Advanced Control of Dynamic Facades and HVAC with Reinforcement Learning

Publication Type

Conference Proceedings

Authors

Abstract

With increased complexity due to time-variable renewable electricity supply and associated variable cost, it has become evident that management of building energy demand as a resource is essential for grid stabilization. However, techno-economic and human constraints make such solutions non-trivial. Reinforcement learning (RL), a discipline of machine learning, was explored to take on this challenge. The open-source Functional Mock-up Interface - Machine Learning Center (FMI-MLC) was developed to provide a standardized interface of RL and simulation environment, through the FMI industry standard for co-simulation. RL demonstrated its ability to operate an electrochromic window and heating, ventilation, and air conditioning system (HVAC), and reduce demand during critical periods of the electric power grid.

Journal

Building Simulation 2021

Year of Publication

2022

Organization

Research Areas

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