S4 Demand Response and Dynamic Pricing

Symposium Co-Chairs

  • Jianwei Huang, The Chinese University of Hong Kong, China
  • Javad Lavaei, Columbia University, USA
  • Damien Ernst, University of Liege, Belgium
  • Maher Chebbo, SAP, France

Scope and Motivation

By changing their instantaneous consumption in response to grid-level conditions, electricity loads have the potential to improve the efficiency, flexibility and cost to operate power systems. Load responsiveness can be elicited by broadcasting a “dynamic” price to loads, where that price contains information about current grid conditions and at a minimum increases with scarcity of supply. Alternatively, loads can be made responsive by having a system operator or third party aggregator directly control their operation. Whereas dynamic pricing relies on decentralized decisionmaking, direct control of loads is a more centralized process in which loads must be aggregated and coordinated in a manner that achieves grid objectives but simultaneously provides adequate service to end-users.
If we are to ultimately understand and capture the complete potential of the demand side in power system operations, we need (1) models of load aggregations that are useful to system operators and aggregators, (2) models of loads that can be used for local decision-making, (3) control and optimization tools for local decisions or system-level control, (4) frameworks to understand the system-level and device-level implications of decentralized and centralized coordination schemes, (5) joint understanding of the demand side and the generation side management especially with renewable energy integrations, (6) new architectures and hardware in all parts of the system, but especially at the loads themselves.

Topics of Particular Interest

The symposium aims to focus on theoretical, experimental and proof-of-concept results of research and innovation in the areas above. Example topics of interest include, but are not limited to
  • Empyrical analysis of pricing/control mechanisms for demand side management
  • Modeling residential, commercial, and industrial consumer behavior
  • Autonomous and frequency-responsive demand side management
  • Aggregation frameworks and mechanism design
  • Communication architecture and hardware to support demand side management
  • Smart grid services provided by demand side resources
  • PHEV charging and vehicle-to-grid systems
  • The investment and pricing of renewable energy sources
  • Analysis of responsive loads that consider protection, reliability, and voltage control in distribution networks
  • Market impact on smart grid performance (e.g., retail competition, dynamic pricing & demand response, impact of wholesale market competition)
  • Generation, load, and price forecasting in deregulated markets

Technical Program Committee (TPC) Members

Maher Chebbo, SAP, France
Chi-Yung Chung, Hong Kong Polytechnic University, Hong Kong
Emiliano Dall'Anese, University of Minnesota, USA
Florian Dorfler, University of California Los Angeles, USA
Lingjie Duan, Singapore University of Technology and Design (SUTD), Singapore
Damien Ernst, University of Liège, Belgium
Javier Fonollosa, Universitat Polit
ècnica de Catalunya, Spain
Nikolaos Gatsis, The University of Texas at San Antonio, USA
Dennice Gayme, Johns Hopkins University, USA
Soumyadip Ghosh, IBM T. J. Watson Research Center, USA
Christoph Goebel, Technical University Munich, Germany
Zhu Han, University of Houston, USA
Jianwei Huang, The Chinese University of Hong Kong, Hong Kong
Abiodun Iwayemi, Illinois Institute of Technology, USA
Kimmo Kansanen, Norwegian University of Science and Technology, Norway
Sila Kiliccote, Lawrence Berkeley National Lavoratory, USA
Javad Lavaei, Columbia University, USA
Jang-Won Lee, Yonsei University, South Korea
Zuyi Li, Illinois Institute of Technology, USA
Hao Liang, University of Waterloo, Canada
Ning Lu, North Carolina State University, USA
Scott Moura, University of California at Berkeley, USA
Dusit Niyato, Nanyang Technological University, Singapore
Peter Palensky, Austrian Institute of Technology, Austria
Dzung Phan, IBM, USA
Liping Qian, Zhejiang University of Technology, China
Lei Rao, General Motors Research Lab, USA
Walid Saad, University of Miami, USA
Lingyang Song, Peking University, China
Ufuk Topcu, University of Pennsylvania, USA
Danny H. K. Tsang, Hong Kong University of Science and Technology, Hong Kong
Ping Wang, Nanyang Technological University, Singapore
Zhifang Wang, Virginia Commonwealth University, USA
Chenye Wu, Carnegie Mellon University, USA
Zhao Xu, Hong Kong Polytechnic University, Hong Kong
Wenxian Yang, Institute for Infocomm Research, Singapore
David Yau, Purdue University, USA
Baosen Zhang, Stanford University, USA
Ying Jun (Angela) Zhang, The Chinese University of Hong Kong