Optimization of Air Handler Controllers for Comfort Level in Smart Buildings Using Nature Inspired Algorithm

This research seeks to improve the temperature control of AHU in building sub-levels using optimization algorithms. Specifically, the study applies the FA and PSO algorithms to optimize the PID control of AHU’s temperature. The study addresses the issue of temperature control in building sub-levels,...

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Bibliographic Details
Published in:Energies (Basel) 2023-12, Vol.16 (24), p.8064
Main Authors: Aziz, Miqdad, Kadir, Kushsairy, Azman, Haziq Kamarul, Vijyakumar, Kanendra
Format: Article
Language:English
Subjects:
Air conditioning
air handling unit
air-conditioning and mechanical ventilation
Algorithms
Buildings
Chilled water systems
Contemporary problems
Cooling
Energy conservation
Energy consumption
Energy efficiency
Environmental conditions
firefly algorithm
Methods
Optimization techniques
particle swarm optimization
Simulation
smart building
Temperature
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Summary:This research seeks to improve the temperature control of AHU in building sub-levels using optimization algorithms. Specifically, the study applies the FA and PSO algorithms to optimize the PID control of AHU’s temperature. The study addresses the issue of temperature control in building sub-levels, which is a common challenge in HVAC systems. The study uses optimization algorithms and a nonlinear model to improve temperature control and reduce fluctuations in temperature from the desired setting. Additionally, a NL-ARX algorithm is utilized to create a nonlinear model based on the thermal dynamics and energy behavioral patterns of ACMV cooling systems. The study evaluates the performance of three controllers—PID, FA-PID, and PSO-PID—based on ITSE as a performance index. The study compares the performance of these controllers to achieve the desired temperature setting, and it analyses the influence of temperature regulation on occupant comfort levels. In this study, we compare different controllers using ITSE as a performance indicator. This shows how well different optimization algorithms work at setting the right temperature. The research gap is the lack of efficient temperature control solutions in building sub-levels that can optimize occupant comfort and energy efficiency. The experimental findings confirm that PSO-PID outperforms conventional PID and FA-PID optimization in terms of achieving the goal objective via computational complexity. Overall, this study’s focus is to explore and compare different optimization algorithms to improve temperature control and occupant comfort in building sub-levels.
ISSN:1996-1073
1996-1073
DOI:10.3390/en16248064