxK
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U2 - 10.1016/j.adapen.2020.100003
DO - 10.1016/j.adapen.2020.100003
M3 - Review article
AN - SCOPUS:85106658164
SN - 2666-7924
VL - 1
JO - Advances in Applied Energy
JF - Advances in Applied Energy
M1 - 100003
ER -