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Bayesian Iterative Method Using Parameter Scheduling for Predicting Optimal Condition on Thermal Index Due to Air Conditioning with Minimized Power

Yohei Saika 1 and Masahiro Nakagawa 2
1. National Institute of Technology, Maebashi, Japan
2. Nagaoka University of Technology, Nagaoka, Japan

Abstract—On the basis of the Bayesian iterative method via parameter scheduling, we investigate the prediction of a set of optimal environmental variables of small-scale space by using air conditioning with minimized power. Numerical calculations clarify dynamic properties of the environmental variables, such as temperature and relative humidity at each sampling point in the present method for several realistic cases in severe summer season. We find the optimal parameter scheduling realizing the optimal environment with minimized power of the air conditioning both using air cooling and dehumidifier.

Index Terms—Bayesian inference, expected a posterior estimation, indoor environment, parameter scheduling

Cite: Yohei Saika and Masahiro Nakagawa, "Bayesian Iterative Method Using Parameter Scheduling for Predicting Optimal Condition on Thermal Index Due to Air Conditioning with Minimized Power," International Journal of Electrical Energy, Vol. 6, No. 1, pp. 32-36, June 2018. doi: 10.18178/ijoee.6.1.32-36

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