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Abstract
This research book presents intelligent computational techniques and
recommends preventive control measures for vulnerability assessment
and control of large scale interconnected power systems. The research
book begins with the investigation and by comparing the performance
of the proposed vulnerability index with other indices used for assessing
the vulnerability of power systems when subjected to various
contingencies. Cl is then considered by using artificial neural network
for vulnerability assessment and neuro-fuzzy technique for vulnerability
control of power systems. In the vulnerability assessment, power
system loss is proposed as a new vulnerability index, neural network
weight extraction is used as a new feature extraction method and the
radial basis function neural network is used to predict vulnerability of
power systems. As for vulnerability control, load shedding based on the
use of neuro-fuzzy technique is proposed. All the proposed methods
were tested and verified on the IEEE 24 bus test system, the IEEE 300
bus test system and a practical 87- bus power system. Simulations were
carried out using the Power System Analysis Toolbox (Milano 2005,
2006) and the development of computational intelligent techniques
were implemented in Matlab version 7. Finally, the research book
presents and discusses the results from this research with
recommendations.
Chapter
| Chapter 01 : Introduction |
| Chapter 02 : Literature Review |
| Chapter 03 : Indices For Vulnerability Assessment Of Power Systems |
| Chapter 04 : Vulnerability Assessment Of Power System Using Atificial Neural Networks |
| Chapter 05 : Feature Extraction Methods For Vulnerability Assessment |
| Chapter 06 : Vulnerability Control Of Power System Using Fuzzy And Neuro-Fuzzy Based Load Shedding |
| Chapter 07 : Results And Discussions |
| Chapter 08 : Conclusion And Suggestions For Future Work |
