Timezone: »

The CityLearn Challenge 2022
Zoltan Nagy · Kingsley Nweye · Sharada Mohanty · Siva Sankaranarayanan · Jan Drgona · Tianzhen Hong · Sourav Dey · Gregor Henze

Wed Dec 07 05:00 AM -- 07:30 AM (PST) @ Virtual

Reinforcement learning has gained popularity as a model-free and adaptive controller for the built-environment in demand-response applications. However, a lack of standardization on previous research has made it difficult to compare different RL algorithms with each other. Also, it is unclear how much effort is required in solving each specific problem in the building domain and how well a trained RL agent will scale up to new environments. The CityLearn Challenge 2022 provides an avenue to address these problems by leveraging CityLearn, an OpenAI Gym Environment for the implementation of RL agents for demand response. The challenge utilizes operational electricity demand data to develop an equivalent digital twin model of the 20 buildings. Participants are to develop energy management agents for battery charge and discharge control in each building with a goal of minimizing electricity demand from the grid, electricity bill and greenhouse gas emissions. We provide a baseline RBC agent for the evaluation of the RL agents performance and rank the participants' according to their solution's ability to outperform the baseline.

Author Information

Zoltan Nagy (The University of Texas at Austin)
Kingsley Nweye (The University of Texas at Austin)
Sharada Mohanty (AIcrowd SA)
Siva Sankaranarayanan (EPRI)
Jan Drgona (Pacific Northwest National Laboratory)

I am a data scientist in the Physics and Computational Sciences Division (PCSD) at Pacific Northwest National Laboratory, Richland, WA. My current research interests fall in the intersection of model-based optimal control, constrained optimization, and machine learning.

Tianzhen Hong (LBNL)

Dr. Tianzhen Hong is a Senior Scientist and Deputy Head of the Building Technologies Department of LBNL. He leads the Urban Systems Group and a team with research on data, methods, computing, occupant behavior, and policy for design and operation of low energy buildings and sustainable urban systems. He is an IBPSA Fellow, ASHRAE Fellow, and a Highly Cited Researcher 2021. He received B.Eng. and Ph.D. in HVACR, and B.Sc. in Applied Mathematics from Tsinghua University, China.

Sourav Dey (University of Colorado, Boulder)
Gregor Henze (University of Colorado, Boulder)

More from the Same Authors