Publication: Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
Date
2020
Authors
Suliman A.
Uskenbayeva R.
Altayeva A.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
This paper proposes a concept for managing climate control systems (HVAC systems) in large commercial buildings based on predictive models. The proposed control concept reduces the consumption of gas used for room heating while maintaining the acceptable range of the required temperature. The authors propose fuzzy and neuro-fuzzy models to ensure comfort temperature and humidity in the indoor environment, and thus minimize energy consumption. The management strategy is formed using predictive models. The developed management strategy is applied to the climate control system through a hardware and software complex consisting of a client connected to the system and a server that forecasts changes in indoor temperature, gas consumption and forms a management strategy. The tests that implemented the proposed concept were performed in a commercial building. The efficiency of the proposed concept is shown in comparison with the control algorithm built into the HVAC system. � 2020 IEEE.
Description
Climate control; Climate models; Control systems; Energy utilization; Fuzzy inference; Fuzzy neural networks; Office buildings; Predictive analytics; Comfort temperatures; Commercial building; Hardware and software; Indoor environment; Indoor temperature; Management strategies; Microclimate control; Neuro-Fuzzy model; HVAC