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Applying neural networks to investigations of the influence of weather conditions on the power consumption of J-PARC

Nomura, Masahiro ; Tamura, Fumihiko  ; Shimada, Taihei ; Yamamoto, Masanobu  ; Furusawa, Masashi*; Sugiyama, Yasuyuki*; Hara, Keigo*; Hasegawa, Katsushi*; Omori, Chihiro*; Yoshii, Masahito*

In recent years, summer temperatures have tended to increase, so understanding the amount of power consumption in summer from weather information has become important in terms of contract power and power saving measures. The relationship between the amount of power consumption and weather conditions is that the accelerator facility has many cooling facilities, so it can be thought that the amount of power used to cool each device increases as the temperature and humidity increase. It seems that it has not been investigated specifically what kind of dependence there is. Therefore, considering the neural network as a kind of fitting function or a model of calculation, we investigated the influence of weather conditions on the power consumption. As a result, it was found that the power consumption of the accelerators mostly depends only on the temperature, and the electric power of Linac and RCS increases by about 1 MW when the temperature of Mito rises by 10$$^{circ}$$C.

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