Call for Papers
Buildings account for 40% of the global energy consumption and 30% of the associated greenhouse gas emissions, while also offering a 50–90% CO2 mitigation potential. The transportation sector is responsible for an additional 30%. Optimal decarbonization requires electrification of end-uses and concomitant decarbonization of electricity supply, efficient use of electricity for lighting, space heating, cooling and ventilation (HVAC), and domestic hot water generation, and upgrade of the thermal properties of buildings. A major driver for decarbonization are integration of renewable energy systems (RES) into the grid, and photovoltaics (PV) and solar-thermal collectors as well as thermal and electric storage into residential and commercial buildings. Electric vehicles (EVs), with their storage capacity and inherent connectivity, hold a great potential for integration with buildings.
The integration of these technologies must be done carefully to unlock their full potential. Artificial intelligence is regarded as a possible pathway to orchestrate these complexities of Smart Cities. In particular, (deep) reinforcement learning algorithms have seen an increased interest and have demonstrated human expert level performance in other domains, e.g., computer games. Research in the building and cities domain has been fragmented and with focus on different problems and using a variety of frameworks. The purpose of this Workshop is to build a growing community around this exciting topic, provide a platform for discussion for future research direction, and share common frameworks.
Topics of Interest
Topics of interest include, but are not limited to:
- Challenges and Opportunities for RL in Building and Cities
- Explorations of model vs model-free RL algorithms and hybrids
- Comparisons of RL algorithms to other control solutions, e.g., model-predictive control
- Frameworks and datasets for benchmarking algorithms
- Theoretical contributions to the RL field brought about by constraints/challenges in the buildings/cities domain
- Applications (demand response, HVAC control, occupant integration, traffic scheduling, EV/battery charging, DER integration)
- Predicting energy consumption for Energy Demand Site Management
- Renewable energy forecasting for Energy Demand Site Management
We solicit submissions in two categories: Original Research Paper and Journal Track. Please indicate the category when submitting the work.
- Original Research Paper: Submitted papers must be unpublished and must not be currently under review for any other publication. Paper submissions must be at most 4 single-spaced US Letter (8.5"x11") pages, including figures, tables, and appendices (excluding references). All submissions must use the LaTeX (preferred) or Word styles found here https://www.acm.org/publications/proceedings-template. Authors must make a good faith effort to anonymize their submissions by (1) using the "anonymous" option for the class and (2) using "anonsuppress" section where appropriate. Papers that do not meet the size, formatting, and anonymization requirements will not be reviewed. Please note that ACM uses 9-pt fonts in all conference proceedings, and the style (both LaTeX and Word) implicitly define the font size to be 9-pt.
- Journal Track: Authors of published journal articles relevant to the workshop audience are invited to present their work, expand their outreach, and engage in discussions with the community. The requirement for the journal track presentation is that it must have been published within the last 12 months prior to the conference (since Nov 2022). Please submit the title, abstract and the DOI link to your paper. Paper will be selected by the program committee based on how well they fit the workshop scope, the allocated time in the program and interest to the community.