Power Substation Construction and Ventilation System Co-Designed Using Particle Swarm Optimization
Jau-Woei Perng,
Yi-Chang Kuo,
Yao-Tsung Chang and
Hsi-Hsiang Chang
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Jau-Woei Perng: Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
Yi-Chang Kuo: Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
Yao-Tsung Chang: Taiwan Power Company Southern Region Construction Office, Kaohsiung 81166, Taiwan
Hsi-Hsiang Chang: Taiwan Power Company Southern Region Construction Office, Kaohsiung 81166, Taiwan
Energies, 2020, vol. 13, issue 9, 1-27
Abstract:
This study discusses a numerical study that was developed to optimize the ventilation system in a power substation prior to its installation. We established a multiobjective particle swarm optimizer to identify the best approach for simultaneously improving, first, the ventilation performance considering the most appropriate inlet size and outlet openings and second, the reduction of the synthetic noise of the ventilation and power consumption from the exhaust fan equipment and its operation. The study used building information modeling to construct indoor and outdoor models of the substation building and verified the overall performance using ANSYS FLUENT 18.0 software to simulate the air velocity and air temperature distribution within the building. Results show that the exhaust fan of the B1F cable finishing room and the 23 kV gas insulated switchgear (GIS) room optimize the reduction of horsepower by approximately 1 Hp and 0.5 Hp. The combined noise is reduced by 4 dBA and 2 dBA; the exhaust fan runs for 30 min, and the two equipment rooms can cool down by 2.9 °C and 1.7 °C, respectively. Therefore, it is confirmed that the MOPSO algorithm provides a more energy-efficient and environmentally friendly building ventilation environment.
Keywords: power substation; inlet and outlet openings; synthetic noise; multiobjective particle swarm optimizer; exhaust fan; gas insulated switchgear (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: 2020
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:9:p:2314-:d:354692
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