Energy Consumption and Carbon Dioxide Production Optimization in an Educational Building Using the Supported Vector Machine and Ant Colony System

Wongchai Anupong (), Iskandar Muda, Sabah Auda AbdulAmeer, Ibrahim H. Al-Kharsan, Aníbal Alviz-Meza () and Yulineth Cárdenas-Escrocia
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Wongchai Anupong: Department of Agricultural Economy and Development, Faculty of Agriculture, Chiang Mai University, Chiang Mai 52000, Thailand
Iskandar Muda: Department of Doctoral Program, Faculty Economic and Business, Universitas Sumatera Utara, Medan 20222, Indonesia
Sabah Auda AbdulAmeer: Department of Mechanical Engineering, Ahl Al Bayt University, Kerbala 56001, Iraq
Ibrahim H. Al-Kharsan: Computer Technical Engineering Department, College of Technical Engineering, The Islamic University, Najaf 54001, Iraq
Aníbal Alviz-Meza: Grupo de Investigación en Deterioro de Materiales, Transición Energética y Ciencia de Datos DANT3, Facultad de Ingenieria y Urbanismo, Universidad Señor de Sipán, Km 5 Via Pimentel, Chiclayo 14001, Peru
Yulineth Cárdenas-Escrocia: GIOPEN, Energy Optimization Research Group, Energy Department, Universidad de la Costa (CUC), Cl. 58 ##55–66, Barranquilla 080016, Atlántico, Colombia

Sustainability, 2023, vol. 15, issue 4, 1-14

Abstract: Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it is essential to find ways to reduce the amount of energy used in this sector. The road administration organization in Jakarta, Indonesia, utilized a questionnaire as well as the insights of industry experts to determine the most effective energy optimization parameters. It was decided to select variables such as the wall and ceiling materials, the number and type of windows, and the wall and ceiling insulation thickness. Several different modes were evaluated using the DesignBuilder software. Training the data with a supported vector machine (SVM) revealed the relationship between the inputs and the two critical outputs, namely the amount of energy consumption and CO 2 production, and the ant colony algorithm was used for optimization. According to the findings, the ratio of the north and east windows to the wall in one direction is 70 percent, while the ratio of the south window to the wall in the same direction ranges from 35 to 50 percent. When the ratio and percentage of the west window to the west wall is between 60 and 70 percent, the amount of produced energy and CO 2 is reduced to negligible levels.

Keywords: building; energy optimization; ACS; SVM (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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