Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm
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 max...
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| Format: | Article |
| Language: | English |
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MDPI
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/40234/1/Indoor%20comfort%20and%20energy%20consumption%20optimization.pdf |
| _version_ | 1825815446888120320 |
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| author | Farah Nur Arina, Baharudin Nor Azlina, Ab. Aziz Mohamad Razwan, Abdul Malek Anith Khairunnisa, Ghazali Zuwairie, Ibrahim |
| author_facet | Farah Nur Arina, Baharudin Nor Azlina, Ab. Aziz Mohamad Razwan, Abdul Malek Anith Khairunnisa, Ghazali Zuwairie, Ibrahim |
| author_sort | Farah Nur Arina, Baharudin |
| collection | UMP |
| description | 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. |
| first_indexed | 2024-03-06T13:13:36Z |
| format | Article |
| id | UMPir40234 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:13:36Z |
| publishDate | 2022 |
| publisher | MDPI |
| record_format | dspace |
| spelling | UMPir402342024-02-13T06:36:05Z http://umpir.ump.edu.my/id/eprint/40234/ Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm Farah Nur Arina, Baharudin Nor Azlina, Ab. Aziz Mohamad Razwan, Abdul Malek Anith Khairunnisa, Ghazali Zuwairie, Ibrahim T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures 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. MDPI 2022-11 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/40234/1/Indoor%20comfort%20and%20energy%20consumption%20optimization.pdf Farah Nur Arina, Baharudin and Nor Azlina, Ab. Aziz and Mohamad Razwan, Abdul Malek and Anith Khairunnisa, Ghazali and Zuwairie, Ibrahim (2022) Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm. Algorithms, 15 (395). pp. 1-21. ISSN 1999-4893. (Published) https://doi.org/10.3390/a15110395 https://doi.org/10.3390/a15110395 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Farah Nur Arina, Baharudin Nor Azlina, Ab. Aziz Mohamad Razwan, Abdul Malek Anith Khairunnisa, Ghazali Zuwairie, Ibrahim Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title | Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title_full | Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title_fullStr | Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title_full_unstemmed | Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title_short | Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| title_sort | indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/40234/1/Indoor%20comfort%20and%20energy%20consumption%20optimization.pdf |
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