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This month’s webinar was focused on reinforcement learning as we had presentations from Dr Henze and his research team at CU Boulder. They discussed the advanced control test bed (ACTB) for buildings as well as opportunities, challenges and cases studies for reinforcement learning control in buildings.

Dr Nagy was the guest speaker in Amazon’s SSI speaker series on Sustainability. He talked about our research on CityLearn. Amazon is sponsoring AWS compute credits for the CityLearn Challenge 2022

Focused on the built environment’s transition to carbon neutrality and sustainability, CISBAT 2023 offers a scientific platform for the presentation of research that pushes the boundaries of energy efficiency and renewable energy technologies.

This award recognizes one or more individuals who have provided outstanding leadership in the promotion of building simulation through research in the course of their career. The award has be announced at the 2022 ASHRAE/IBPSA-USA BPAC/SimBuild Conference .

Led by IEL’s awesome PhD Student Kingsley, we have a new paper in Energy and AI. Open Access: https://www.sciencedirect.com/science/article/pii/S2666546822000489 Title: Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings Abstract:

Led by Aisling Pigott (CU Boulder), we have a new paper out in Electric Power Systems Research in collaboration with Dr Kyri Baker’s research group at CU Boulder. This work has also been presented at IEEE PSCC 2022

Dr Nagy has joined the organizing committee of ACM E-Energy 2023 as Publicity Chair, as well as the technical program commitee.

Big congrats to awesome IEL graduate students Kingsley and Praveen for winning Runners-Up prize ($5000) in Technical Demonstration category of the RTEM Hackathon 2022 organized by NYSERDA, OnboardData and others. https://www.

The Call for papers for the third edition of the ACM Workshop on Reinforcement Learning for Energy Management in Buildings and Cities is now published at http://rlem-workshop.net We expand beyond RL to more general AI in buildings, in particular real world demonstrations.

PV+Battery storage are the cornerstone of virtual power plants to provide grid flexibility. But what is the optimal charging/discharging policy to reduce costs and emissions from buildings ? And can you transfer knowledge/policies from one building to others?