UID:
almahu_9949225685602882
Format:
1 online resource (490 p.)
ISBN:
0-323-16305-X
Content:
Control and Dynamic Systems V41: Analysis and Control System Techniques for Electric Power Systems Part 1 of 4
Note:
Description based upon print version of record.
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Front Cover; Analysis and Control System Techniques for Electric Power Systems, Part 1 of 4; Copyright Page; Table of Contents; CONTRIBUTORS; PREFACE; CHAPTER 1. MODERN APPROACHES TO MODELING AND CONTROL OF ELECTRIC POWER SYSTEMS; I. INTRODUCTION; II. TRADITIONAL VIEW; III. POWER SYSTEMS OF TODAY; IV. ELECTRIC POWER SYSTEMS OF THE FUTURE-FLEXIBLE AC TRANSMISSION SYSTEMS (FACTS); V. CONCLUSIONS - POTENTIAL ROLE OF FACTS DEVICES IN IMPLEMENTING MOST EFFECTIVE CONTROLS; REFERENCES; CHAPTER 2. DYNAMIC STATE ESTIMATION TECHNIQUES FOR LARGE-SCALE ELECTRIC POWER SYSTEMS; 1 INTRODUCTION
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2 PROBLEM FORMULATION AND OVERVIEW OF SOLUTIONS3 THE PROPOSED METHOD; 4 PROSPECTIVE REAL-TIME APPLICATIONS; 5 EXPERIMENTAL EVALUATION; 6 CONCLUSION; 7 REFERENCES; CHAPTER 3. OPTIMAL POWER FLOW ALGORITHMS; 1 PROBLEM DEFINITION; 2 HISTORICAL REVIEW OF OPF DEVELOPMENT; 3 CLASSIFICATION OF ALGORITHMS TO ACHIEVE OPF OPTIMALITY CONDITIONS; 4 OPF CLASS A:POWER FLOW SOLVED SEPARATELY FROM OPTIMIZATION ALGORITHM; 5 OPF CLASS B . POWER FLOW INTEGRATEDIN OPTIMIZATION ALGORITHM; 6 FINAL EVALUATION OF THE METHODS; A APPENDIX; References; CHAPTER 4. SPARSITY IN LARGE-SCALE NETWORK COMPUTATION
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I. A Historical Introduction to SparsityII. Sparse Matrix Structures; III. Basic Sparse Matrix Operations; IV. Sparse-Vector Operations; V. Inverse Elements And The Sparse Inverse; VI. Matrix Modifications; VII. Reductions and Equivalents; VIII. Approximate Sparse-Vector Techniques; IX. Compensation; X. Parallel Processing; XI. Applications; XII. Concluding Remarks; References; CHAPTER 5. TECHNIQUES FOR DECENTRALIZED CONTROL FOR INTERCONNECTED SYSTEMS; I. INTRODUCTION; II. DECENTRALIZED STABILIZATION VIA LOCAL STATE FEEDBACK; III. OBSERVER-BASED DECENTRALIZED STABILIZATION; IV. CONCLUSIONS
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APPENDIX A. DERIVATION OF Eq.(12)APPENDIX B. PROOF OF Lemma 1; APPENDIX C. PROOF OF Theorem 3; APPENDIX D. PROOF OF Corollary 1; References; CHAPTER 6. KNOWLEDGE BASED SYSTEMS FOR POWER SYSTEM SECURITY ASSESSMENT; I. INTRODUCTION; II. POWER SYSTEM SECURITY ASSESSMENT; III. APPLYING KNOWLEDGE BASED SYSTEMS; IV. CQR, AN EXPERT SYSTEM THAT ASSESSES SECURITY; V. CONCLUSION; References; Chapter 7. Neural Networks and Their Application to Power Engineering; 1 Introduction; 2 A Brief History of Neural Networks; 3 Neural Network Paradigms; 4 Learning; 5 Neural Network Implementation
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6. Selected Applications to Power Systems**References; INDEX
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English
Additional Edition:
ISBN 0-12-012741-5
Language:
English
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