标题：A Comparative Study Between Thermostat/Hygrometer-Based Conventional and Artificial Neural Network-Based Predictive/Adaptive Thermal Controls in Residential Buildings
期刊名称：Journal of Asian Architecture and Building Engineering
印刷版ISSN：1346-7581
电子版ISSN：1347-2852
出版年度：2012
卷号：11
期号：1
页码：169-176
DOI：10.3130/jaabe.11.169
语种：English
出版社：日本建築学会、大韓建築学会、中国建築学会
摘要：This study aimed at testing the feasibility of employing artificial neural network (ANN)-based predictive and adaptive control logics to improve thermal comfort and energy efficiency through a decrease in overshoots and undershoots of control variables. Three control logics were developed: (1) conventional temperature/humidity control logic, (2) ANN-based temperature/humidity control logic, and (3) ANN-based Predicted Mean Vote (PMV) control logic. Performance tests were conducted in a thermal chamber for non-application of setback and application of setback of thermal factors. Analysis revealed that the ANN-based predictive temperature/humidity control logic generally provided greater periods of thermal comfort than that of the conventional logic, as well as a reduction in overshoots and undershoots. In addition, the ANN-based PMV control logic provided significantly better PMV conditions than both temperature/humidity based control logics. In more cases, ANN-based control logic demonstrated a reduction in electricity consumption, compared to non-ANN-based control logic, especially for a system with a large time-lag effect such as a radiant water heating system.
关键词：artificial neural network;predictive controls;adaptive controls;thermal comfort;PMV control
