Energy-saving analysis of neural network control based on PMV in a ship air conditioning system

Energy-saving analysis of neural network control based on PMV in a ship air conditioning system

In this paper, the design of neural network approach is developed aiming at the control of the indoor thermal comfort in air-conditioned cabins. Thermal environment of an air-conditioned ship cabin is simulated and analyzed. From the simulation results, predicted mean vote (PMV) is maintained near z...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Liu Hongmin, Tu Shuping
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
Atmospheric modeling
Energy consumption
Indexes
Marine vehicles
Mathematical model
neural network control air-conditioning
PMV
ship cabin
Temperature control
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Beschreibung
Zusammenfassung:In this paper, the design of neural network approach is developed aiming at the control of the indoor thermal comfort in air-conditioned cabins. Thermal environment of an air-conditioned ship cabin is simulated and analyzed. From the simulation results, predicted mean vote (PMV) is maintained near zero value with the fluctuation range of ±0.36 under neural network control. As for energy consumption, energy consumption of neural network control is less than that of control strategy based on temperature feedback. 8.5% energy can be saved.
DOI:10.1109/MEC.2011.6025715