Demand-Driven Power Saving for HVAC System with Agent-Based Sensor Network in Buildings
Date Issued
2014
Date
2014
Author(s)
Tsao, Yi-ting
Abstract
Heating, Ventilation, and Air Conditioning (HVAC) systems account for 20% to 50% of power consumption in buildings. Reducing the power consumption of HVAC systems has become a popular issue with the growing concerns for energy conservation. This research focuses on demand-driven performance improvement of Building Energy Management Systems (BEMS)for the HVAC system in the Department of Computer Science and Information Engineering (CSIE) building at National Taiwan University (NTU).
Generally speaking, the functionality of BEMS consists of measurement, control, and power saving. This thesis proposes using cooling demand estimation as the basis for designing the energy saving mechanism. Three approaches to control are compared on human comfort, power consumption, and maintenance. The experimental results showed that the demand driven control approach saved 1.74% to 6.51% of power consumption in the daytime.
To overcome the problem due to climate differences, we apportion the electricity payment on demand by adjusting its price accordingly, We observe that demand-based apportionment may help reduce the power consumption during peak hours.
To mitigate the difficulty in fusing heterogeneous sensor data, an agent-based sensor network is constructed to provide an integrated interface for data access. A user study is conducted to show that the agent-based sensor network reduces data access time by about one third.
Subjects
節能
中央空調
多代理人
Type
thesis
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