This workshop invites works from different strands of the AI community that pertain to the design of algorithms, models, and techniques to deal with smart grids and smart buildings.

Important Dates:

• October 23, 2017 - Submission Deadline
• November 9, 2017 - Acceptance Notification
• November 21, 2017 - Camera-Ready Deadline
• February 2 or 3, 2018 - Workshop Date

Call for paper [txt]

Registration and hotel information

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.

IIn 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 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

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=aisgsb2018.

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 2018 technical program. The deadline for receipt of submissions is October 13, 2017. 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.

TBA

Workshop Co-Chairs:

• Rodney Martin, NASA Ames Research Center <rodney.martin@nasa.gov>
• Christopher D. Kiekintveld, University of Texas at El Paso < cdkiekintveld@utep.edu >
• Son Cao Tran, New Mexico State University <tson@cs.nmsu.edu>
• Long Tran-Thanh, University of Southampton <l.tran-thanh@soton.ac.uk>
• Mischa Schmidt, NEC Laboratories Europe <Mischa.Schmidt@neclab.eu>