IoT Thrust Seminar


Energy Sharing: New Business Model for Electric Internet of Things

2:00pm - 3:00pm
Meeting ID: 945 0964 6939, Passcode: 386012

The proliferation of distributed energy resources and the integration of multiple energy carriers are reshaping our energy system from a highly regulated, operator-controlled network into a sophisticated Electric Internet of Things. This leads to two-side unpredictability in both uncertain renewable sources and more random user behaviours, leaving a large number of idle resources and unmet loads simultaneously. Therefore, an innovative paradigm that can unlock the unexplored flexibility in the energy network is desired. One successful business model with a similar initiative is the sharing economy in other sectors. Inspired by that, I explore the potential of energy sharing by answering why, how, and what if. For why, three typical approaches, i.e., self-sufficiency, sharing, centralized operation, are compared under a stochastic framework, and sharing stands out for the fact that it can achieve a nearly social optimal efficiency in a distributed manner. For how, I design effective mechanisms for sharing among node-level and networked prosumers, respectively. Several desirable properties of the sharing market equilibrium are proved theoretically. I also develop a bidding process for implementation with proof of its convergence under mild conditions. For what if, a two-stage robust economic dispatch problem is used as an example by replacing the centralized real-time operation with a distributed sharing scheme. I prove that the flexibility of the system is retained with only a slight sacrifice of the economy. These works reveal fundamental understandings that facilitate in-depth analyses of the future energy sharing market.

Event Format
Speakers / Performers:
Dr. Yue CHEN
IoT Thrust’s Junior Faculty Candidate

Yue Chen received her B.E. (2015) and Ph.D. (2020) degrees in Electrical Engineering from Tsinghua University (THU), China, and her B.S. (2017) degree in Economics from Peking University, China. Her Ph.D. advisors are Prof. Qiang Lu and Prof. Shengwei Mei. She was awarded as the Outstanding Graduates and Excellent Thesis for both Bachelor and Ph.D.  From 2018 to 2019, Yue was a visiting student at California Institute of Technology (Caltech) working with Prof. Steven H. Low. She was the recipient of Stanford Bits & Watts postdoc fellowship, 2019 IEEE Transactions on Smart Grid Best Reviewer Award, and was selected as the 2020 Rising Stars in Electrical Engineering and Computer Science (EECS) by UC Berkeley and in Civil and Environmental Engineering (CEE) by Carnegie Mellon University. Broadly, her research interests include smart cities, sustainable energy, transactive energy, and integrated energy systems based on optimization, algorithmic game theory, and mathematical economics.

Recommended For
Faculty and staff
PG students
Department of Electronic & Computer Engineering
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