The first extensive reference on these important techniques The restructuring of the electric utility industry has created the need for a mechanism that can effectively coordinate the various entities in a power market, enabling them to communicate efficiently and perform at an optimal level. Communication and Control in Electric Power Systems, the first resource to address its subject in an extended format, introduces parallel and distributed processing techniques as a compelling solution to this critical problem. Drawing on their years of experience in the industry, Mohammad Shahidehpour and…mehr
The first extensive reference on these important techniques The restructuring of the electric utility industry has created the need for a mechanism that can effectively coordinate the various entities in a power market, enabling them to communicate efficiently and perform at an optimal level. Communication and Control in Electric Power Systems, the first resource to address its subject in an extended format, introduces parallel and distributed processing techniques as a compelling solution to this critical problem. Drawing on their years of experience in the industry, Mohammad Shahidehpour and Yaoyu Wang deliver comprehensive coverage of parallel and distributed processing techniques with a focus on power system optimization, control, and communication. The authors begin with theoretical background and an overview of the increasingly deregulated power market, then move quickly into the practical applications and implementations of these pivotal techniques. Chapters include: Integrated Control Center Information Parallel and Distributed Computation of Power Systems Common Information Model and Middleware for Integration Online Distributed Security Assessment and Control Integration, Control, and Operation of Distributed Generation Agent Theory and Power Systems Management e-Commerce of Electricity A ready resource for both students and practitioners, Communication and Control in Electric Power Systems proves an ideal textbook for first-year graduate students in power engineering with an interest in computer communication systems and control center design. Designers, operators, planners, and researchers will likewise appreciate its unique contribution tothe professional literature.
MOHAMMAD SHAHIDEHPOUR, PhD, is a professor in the Electrical and Computer Engineering Department and Director of the Electric Power and Power Electronics Center at the Illinois Institute of Technology, where he has served in various administrative positions, including Dean of the Graduate College and Associate Vice President for research. He has over twenty years of experience as a consultant to the electric power industry. He is the author of more than 250 technical papers as well as three books on power system optimization and energy scheduling. Dr. Shahidehpour is a Fellow of IEEE. YAOYU WANG, PhD, is a senior research scientist in the Electric Power and Power Electronics Center at the Illinois Institute of Technology. He has twelve years of industrial and academic experience in power systems computation, optimization, and control; power market analysis; and EMS/DMS applications, development, and integration. He was a recipient of a research fellowship from the Japan Society for the Promotion of Science, and was a guest research scientist of Germany's Alexander von Humboldt Foundation. Dr. Wang is a Senior Member of IEEE.
Inhaltsangabe
Preface.
1. Introduction.
2. Parallel and Distributed Processing of Power Systems.
3. Information System for Control Centers.
4. Common Information Model and Middleware for Integration.
5. Parallel and Distributed Load Flow Computation.
6. Parallel and Distributed Load Flow of DistributionSystems.
7. Parallel and Distributed State Estimation.
8. Distributed Power System Security Analysis.
9. Hierarchical and Distributed Control of Voltage/VAR.
10. Transmission Congestion Management Based on Multi-AgentTheory.
11. Integration, Control, and Operation of DistributedGeneration.
12. Special Topics in Power System Information System.
Appendix A. Example System Data.
Appendix B. Measurement Data for Distributed StateEstimation.
