Title: Regression model for estimating thermal resource usage in air conditioning systems: daily demand forecast by potential integral method, considering thermal inertia of room and weather conditions

Authors: Sho Ikawa; Kaoru Kuramoto; Satoshi Kumagai; Shuuzou Kishima

Addresses: Graduate School of Science and Engineering, Aoyama Gakuin University, Kanagawa, Japan ' College of Science and Engineering, Aoyama Gakuin University, Kanagawa, Japan ' College of Science and Engineering, Aoyama Gakuin University, Kanagawa, Japan ' National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan

Abstract: Air conditioning systems are required to achieve both the maintenance of energy conservation and proper control of room environment. Nonetheless, both the building manager and the user (i.e., room resident) are typically ignorant about the amount of air conditioning thermal resources being used by a particular room. Herein, we propose a method to predict the daily demand of thermal resources for individual rooms, considering their thermal characteristics. The amount of thermal resource consumption of individual rooms was predicted. A prediction model of the next-day consumption was also developed. The obtained results indicated that the influence of enthalpy at the end of the previous day was strong, and that the influence of the average temperature of the external factors was small.

Keywords: air conditioning system; prediction model; thermal resource.

DOI: 10.1504/AJMSA.2019.101410

Asian Journal of Management Science and Applications, 2019 Vol.4 No.1, pp.3 - 14

Received: 05 Apr 2018
Accepted: 25 Nov 2018

Published online: 01 Aug 2019 *

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