Abstract
Purpose: This study aimed at proposing a predictive algorithm for the optimal control of the cooling system and openings of the double skin building in an integrated manner. Method: Two artificial neural network models were developed and employed in the predictive algorithm - the one is for controlling the cooling system and the other is for operating envelope openings. The thermal- and system operating performance were tested using the Transient Systems Simulation (TRNSYS) and Matrix Laboratory (MATLAB) softwares. The performance was compared with that of a conventional rule-based algorithm. Result: The predictive control algorithm presented more comfortable thermal environment with remarkable increase of the comfortable period up to 27% of whole period. In addition, the cooling system worked more stably decreasing the number of system
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