Metaheuristics for Intelligent Electrical Networks

Table of contents

1. Cover
2. Title
3. Copyright
4. Introduction
5. 1 Single Solution Based Metaheuristics
   1. 1.1. Introduction
   2. 1.2. The descent method
   3. 1.3. Simulated annealing
   4. 1.4. Microcanonical annealing
   5. 1.5. Tabu search
   6. 1.6. Pattern search algorithms
   7. 1.7. Other methods
   8. 1.8. Conclusion
6. 2 Population-based Methods
   1. 2.1. Introduction
   2. 2.2. Evolutionary algorithms
   3. 2.3. Swarm intelligence
   4. 2.4. Conclusion
7. 3 Performance Evaluation of Metaheuristics
   1. 3.1. Introduction
   2. 3.2. Performance measures
   3. 3.3. Statistical analysis
   4. 3.4. Literature benchmarks
   5. 3.5. Conclusion
8. 4 Metaheuristics for FACTS Placement and Sizing
   1. 4.1. Introduction
   2. 4.2. FACTS devices
   3. 4.3. The PF model and its solution
   4. 4.4. PSO for FACTS placement
   5. 4.5. Application to the placement and sizing of two FACTS
   6. 4.6. Conclusion
9. 5 Genetic Algorithm-based Wind Farm Topology Optimization
   1. 5.1. Introduction
   2. 5.2. Problem statement
   3. 5.3. Genetic algorithms and adaptation to our problem
   4. 5.4. Application
   5. 5.5. Conclusion
10. 6 Topological Study of Electrical Networks
    1. 6.1. Introduction
    2. 6.2. Topological study of networks
    3. 6.3. Topological analysis of the Colombian electrical network
    4. 6.4. Conclusion
11. 7 Parameter Estimation of α-Stable Distributions
    1. 7.1. Introduction
    2. 7.2. Lévy probability distribution
    3. 7.3. Elaboration of our non-parametric α-stable distribution estimator
    4. 7.4. Results and comparison with benchmarks
    5. 7.5. Conclusion
12. 8 SmartGrid and MicroGrid Perspectives
    1. 8.1. New SmartGrid concepts
    2. 8.2. Key elements for SmartGrid deployment
    3. 8.3. SmartGrids and components technology architecture
13. Appendix 1
    1. A1.1. Test functions
14. Appendix 2
    1. A2.1. Application to the multi-objective case
15. Bibliography
16. Index
17. End User License Agreement