Applied Mathematics for Restructured Electric Power Systems : Optimization, Control, and Computational Intelligence
Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence consists of chapters based on work presented at a National Science Foundation workshop organized in November 2003. The theme of the workshop was the use of applied mathematics to solve...
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Boston, MA :
Springer US
[20..].
Cham : Springer Nature |
| Schriftenreihe: | Power Electronics and Power Systems
|
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Anmerkung: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Applied Mathematics for Restructured Electric Power Systems, Texte imprimé, 9780387234700 |
Inhaltsangabe:
- Applied Mathematics for Restructured Electric Power Systems Reactive Power and Voltage Control Issues in Electric Power Systems Identification of Weak Locations in Bulk Transmission Systems Using Voltage Stability Margin Index Bifurcation and Manifold Based Approach for Voltage and Oscillatory Stability Assessment and Control On-Line ATC Evaluation for Large-Scale Power Systems: Framework and Tool Automating Operation of Large Electric Power Systems Over Broad Ranges of Supply/Demand and Equipment Status Robust Control of Large Power Systems VIA Convex Optimization Instability Monitoring and Control of Power Systems Dynamic Embedded Optimization and Shooting Methods for Power System Performance Assessment Computational Intelligence Techniques for Control of FACTS Devices Placement and Coordinated Tuning of Control Devices for Capacity and Security Enhancement Using Metaheuristics Load Forecasting Independent Component Analysis Techniques for Power System Load Estimation