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

Miqdad Aziz (), Kushsairy Kadir, Haziq Kamarul Azman and Kanendra Vijyakumar
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Miqdad Aziz: Department of Electrical Technology Section, Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI), Kuala Lumpur 53100, Malaysia
Kushsairy Kadir: Department of Electrical Technology Section, Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI), Kuala Lumpur 53100, Malaysia
Haziq Kamarul Azman: Department of Electrical Engineering Section, Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI), Kuala Lumpur 53100, Malaysia
Kanendra Vijyakumar: Department of Electrical Engineering, Universiti Teknologi MARA (UiTM), Shah Alam 40450, Malaysia

Energies, 2023, vol. 16, issue 24, 1-32

Abstract: 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.

Keywords: air-conditioning and mechanical ventilation; air handling unit; energy efficiency; firefly algorithm; particle swarm optimization; smart building; thermal comfort (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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