Abstract:
Energy storage units hold promise to transform the electric power industry, since they can supply power to end customers during peak demand times, and operate as customer...Show MoreMetadata
Abstract:
Energy storage units hold promise to transform the electric power industry, since they can supply power to end customers during peak demand times, and operate as customers upon a power surplus. This paper studies online energy management with renewable energy resources and energy storage units. For the problem at hand, the popular approaches rely on stochastic dual (sub)gradient (SDG) iterations for a chosen stepsize μ, which generally require battery capacity O(1/μ) to guarantee an O(μ)-optimal solution. With the goal of achieving optimal energy cost with considerably reduced battery capacity requirements, an online learning-aided management (OLAM) scheme is introduced for energy management, which incorporates statistical learning advances into real-time energy management. To facilitate real-time implementation of the proposed scheme, the alternating direction method of multipliers method is also leveraged to solve the involved subproblems in a distributed fashion. It is analytically established that OLAM incurs an O(μ) optimality gap, while only requiring battery capacity O(log2(μ)/√μ). Simulations on the IEEE power grid benchmark corroborate that OLAM incurs similar average cost relative to that of SDG, while requiring markedly lower battery capacity.
Published in: IEEE Transactions on Smart Grid ( Volume: 10, Issue: 2, March 2019)
Funding Agency:
State Key Laboratory of ASIC and System, Shanghai Institute for Advanced Communication and Data Science, Fudan University, Shanghai, China
Bingcong Li received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University in 2017. He is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and reinforcement learning with applications to cyber physical systems. He was a recipient of the National Scholarship twice from China in 2014 and 2015 and UMN ECE D...Show More
Bingcong Li received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University in 2017. He is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and reinforcement learning with applications to cyber physical systems. He was a recipient of the National Scholarship twice from China in 2014 and 2015 and UMN ECE D...View more
Department of Electrical and Computer Engineering and the Digital Technology Center, University of Minnesota, Minneapolis, MN, USA
Tianyi Chen (S’14) received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University, and the M.Sc. degree in electrical and computer engineering from the University of Minnesota (UMN), in 2014 and 2016, respectively, where he is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and stochastic network optimi...Show More
Tianyi Chen (S’14) received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University, and the M.Sc. degree in electrical and computer engineering from the University of Minnesota (UMN), in 2014 and 2016, respectively, where he is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and stochastic network optimi...View more
State Key Laboratory of ASIC and System, Shanghai Institute for Advanced Communication and Data Science, Fudan University, Shanghai, China
Xin Wang (SM’09) received the B.Sc. and M.Sc. degrees from Fudan University, Shanghai, China, in 1997 and 2000, respectively, and the Ph.D. degree from Auburn University, Auburn, AL, USA, in 2004, all in electrical engineering.
From 2004 to 2006, he was a Post-Doctoral Research Associate with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. In 2006, he joined the Department of Co...Show More
Xin Wang (SM’09) received the B.Sc. and M.Sc. degrees from Fudan University, Shanghai, China, in 1997 and 2000, respectively, and the Ph.D. degree from Auburn University, Auburn, AL, USA, in 2004, all in electrical engineering.
From 2004 to 2006, he was a Post-Doctoral Research Associate with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. In 2006, he joined the Department of Co...View more
Department of Electrical and Computer Engineering and the Digital Technology Center, University of Minnesota, Minneapolis, MN, USA
Georgios B. Giannakis (F’97) received the Diploma degree in electrical engineering from the National Technical University of Athens, Greece, 1981, and the M.Sc. degree in electrical engineering, the M.Sc. degree in mathematics, and the Ph.D. degree in electrical engineering from the University of Southern California in 1983, 1986, and 1986, respectively, where he was from 1982 to 1986. He was with the University of Virgin...Show More
Georgios B. Giannakis (F’97) received the Diploma degree in electrical engineering from the National Technical University of Athens, Greece, 1981, and the M.Sc. degree in electrical engineering, the M.Sc. degree in mathematics, and the Ph.D. degree in electrical engineering from the University of Southern California in 1983, 1986, and 1986, respectively, where he was from 1982 to 1986. He was with the University of Virgin...View more
Contents State Key Laboratory of ASIC and System, Shanghai Institute for Advanced Communication and Data Science, Fudan University, Shanghai, China
Bingcong Li received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University in 2017. He is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and reinforcement learning with applications to cyber physical systems. He was a recipient of the National Scholarship twice from China in 2014 and 2015 and UMN ECE Department Fellowship in 2017.
Bingcong Li received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University in 2017. He is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and reinforcement learning with applications to cyber physical systems. He was a recipient of the National Scholarship twice from China in 2014 and 2015 and UMN ECE Department Fellowship in 2017.View more
Department of Electrical and Computer Engineering and the Digital Technology Center, University of Minnesota, Minneapolis, MN, USA
Tianyi Chen (S’14) received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University, and the M.Sc. degree in electrical and computer engineering from the University of Minnesota (UMN), in 2014 and 2016, respectively, where he is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and stochastic network optimization with applications to smart grids, sustainable cloud networks, and Internet-of-Things. He was in the Best Student Paper Award finalist of the Asilomar Conference on Signals, Systems, and Computers. He was a recipient of the National Scholarship from China in 2013, the UMN ECE Department Fellowship in 2014, and the UMN Doctoral Dissertation Fellowship in 2017.
