The Smart Buildings Control Suite: A Diverse Open Source Benchmark to Evaluate and Scale HVAC Control Policies for Sustainability

TL;DR

This paper introduces the Smart Buildings Control Suite, an open source benchmark with real data and scalable models to evaluate and improve HVAC control policies for sustainable building management.

Contribution

It provides the first open source, scalable HVAC control benchmark with real data, simulators, and models to facilitate research on scalable building climate control solutions.

Findings

Includes data from 11 buildings over 6 years.

Provides scalable simulators and PINN models for diverse buildings.

Compatible with Gym and TensorFlow Datasets for easy adoption.

Abstract

Commercial buildings account for 17% of U.S. carbon emissions, with roughly half of that from Heating, Ventilation, and Air Conditioning (HVAC). HVAC devices form a complex thermodynamic system, and while Model Predictive Control and Reinforcement Learning have been used to optimize control policies, scaling to thousands of buildings remains a significant unsolved challenge. Most current algorithms are over-optimized for specific buildings and rely on proprietary data or hard-to-configure simulations. We present the Smart Buildings Control Suite, the first open source interactive HVAC control benchmark with a focus on solutions that scale. It consists of 3 components: real-world telemetric data extracted from 11 buildings over 6 years, a lightweight data-driven simulator for each building, and a modular Physically Informed Neural Network (PINN) building model as a simulator alternative. The buildings span a variety of climates, management systems, and sizes, and both the simulator and PINN easily scale to new buildings, ensuring solutions using this benchmark are robust to these factors and only reliant on fully scalable building models. This represents a major step towards scaling HVAC optimization from the lab to buildings everywhere. To facilitate use, our benchmark is compatible with the Gym standard, and our data is part of TensorFlow Datasets.