Multi-agent system for energy consumption optimisation in higher education institutions

被引：21
作者：
Al-Daraiseh, Ahmad [1 ]
El-Qawasmeh, Eyas [1 ]
Shah, Nazaraf [2 ]
机构：
[1] King Saud Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
[2] Coventry Univ, Fac Engn & Comp, Coventry, W Midlands, England
来源：
JOURNAL OF COMPUTER AND SYSTEM SCIENCES | 2015年 / 81卷 / 06期
关键词：
Energy management; Energy optimisation; Energy conservation; Sensor network; HVAC control; Energy efficiency; COMFORT MANAGEMENT; PREDICTIVE CONTROL; OCCUPANT BEHAVIOR; MODEL; CONSERVATION; ENVIRONMENT;
D O I：
10.1016/j.jcss.2014.12.010
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Global warming is one of the most serious issues faced by today's world. The increase in world population and adoption of modern lifestyle have dramatically increased the demand for energy. Over the last decade Higher Educational Institution (HEI) buildings have seen massive increase in energy consumption due to increased use of IT equipments, longer occupancy and increased use of Heating Ventilation and Air Conditioning (HVAC) systems. Current Building Management Systems (BMS) fail to optimize energy consumption of HVAC systems in commercial and educational buildings. In this paper we present an intelligent agent based system to optimize energy consumption of HVAC system in HEI buildings. The system employs artificial intelligence techniques to predict the demand of the system and optimize energy consumption of the HVAC system. The experimental results have shown that the deployment of the system has resulted in 3% reduction in energy consumption of HVAC. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码：958 / 965
页数：8
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