H-42 老人ホームにおける潜熱・顕熱蓄熱材併用型床暖房の性能評価と運転方法に関する研究 : その3.早春を含めた暖房期全般の可能性推定モデルを内含させたニューラルネットワークモデルの構築

概要

論文の詳細を見る
The floor heating system that constructed of latentlsensible heat storage material with using off-peak electricity needs prediction control system of the next days heating load. The authors constructed the neural network including possibility presumption models of heating period including early spring. Next, the authors predicted maximum heating set temperature of storage materials by range of the possibility about heating load that was predicted by the neural network. The following results are clarified. (1)The authors could predict same range of possibility about heating load that predicted already reported. (2)The authors could predict maximum heating set temperature of storage materials that made the room temperature comfortable.
社団法人空気調和・衛生工学会の論文
2005-07-25