IEEE SmartGridComm Symposium on

Smart/Virtual Metering, Demand Response, Dynamic Pricing

 

Symposium Co-Chairs
Archan Misra Telcordia Technologies, USA	Yoshizumi Serizawa Central Research Institute of Electric Power Industry (CRIEPI), Japan	Tina Tsou Huawei Technologies, China

Scope and Motivation

Demand response (DR), or the ability to dynamically adjust current or future electricity loads, in response to pricing signals, is one of the most important ‘demand-side’ capabilities envisaged in the future smart grid. The basic theories of relatively less-dynamic forms of demand response, such as peak load pricing, was worked out in the 1960s and 1970s and became a common practice in European utilities during that period. The future, however, is likely to witness significantly more dynamic and market-driven DR operations, characterized by more complex dynamics in electricity pricing and the ability of consumers to perform finer-grained control of their consumption profiles.

Enabling such sophisticated DR capabilities requires advances across a broad set of infrastructural, appliance-oriented and operational capabilities. For example, effective DR mechanisms, protocols and algorithms must be developed that allow individuals (or groups of individual) to negotiate and specify their collective and individual load modification behavior in response to changes in electricity prices. Similarly, smart meters need to be enhanced to capture and expose the consumption patterns at different levels of granularity (devices, individuals, organizations), while ensuring appropriate respect for privacy preferences. Also, dynamic pricing signals need to be enhanced to better exploit knowledge about the likely future evolution of demand and supply, while DR adaptation needs to better incorporate the increasing availability of renewable, micro-grid energy sources.

Accordingly, this symposium solicits original, research contributions that address all aspects (theoretical and practical) of the LOGICAL life cycle of demand sensing (smart metering), resource pricing (dynamic pricing) and load adaptation (DR). Papers can summarize recent theoretical developments and practical experience in the topic area, explore the impact of smart/virtual metering on the utility's cost structure and resultant use of dynamic pricing and evaluate open issues in the regulatory issues of applying DR. We especially solicit papers that describe practical experiences and insights gained from the operational use of novel DR paradigms.

Papers focusing specifically on the underlying communications and networking technologies should, however, be submitted to the alternative appropriate symposia.

Topics of Particular Interest

Areas of interest include, but are not limited to:

1. Dynamic Pricing Models
2. Incentive-based vs. Punitive Pricing, Energy Profiles and Demand Response
3. DR Architectures (Centralized, Distributed, Hierarchical)
4. DR Capabilities in Consumer and Industrial Appliances
5. Security, Authentication and Privacy in DR and Smart Metering
6. Smart Meters and Consumer Portals/Gateways: Capabilities, Visualizations, and Data Management
7. Context-Awareness and DR Policies
8. Cooperative and non-cooperative DR optimization
9. Individualized and community DR strategies
10. Integration of Microgrids and Renewables in DR architectures
11. DR experiences and experimental outcomes
12. Virtualization in Pricing and DR
13. Energy Management Systems (EMS) and Automated DR
14. Analytics-driven Insights for DR strategies
15. Standards activities for DR and dynamic pricing

Submission Guidelines

Submission deadlines and format requirements are the same for all symposia, see here

Papers can be submitted here

Technical Program Committee (TPC) Members

Kaywan Afkhamie, Atheros, USA
Hiroshi Asano, CRIEPI, Japan
Scott Bradner, Harvard University, USA
Gerd Bumiller, iAd GmbH, Germany
Constantine Caramanis, The University of Texas at Austin, USA
Michael Caramanis, Boston University, USA
Gordon Gregg, Aclara, USA
Toru Hattori, CRIEPI, Japan
David Holmberg, NIST, USA
Jayant Kalagnanam, IBM Research, USA
Rajeev Koodli, Cisco Systems, USA
Bruce Nordman, Lawrence Berkeley National Laboratory, USA
Tetsuo Otani, Central Research Institute of Electric Power Industry, Japan
Don Tench, IESO, Canada
Vincent Wong, University of British Columbia, Canada
Peili Xu, Huawei, China
Abraham Young, Huawei Technologies, China