Enhancing Historic Building Performance with the Use of Fuzzy Inference System to Control the Electric Cooling System

Date
2020-07-21
Authors
Martinez-Molina, Antonio
Alamaniotis, Miltiadis
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract

In recent years, the interest in properly conditioning the indoor environment of historic buildings has increased significantly. However, maintaining a suitable environment for building and artwork preservation while keeping comfortable conditions for occupants is a very challenging and multi-layered job that might require a considerable increase in energy consumption. Most historic structures use traditional on/off heating, ventilation, and air conditioning (HVAC) system controllers with predetermined setpoints. However, these controllers neglect the building sensitivity to occupancy and relative humidity changes. Thus, sophisticated controllers are needed to enhance historic building performance to reduce electric energy consumption and increase sustainability while maintaining the building historic values. This study presents an electric cooling air controller based on a fuzzy inference system (FIS) model to, simultaneously, control air temperature and relative humidity, taking into account building occupancy patterns. The FIS numerically expresses variables via predetermined fuzzy sets and their correlation via 27 fuzzy rules. This intelligent model is compared to the typical thermostat on/off baseline control to evaluate conditions of cooling supply during cooling season. The comparative analysis shows a FIS controller enhancing building performance by improving thermal comfort and optimizing indoor environmental conditions for building and artwork preservation, while reducing the HVAC operation time by 5.7%.

Description
Final published version of this article is available at https://www.mdpi.com/2071-1050/12/14/5848.
Keywords
fuzzy control, historic buildings, electric systems, HVAC, Artificial Intelligence, fuzzy inference system, FIS, thermal comfort, preservation, electric cooling systems, fuzzy control, historic buildings, electric systems, HVAC, Artificial Intelligence, fuzzy inference system, FIS, thermal comfort, preservation, electric cooling systems
Citation
Martinez-Molina, A., & Alamaniotis, M. (2020). Enhancing Historic Building Performance with the Use of Fuzzy Inference System to Control the Electric Cooling System. Sustainability, 12(14), 5848. https://doi.org/10.3390/su12145848
Department
Architecture and Planning
Electrical and Computer Engineering