Tianyi Chen (S’14) received the B.Eng. degree (with Highest Hons.) in communication science and engineering from Fudan University, and the M.Sc. degree in electrical and computer engineering from the University of Minnesota (UMN), in 2014 and 2016, respectively, where he is currently pursuing the Ph.D. degree with UMN. His research interests lie in online learning, online convex optimization, and stochastic network optimization with applications to smart grids, sustainable cloud networks, and Internet-of-Things. He was in the Best Student Paper Award finalist of the Asilomar Conference on Signals, Systems, and Computers. He was a recipient of the National Scholarship from China in 2013, the UMN ECE Department Fellowship in 2014, and the UMN Doctoral Dissertation Fellowship in 2017.View more
State Key Laboratory of ASIC and System, Shanghai Institute for Advanced Communication and Data Science, Fudan University, Shanghai, China
Xin Wang (SM’09) received the B.Sc. and M.Sc. degrees from Fudan University, Shanghai, China, in 1997 and 2000, respectively, and the Ph.D. degree from Auburn University, Auburn, AL, USA, in 2004, all in electrical engineering.
From 2004 to 2006, he was a Post-Doctoral Research Associate with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. In 2006, he joined the Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA, as an Assistant Professor, and then an Associate Professor from 2010. He is currently a Distinguished Professor with the Department of Communication Science and Engineering, Fudan University. His research interests include stochastic network optimization, energy-efficient communications, cross-layer design, and signal processing for communications. He served as an Associate Editor for the IEEE Signal Processing Letters. He currently serves as an Associate Editor for the IEEE Transactions on Signal Processing and as an Editor for the IEEE Transactions on Vehicular Technology.
Xin Wang (SM’09) received the B.Sc. and M.Sc. degrees from Fudan University, Shanghai, China, in 1997 and 2000, respectively, and the Ph.D. degree from Auburn University, Auburn, AL, USA, in 2004, all in electrical engineering.
From 2004 to 2006, he was a Post-Doctoral Research Associate with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. In 2006, he joined the Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA, as an Assistant Professor, and then an Associate Professor from 2010. He is currently a Distinguished Professor with the Department of Communication Science and Engineering, Fudan University. His research interests include stochastic network optimization, energy-efficient communications, cross-layer design, and signal processing for communications. He served as an Associate Editor for the IEEE Signal Processing Letters. He currently serves as an Associate Editor for the IEEE Transactions on Signal Processing and as an Editor for the IEEE Transactions on Vehicular Technology.View more
Department of Electrical and Computer Engineering and the Digital Technology Center, University of Minnesota, Minneapolis, MN, USA
Georgios B. Giannakis (F’97) received the Diploma degree in electrical engineering from the National Technical University of Athens, Greece, 1981, and the M.Sc. degree in electrical engineering, the M.Sc. degree in mathematics, and the Ph.D. degree in electrical engineering from the University of Southern California in 1983, 1986, and 1986, respectively, where he was from 1982 to 1986. He was with the University of Virginia from 1987 to 1998, and since 1999, he has been a Professor with the University of Minnesota, where he holds an Endowed Chair in wireless telecommunications, the University of Minnesota McKnight Presidential Chair in ECE, and serves as the Director of the Digital Technology Center.
His general interests span the areas of communications, networking, and statistical signal processing—subjects on which he has published over 400 journal papers, 700 conference papers, 25 book chapters, two edited books, and two research monographs with an H-index of 128. Current research focuses on learning from big data, wireless cognitive radios, and network science with applications to social, brain, and power networks with renewables. He is the (co-)inventor of 30 patents issued. He was a (co-)recipient of nine best paper awards from the IEEE Signal Processing (SP) and Communications Societies, including the G. Marconi Prize Paper Award in Wireless Communications, the Technical Achievement Awards from the SP Society in 2000 and from EURASIP in 2005, the Young Faculty Teaching Award, the G. W. Taylor Award for Distinguished Research from the University of Minnesota, and the IEEE Fourier Technical Field Award in 2015. He is a fellow of EURASIP, and has served the IEEE in a number of posts, including that of a Distinguished Lecturer for the IEEE-SP Society.
Georgios B. Giannakis (F’97) received the Diploma degree in electrical engineering from the National Technical University of Athens, Greece, 1981, and the M.Sc. degree in electrical engineering, the M.Sc. degree in mathematics, and the Ph.D. degree in electrical engineering from the University of Southern California in 1983, 1986, and 1986, respectively, where he was from 1982 to 1986. He was with the University of Virginia from 1987 to 1998, and since 1999, he has been a Professor with the University of Minnesota, where he holds an Endowed Chair in wireless telecommunications, the University of Minnesota McKnight Presidential Chair in ECE, and serves as the Director of the Digital Technology Center.
His general interests span the areas of communications, networking, and statistical signal processing—subjects on which he has published over 400 journal papers, 700 conference papers, 25 book chapters, two edited books, and two research monographs with an H-index of 128. Current research focuses on learning from big data, wireless cognitive radios, and network science with applications to social, brain, and power networks with renewables. He is the (co-)inventor of 30 patents issued. He was a (co-)recipient of nine best paper awards from the IEEE Signal Processing (SP) and Communications Societies, including the G. Marconi Prize Paper Award in Wireless Communications, the Technical Achievement Awards from the SP Society in 2000 and from EURASIP in 2005, the Young Faculty Teaching Award, the G. W. Taylor Award for Distinguished Research from the University of Minnesota, and the IEEE Fourier Technical Field Award in 2015. He is a fellow of EURASIP, and has served the IEEE in a number of posts, including that of a Distinguished Lecturer for the IEEE-SP Society.View more
