Applying smart models for energy saving in optimal chiller loading

•A new smart method NNPSO of optimal chiller load is proposed.•This paper used neural networks and particle swarm optimization algorithm.•This study can save 12.68–17.63% as the load varies from 0.55 to 0.95 PLR.•The NNPSO method had fast convergence and highly accurate results.•The results demonstr...

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Veröffentlicht in:	Energy and buildings 2014-01, Vol.68, p.364-371
Hauptverfasser:	Chen, Ching-Liang, Chang, Yung-Chung, Chan, Tien-Shun
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Building technical equipments Buildings Buildings. Public works Computation methods. Tables. Charts Energy management and energy conservation in building Energy saving Environmental engineering Exact sciences and technology Neural network Optimal chiller loading Particle swarm algorithm Structural analysis. Stresses Ventilation. Air conditioning
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