Artificial Intelligence-Assisted Heating Ventilation and Air Conditioning Control and the Unmet Demand for Sensors: Part 1. Problem Formulation and the Hypothesis

Abstract

In this study, information pertaining to the development of artificial intelligence (AI) technology for improving the performance of heating, ventilation, and air conditioning (HVAC) systems was collected. Among the 18 AI tools developed for HVAC control during the past 20 years, only three functions, including weather forecasting, optimization, and predictive controls, have become mainstream. Based on the presented data, the energy savings of HVAC systems that have AI functionality is less than those equipped with traditional energy management system (EMS) controlling techniques. This is because the existing sensors cannot meet the required demand for AI functionality. The errors of most of the existing sensors are less than 5%. However, most of the prediction errors of AI tools are larger than 7%, except for the weather forecast. The normalized Harris index (NHI) is able to evaluate the energy saving percentages and the maximum saving rations of different kinds of HVAC controls. Based on the NHI, the estimated average energy savings percentage and the maximum saving rations of AI-assisted HVAC control are 14.4% and 44.04%, respectively. Data regarding the hypothesis of AI forecasting or prediction tools having less accuracy forms Part 1 of this series of research.

Artificial intelligence implementation framework development for building energy saving

“…• Normalized Harris index The Harris index (H) and NHI, 1 as shown in Equations 1 and 2, respectively, were used to evaluate the performance of conventional and AI-assisted HVAC control outputs.…”

“…AI integration in building energy management to improve energy efficiency is one such field. In our previous study, 1 97 full-text articles published related to "AI" and "Heating, ventilation and air conditioning (HVAC)" were surveyed to explore how AI could improve the performances of HVAC systems. This research goes further to collect 113 articles related to "AI" and "building" to investigate how to apply AI for building energy saving.…”

Investigation of Thermal Comfort Responses with Fuzzy Logic

“…During these years, thermostats underwent significant changes, and integrated modern IT solutions, such as sensors, actuators, hardware, software, and cloud solutions [39]. More than 18 AI solutions are available for HVAC systems developed during the last 20 years, but only three of them have become especially popular: weather forecasting, optimization, and predictive controls [40]. Most of the technical building systems today do not work as efficiently as those with artificial intelligence.…”

“…Most of the technical building systems today do not work as efficiently as those with artificial intelligence. This is due to the fact that existing sensors are not able to meet the requirements of AI [39,40] Reducing energy consumption is only one task in today's environmentally conscious development. Systems with AI are expected to give feedback on the state of the internal environment, as well.…”

“…Systems with AI are expected to give feedback on the state of the internal environment, as well. These indices may help optimize HVAC systems, such as the Harris Index, but this does not characterize the internal environment from a comfort theory point of view [40][41][42]…”