Artificial Intelligence for Environmentally Responsive Buildings

You are cordially invited to attend the Research Seminar: Artificial Intelligence for Environmentally Responsive Buildings by Elence Xinzhu Chen

Date: 8 February 2024 (Thurs)
Time: 9:30 AM – 10:30 AM
Venue: SDE 4 Level 5 Forum

Abstract
The building sector emerges as a pivotal player in global energy dynamics, accounting for nearly a third of the world’s energy consumption and greenhouse gas emissions, the urgency to enhance building energy efficiency is more pronounced than ever. This seminar aims to address this crucial challenge, highlighting the significant economic, social, and environmental impacts of optimizing building operations in alignment with worldwide goals for carbon neutrality. Many Building Management Systems (BMS), however, still operate on traditional principles, lack optimization, and function in isolation. This underscores the critical need for more advanced, adaptable, and interconnected solutions to foster the development of intelligent and eco-friendly buildings.

This seminar will discuss the integration of artificial intelligence (AI) algorithms into building control system optimizations. By applying data-driven approaches, the AI-aided control algorithm can adapt to dynamic environments, coordinate multiple building systems, and balance multiple optimization objectives. During the seminar, two pivotal methodologies will be discussed: (1) the deployment of adaptive model predictive control specifically tailored for natural ventilation, and (2) the application of multi-agent model-free reinforcement learning in achieving coordinated control. This exploration navigates the path towards more energy-efficient, intelligent, and sustainable buildings.

About the speaker

Elence Xinzhu Chen is an instructor in Architecture at the Harvard University Graduate School of Design and a postdoctoral fellow at the Harvard Center for Green Buildings and Cities. Her research integrates advanced machine learning techniques with building performance simulation and system control to advance the development of smart, sustainable, and autonomous buildings. Her research interests include advanced building control, machine learning for modeling and controlling the built environment, zero energy/carbon buildings and cities, grid-interactive buildings, and urban energy simulations. Her recent papers have been published in Building and Environment, Energy and Buildings, Sustainable Cities and Society, and have been presented at IBPSA Building Simulation Conference, ASHREA winter Conference, etc.

Elence holds a Doctor of Design in Building Technology and a Master of Design with concentration in Energy and Environment from the Harvard University Graduate School of Design, where she was awarded the Daniel L. Schodek Award for Technology and Sustainability. She earned a Bachelor of Science in Project and Facilities Management with honors from National University of Singapore.