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Title: Smart grid analysis with particular references to power quality and load forecast
Author: Zhou, Long
ISNI:       0000 0004 2690 1456
Awarding Body: City University London
Current Institution: City, University of London
Date of Award: 2010
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The electricity industry was designed more than 50 years ago when the load and generation was less, now we are in the information age with a digital society where the demand is very high, this has forced the electricity infrastructure to its limits which was not designed for, in addition, the electricity demand continues to grow. So the focus of the question becomes what we need to do from technology prospective to meet that growing demand for electricity, and do it in a way that we don't create a greater carbon footprint. Smart grid is the next generation of the electricity infrastructure based on the optimisation of the current system in all levels. Since the current system is facing various problems from increasing disturbances, system is operating on the limit, aging equipments, load change etc. therefore an improvement is essential to minimize these problems. To enhance the current system and resolve the issues that it's facing, Smart grid must have the right tools to solve it and reduce it. First of all, this thesis gives a brief concept of smart grid and summarizes many issues about smart grid, such as strategy planning, drivers for develop the Smart Grid, key characteristics, technologies of the Smart Grid, benefits in implementing Smart Grid, key Challenges, implementation sequence. And then this thesis discusses smart metering system and its standards. Secondly, this thesis reports on development of a new approach to deal with power quality problem. Wavelet Transform (WT) is used for the new approach. Complex Morlet Wavelet (CMW) is selected for the new approach introduced in this thesis. The proposed algorithm is able to identify all harmonic components including integer, non-integer and sub-harmonics. Comparing with DFT, the proposed algorithm achieves exact estimation of the harmonic frequency. Thirdly, reports on the development of a WT-based dynamic waveform reconstruction algorithm which is able to identify amplitude variations of harmonic components of the distorted waveform in the examined period. At last, this thesis reports a new Wavelet-GA-ANN based hybrid model for accurate prediction of short-term load forecast. Finally, the conclusions and future work will be given.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TA Engineering (General). Civil engineering (General)