CityLearn Challenge 2022 - Winners Announced!

šŸ†And here are the winners! Please join me in congratulating the winners of the CityLearn Challenge 2022:

šŸ„‡1st Prize ($8000) Team Together (Alibaba Group, China)
šŸ„ˆ2nd Prize ($5000) Team ambitiousengineers (University of WashingtonandĀ University of Hawaii at Manoa, USA)
šŸ„‰3rd Prize ($2000) Team CUFE (Cairo University, Egypt)

Thank you toĀ EPRIĀ for sponsoring the award and providing real-world data for use in the challenge, and toĀ Amazon ScienceĀ for sponsoring the compute credits.Ā 

Kingsley NweyeĀ (Intelligent Environments Laboratory) andĀ Dipam ChakrabortyĀ (AIcrowd) ran a fantastic job in the background to ensure a smooth challenge!

Runner-Ups
Team DivMARL (University of Alberta, Canada) andĀ 
Team Greener (Microsoft ResearchĀ Asia,Ā Tsinghua University,Ā iSoftStone)

All teams provided solutions for behind the meter coordination of distributed energy resources in single family homes based on real world data and the CityLearn Open AI Gym environment. Read about the challenge here:Ā https://lnkd.in/grnpRghM

We are working on a solutions paper with the participants. Meanwhile, you can also rewatch the teamā€™s presentation at our NeurIPSā€™22 workshop here:Ā https://lnkd.in/gYRMS72S

AND: ACM SIGEnergy is awarding three travel grants (up to $1000 each) to BuildSys23 or eEnergy23 as community prizes for the following challenge participants for their contribution in improving the challenge (identifying and fixing bugs, providing notebooks to other participants, and/or participating in online discussions):

Ludwig BaldĀ (University of Tuebingen, Germany)
Chia E. Tungom (Chemago)Ā (Shenzhen UniversityĀ & OneWo, China)
Julian Jacques Ruddick (Vrije Universiteit Brussel, Belgium)

A big special THANK YOU goes to the over 600 participants who made this challenge a big success!

Thanks to theĀ Energy Institute, The University of Texas at AustinĀ for financially supporting the challenge organization andĀ AIcrowdĀ for executing the challenge. Finally, thanks to our advisorsĀ Tianzhen HongĀ (Berkeley Lab)Ā JĆ”n DrgoňaĀ (Pacific Northwest National Laboratory) and Greg Henze (University of Colorado Boulder).

And last but not least thanks toĀ Siva SankaranarayananĀ - EPRI’s lead for the AI Grand Challenge in Grid-Interactive Smart Communities.

See you all for the CityLearn Challenge 2023!

Zoltan Nagy
Zoltan Nagy
Assistant Professor

My research interests include reinforcement learning for buildings and smart cities.