Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm
Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi...
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2023
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my.uniten.dspace-244382023-05-29T15:23:30Z Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm Nasruddin Sholahudin Satrio P. Mahlia T.M.I. Giannetti N. Saito K. 57211141063 57202068616 57193959584 56997615100 56671465200 55105152500 Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi-objective genetic algorithm; Objective functions; Passive solar design; Radiant cooling; HVAC; air conditioning; artificial neural network; building; cooling; energy use; genetic algorithm; optimization; temperature effect The optimization of heating, ventilating and air conditioning (HVAC) system operations and other building parameters intended to minimize annual energy consumption and maximize the thermal comfort is presented in this paper. The combination of artificial neural network (ANN) and multi-objective genetic algorithm (MOGA) is applied to optimize the two-chiller system operation in a building. The HVAC system installed in the building integrates radiant cooling system, variable air volume (VAV) chiller system, and dedicated outdoor air system (DOAS). Several parameters including thermostat setting, passive solar design, and chiller operation control are considered as decision variables. Subsequently, the percentage of people dissatisfied (PPD) and annual building energy consumption is chosen as objective functions. Multi-objective optimization is employed to optimize the system with two objective functions. As the result, ANN performed a good correlation between decision variables and the objective function. Moreover, MOGA successfully provides several alternative possible design variables to achieve optimum system in terms of thermal comfort and annual energy consumption. In conclusion, the optimization that considers two objectives shows the best result regarding thermal comfort and energy consumption compared to base case design. � 2019 Elsevier Ltd Final 2023-05-29T07:23:30Z 2023-05-29T07:23:30Z 2019 Article 10.1016/j.seta.2019.06.002 2-s2.0-85067884492 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067884492&doi=10.1016%2fj.seta.2019.06.002&partnerID=40&md5=e42ee199ff7314d3a8ddadc1a6564a78 https://irepository.uniten.edu.my/handle/123456789/24438 35 48 57 Elsevier Ltd Scopus |
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| description |
Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi-objective genetic algorithm; Objective functions; Passive solar design; Radiant cooling; HVAC; air conditioning; artificial neural network; building; cooling; energy use; genetic algorithm; optimization; temperature effect |
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57211141063 |
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57211141063 Nasruddin Sholahudin Satrio P. Mahlia T.M.I. Giannetti N. Saito K. |
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Article |
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Nasruddin Sholahudin Satrio P. Mahlia T.M.I. Giannetti N. Saito K. |
| spellingShingle |
Nasruddin Sholahudin Satrio P. Mahlia T.M.I. Giannetti N. Saito K. Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| author_sort |
Nasruddin |
| title |
Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| title_short |
Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| title_full |
Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| title_fullStr |
Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| title_full_unstemmed |
Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| title_sort |
optimization of hvac system energy consumption in a building using artificial neural network and multi-objective genetic algorithm |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806425925406949376 |
| score |
13.222552 |