2nd International Workshop on AI for Smart Grids and Smart Buildings
(AISGSB17)
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February 4 or 5, 2017
Held in conjunction with AAAI 2017
San Francisco, California, USA
http://www.cs.nmsu.edu/aisgsb17
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Call for Papers
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Workshop Description and Motivation:
The availability of advanced sensing and communication infrastructures,
electric monitoring facilities, computational intelligence, widespread
use and interest in renewable energy sources, and customer-driven
electricity usage, storage and generation capabilities, have posed the
foundations for a robust and dynamic next generation economic interplay
between the demand-side: smart buildings, and the supply-side: smart power
grids. Three key aspects distinguish this evolving economy from more
traditional market forces:
(1) Information: both energy producers and consumers have access to
information (e.g., production costs, customers' electricity needs,
time distribution of demands);
(2) Exchange: communication is possible on a continuous basis, thus
enabling both individual as well as group decision processes
(e.g., producers and consumers can negotiate prices and energy
exchanges);
(3) energy can be produced not only by power plants, but also by
customers (e.g., via solar panels) and stored for later use
(or redistributed through the electric grid), and
(4) given all of the above, customers can employ advanced tactical
measures for improving building operations and reducing energy
consumption without sacrificing occupant satisfaction, which has
direct economic implications for producers.
In general terms, a smart grid enables the distributed generation and
two-directional flow of electricity and information, within an integrated
system of connected smart buildings as key agents within this new ecosystem.
AI plays a key role in the relationship between the smart grid and smart
buildings. New technologies offer infrastructure that provides information
to support automated decision making on how to (automatically) adapt
production/consumption, optimize costs, waste, and environmental impact,
and provide reliability, safety, security, and efficiency. Indeed, several
research projects have already developed the view of this ecosystem as a
multi-agent system, where agents coordinate and negotiate to achieve smart
grid and smart building objectives.
The goal of this workshop is to bring together researchers and practitioners
from diverse areas of AI to explore both established and novel applications
of AI techniques to address problems related to the design, implementation,
deployment, and maintenance of both smart buildings and the smart grid –
either as independent topics or together in an overarching multi-agent
system.
Topics include, but are not limited to:
• Distributed decision making and distributed optimization
• Agents and multi-agent applications in smart grids
• Data analytics and machine learning techniques applied to smart buildings,
grids and energy management
• Advanced machine learning techniques used to improve building maintenance
and operations and reduce energy consumption without sacrificing occupant
satisfaction
• Novel information and sensing technologies that can be used to enable the
deployment of advanced machine learning and data mining techniques within
the built environment
• Knowledge-based methods in design of smart buildings and smart grids
• Coordination of intelligent agents in smart grids
• Negotiation and trading strategies in energy markets
• Human-computer interactions and human-in-the-loop systems within smart grids
• Simulations of energy markets and smart grids
Workshop Format:
The workshop is expected to be a full-day event. It will include three
components:
(1) one invited keynote speaker, selected among leading researchers
exploring the advanced use of AI techniques to address practical
issues of smart grids and smart buildings;
(2) a collection of presentations selected from peer-reviewed submissions,
in response to an open call for papers; (3) a closing panel, including
both invited panelist and workshop participants, to discuss future
directions of research in this field.
Submission Guidelines:
Participants should submit a paper (maximum 6 pages + 1 page of references),
describing their work on one or more of the topics relevant to the workshop.
Accepted papers will be presented during the workshop and will be published
as AAAI technical reports, which will be made freely available in AAAI's digital
library.
Authors are requested to prepare their papers using the AAAI style files (http://www.aaai.org/Publications/Templates/AuthorKit.zip).
All submissions are conducted via the following website:
http://www.easychair.org/conferences/?conf=aisgsb2017.
Submissions should include the name(s), affiliations, and email addresses of
all authors in the body of the email. We welcome the submission of papers
rejected from the AAAI 2017 technical program. The deadline for receipt of
submissions is October 21, 2016. Papers received after this date may not be
reviewed.
Submissions will be refereed on the basis of technical quality, novelty,
significance, and clarity. Each submission will be thoroughly reviewed by at
least two program committee members.
For questions about the submission process, contact the workshop co-chairs.
Important Dates:
* October 21, 2016 - Submission Deadline
* November 18, 2016 - Acceptance Notification
* December 8, 2016 - Camera-Ready Deadline
* February 4 or 5, 2017 - Workshop Date
Organizing Committee:
Rodney Martin, NASA Ames Research Center
Enrico Pontelli, New Mexico State University
Son Cao Tran, New Mexico State University
Long Tran-Thanh, University of Southampton
Contact Information:
aisgsb2017@easychair.org
--------
Long Tran-Thanh
Lecturer
--
Agents, Interaction, and Complexity Group,
Electronics and Computer Science,
University of Southampton, SO17 1BJ
--
http://users.ecs.soton.ac.uk/ltt08r
tel: +44 (0) 2380593715
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