Advanced Control and Analysis of Wind and Solar Energy Systems

Steven Yi-Chi Kong (2011). Advanced Control and Analysis of Wind and Solar Energy Systems PhD Thesis, School of Information Technol and Elec Engineering, The University of Queensland.

       
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s4027864_phd_abstract.pdf abstract Click to show the corresponding preview/stream application/pdf 59.87KB 7
s4027864_phd_finalThesis.pdf thesis Click to show the corresponding preview/stream application/pdf 7.71MB 21
Author Steven Yi-Chi Kong
Thesis Title Advanced Control and Analysis of Wind and Solar Energy Systems
School, Centre or Institute School of Information Technol and Elec Engineering
Institution The University of Queensland
Publication date 2011-11
Thesis type PhD Thesis
Supervisor Dr. Ramesh Bansal
Prof. Zhao Yang Dong
Dr. David Cornforth
Total pages 161
Total colour pages 28
Total black and white pages 133
Language eng
Subjects 09 Engineering
Abstract/Summary This research project investigates and analyses the impact of wind energy on power system networks as well as implementation of advanced controls in renewable energies of wind and solar power technologies. The analysis of wind turbine system includes small signal stability study of different turbine technologies available on the market today. Implementation of advanced control strategy for wind power is also investigated to provide improved power generation as well as mitigation of electrical and mechanical transients. The proposed advanced control strategy is a H∞ rotor side control (RSC) implementation specifically for doubly fed induction generators (DFIG), which replaces the standard RSC proportional integral (PI) control strategies. Analysis and simulation between the proposed and conventional control strategies in terms of electrical and mechanical damping are provided as well as validation in NREL’s Fatigue, Aerodynamics, Structures and Turbulence (FAST) model to verify the performance of proposed control strategy. Solar inverter technology has also been investigated in this project as part of the industrial research at CSIRO. The main driver behind the initiative is to develop an inverter control algorithm that would enable auto- islanding capabilities for a microgrid system as!well!as!to!provide stable and efficient power transfers within the whole network. In this work, genetic algorithm is applied to inverter control design and validated with computer simulation studies. The results suggested the genetic evolutionary approach for designing a controller for multiple inverter systems is an effective tool to determine control parameters as well as providing superior transient performances.
Keyword Power system stability, small signal stability, eigenvalues, damping controller, wind energy conversion systems, wind farms, wind turbines, doubly fed induction generator (DFIG), squirrel cage induction generator (SCIG), permanent magnet synchronous generator (PMSG), microgrid, inverter, genetic algorithm (GA).
Additional Notes colour: 52,55-57,59-62,64-65,67,93-95,102-109,118-123 landscape:148-153

 
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Created: Tue, 15 Nov 2011, 10:54:14 EST by Mr Steven Kong on behalf of Library - Information Access Service