Citation

Baharudin, Farah Nur Arina and Ab Aziz, Nor Azlina and Abdul Malek, Mohamad Razwan and Ghazali, Anith Khairunnisa and Ibrahim, Zuwairie (2022) Indoor Comfort and Energy Consumption Optimization Using an Inertia Weight Artificial Bee Colony Algorithm. Algorithms, 15 (11). p. 395. ISSN 1999-4893

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Abstract

A comfortable indoor environment contributes to a better quality of life and wellbeing for its occupants. The indoor temperature, lighting, and air quality are the main controlling factors of user comfort levels. The optimum control of the lighting, air conditioners, and air ventilators helps in maximizing the user’s comfort level. Nonetheless, the energy consumption of these appliances needs to be taken into consideration to minimize the operational cost and at the same time provide an environmentally friendly system. Comfort level maximization and energy consumption minimization are optimization problems. This issue is becoming more important due to the lifestyle changes caused by the COVID-19 pandemic that resulted in more time spent at home and indoors. Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, linearly decreasing, and exponentially increasing inertia are proposed here for the optimization of the indoor comfort index and energy usage. The multi-objective problem is tackled as a weighted single objective optimization problem. The proposed solution is tested using a dataset of 48 environmental conditions. The results of the simulation show that the IW-ABC performs better than the original ABC and other benchmark algorithms and the IW-ABC with linear increasing inertia weight has the most improved convergence behavior.

Item Type:	Article
Uncontrolled Keywords:	Artificial bee colony, comfort index, energy consumption, inertia weight, residential building
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD9000-9999 Special industries and trades Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75-76.95 Calculating machines
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Jan 2023 03:05
Last Modified:	04 Jan 2023 03:05
URII:	http://shdl.mmu.edu.my/id/eprint/10741

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