Research Projects

The Power at Home project focuses on aligning decarbonization and energy efficiency with the realities of how people live in New York. Standard energy models often assume a uniform nine-to-five lifestyle, which does not capture the range of daily rhythms across the city. The Columbia Building Energy Research Lab and the Living Data Lab are partnering to study real patterns of energy use among residents, including night shift workers, early morning caregivers, and artists who keep later schedules.

Developing reinforcement learning agents for building Heating Ventilation and Air Conditioning Systems (HVAC) requires pretraining with weeks of data or learning from simulated environments. This work seeks to determine the necessary dynamics to capture in a simulated environment to enable "good enough" initial performance. The aim is to develop simulated environments that can be used to train RL agents when limited data is available from the building.

To achieve climate change goals, we have to address how to decarbonize existing buildings. This means understanding what retrofits will reduce building energy demand and greenhouse gas emissions from local combustion. While it may seem simple, the options available to building professionals are vast and oftentimes difficult to assess against each other. The same is true of policymakers attempting to understand how to best achieve, support, and incentivize building decarbonization across countries and cities.

BERL is partnering with NYSERDA to aid in identifying desired use cases for Generative AI (GenAI) for Commercial Real Estate. Unlike traditional AI systems that primarily recognize or classify information, GenAI can generate original material that resembles human creativity and reasoning. Its abilities include producing coherent and contextually appropriate writing or artwork, summarizing complex information, understanding language and intent, writing and explaining computer code, analyzing data, and adapting outputs to a user’s tone or goals. 

The SESIMP-B project developed and demonstrated a plug-and-play smart service panel designed to better integrate Battery Energy Storage Systems with building loads and local distributed energy resources. The work aimed to make storage systems easier to install, more coordinated, and more cost-effective for a wide range of buildings, including those in underserved communities.