Improvement of control function for energy management system
An Air-Conditioning and Mechanical Ventilation (ACMV) system is one of the most important technological advancements to arise from the industrial revolution. A building energy management system is involved in the control of all aspects of building automation and not only in the ACMV system, such con...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2017
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Online Access: | http://hdl.handle.net/10356/69517 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | An Air-Conditioning and Mechanical Ventilation (ACMV) system is one of the most important technological advancements to arise from the industrial revolution. A building energy management system is involved in the control of all aspects of building automation and not only in the ACMV system, such conformity is the main reason for its ubiquity. It is a software patch that works over the normal automation software which helps monitor and control the energy usage in the system. The building energy management system is heavily concerned with the working of the ACMV system since it is the major area of energy consumption.
The betterment of the control function for a building energy management system is the problem at hand. The technique followed to optimise the control function of the energy management system is by narrowing the outlook to the area of major energy consumption. The chiller is responsible for the majority of power consumption in the ACMV system, which in turn makes it the single largest contributor to the energy loss. In order to improve the performance of the energy management system the chiller staging algorithm is analysed for optimality. If the chiller staging algorithm employed is the most optimal then the overall energy consumption is drastically reduced.
The specific contribution to the realm of building energy management systems here is the focus strained on the chiller staging algorithm. The cooling load of a building is modelled as a function of a set of input parameters which can be chosen depending upon the weather conditions of the region and the sensors available in the building. The model is developed with the data from the BSTAR model development in Nanyang Technological University. The staging data obtained from the predicted cooling load is then analysed to determine if the staging algorithm implemented is optimal in nature. Thus verification of the chiller staging algorithm leads to the use of the optimal algorithm, which in turn improves the functioning of the control system of the building energy management system.
This method is different from other such existing techniques in that it can be easily implemented and can be adapted to suit different kinds of structures. The basic framework is such that improvements to suit specific applications can be implemented easily. The model is developed using four different techniques to provide a choice for the user so as to utilise the best model for the system under consideration. This improvement to the energy management system tackles the problem at its root and improves the overall efficacy of the same a lot more effectively than its contemporary solutions. |
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