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Abstract

Power substations can be considered the major component of an electric power transmission system, influencing the reliability, security and efficiency of all functions of the system. The idea of "intelligent sub-stations" is the main theme of this thesis.

First of all, a distributed monitoring system was developed so that the concept of sub-station automation could be realised. The monitoring system was successful in interfacing all major components inside a sub-station using simple hardware and off-the-shelf personal computers. This system formed the foundation of all subsequent research work described in this thesis. It was further developed to possess two outstanding functions, namely computer vision and Internet access. Using computer vision, the human operators in the central control centre were able to get the full picture of what happened in the sub-station with full confidence under a real-time mode. With Internet access, relevant information could be made available to all personnel concerned with the normal operation and maintenance and ad hoc emergency fault attendance as well.

With this basic hardware and software being successfully implemented in three sub-stations in Hong Kong, advanced features involving techniques in artificial intelligence were employed for enhancing the existing functions of the distributed monitoring system. Fuzzy logic was extensively applied for reactive power control and power harmonics signature recognition. The response and accuracy of reactive power control which was so important in maintaining a constant voltage level of the power system could be improved. With power harmonics signature recognition, the concept of power quality control could be realised as this problem was getting more and more serious as power electronics equipment was extensively utilised. Artificial neural networks were employed to evaluate the harmonics spectra of the power line, which could be a useful partner to the fuzzy system. The fundamental frequency could be evaluated on a real-time basis. The artificial neural networks were extended from the conventional real space into the complex space which saw great application in power system analysis. Finally, evolutionary programming was used to estimate the parameters of rotating machines during the state of transient operation. With the modem field oriented control strategy, accurate parameter estimation was more and more demanding. Further to that, parameter estimation could be a useful aid to the policy of condition based maintenance which was widely used in the power industry.

As future research work, preliminary studies on the application of thermography in power sub-stations and virtual reality were carried out. A brief report on these studies is included in the concluding chapter. As a final remark, the systems described in this thesis may also be useful to aid the successful implementation of the policy of deregulation of power systems in the future.

Publication Type:	Thesis (Doctoral)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments:	School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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