IEEE / UBC ECE Communications Seminar

When:
29 September 2017 @ 11:00 – 12:00
2017-09-29T11:00:00-07:00
2017-09-29T12:00:00-07:00
Where:
Room 418, Macleod Building, UBC
Macleod Bldg
2356 Main Mall, Vancouver, BC V6T 1Z4
Canada
Cost:
Free
Contact:
Vincent Wong
IEEE / UBC ECE Seminar, co-sponsored by the IEEE Vancouver Joint Communications Chapter.
 
Title: Gaussian Residual Bidding-based Coalitional Framework for Renewable Energy Market
Presented by:  Prof. Hongseok Kim, Sogang University, Korea

Date and time:  Friday, September 29, at 11 am

Location: Room 418, Macleod Building, UBC, 2356 Main Mall, Vancouver

Abstract: To stabilize output variability of distributed renewable energy sources (RESs), integrating large-scale RESs is highly utilized, and aggregated RESs are treated almost as any other conventional generators in existing electricity markets. In this talk we first propose a coalitional framework to cope with the uncertainty of RESs when RES owners can participate in a wholesale electricity market as sellers, where a market operator financially penalizes RES owners for deviations between day-ahead and real-time markets. Our theoretical approach incentivizes participants in a coalition by mitigating penalty fees caused by renewable variability. Furthermore, we propose a bidding strategy called Gaussian residual bidding (GRB) to maximize a coalition gain of participants. We prove that the considered game is convex game when GRB is used for all participants. Our extensive simulations with real data demonstrate that the proposed bidding strategy combined with the coalitional framework outperforms other bidding strategies as well as non-coalition cases under various market scenarios. Our results exhibit the revenue of GRB is improved up to 200% compared to the existing empirical quantile bidding and forecast bidding strategies.

Biography:  Dr. Hongseok Kim is an Associate Professor at Sogang University, Seoul, Korea. He received the B.S. and M.S. degrees in electrical engineering from Seoul National University, Seoul, South Korea, in 1998 and 2000, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Texas at Austin, Austin, TX, USA, in 2009. From 2000 to 2005, he was a Member of the Technical Staff in Korea Telecom Labs. From 2009 to 2010, he was a Postdoctoral Research Associate in the Department of Electrical Engineering, Princeton University, Princeton, NJ, USA, and from 2010 to 2011, as a Member of technical staff in Bell Labs, Murray Hill, NJ, USA. His research interests include resource allocation, optimization and machine learning with applications to smart grid and wireless networks such as optimal power flow, microgrid, energy storage and battery management system, load and renewable prediction, power economics, 5G wireless system with renewables, green communications, scheduling in MAC layer, etc.