Energy efficiency

A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings

Reinforcement learning (RL) has been shown to have the potential for optimal control of heating, ventilation, and air conditioning (HVAC) systems. Although research on RL-based building control has received extensive attention in recent years, there …

eplusr: A framework for integrating building energy simulation and data-driven analytics

Building energy simulation (BES) has been widely adopted for the investigation of building environmental and energy performance for different design and retrofit alternatives. Data-driven analytics is vital for interpreting and analyzing BES results …

Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning

Whole building energy model (BEM) is a physics-based modeling method for building energy simulation. It has been widely used in the building industry for code compliance, building design optimization, retrofit analysis, and other uses. Recent …

Green and cool roofs’ urban heat island mitigation potential in tropical climate

Urban heat island (UHI) can significantly affect building’s thermal-energy performance. Urban materials absorb solar and infrared radiation and the accumulated heat is dissipated in the atmosphere increasing further the air temperature. Roofs are …