ELECTRIC POWER GENERATION, Second Edition: TRANSMISSION AND DISTRIBUTION, Edition 2

SINGH, S. N.

июнь 2008 г. · PHI Learning Pvt. Ltd.

Об электронной книге

This accessible text, now in its Second Edition, continues to provide a comprehensive coverage of electric power generation, transmission and distribution, including the operation and management of different systems in these areas. It gives an overview of the basic principles of electrical engineering and load characteristics and provides exhaustive system-level description of several power plants, such as thermal, electric, nuclear and gas power plants. The book fully explores the basic theory and also covers emerging concepts and technologies. The conventional topics of transmission subsystem including HVDC transmission are also discussed, along with an introduction to new technologies in power transmission and control such as Flexible AC Transmission Systems (FACTS). Numerous solved examples, inter-spersed throughout, illustrate the concepts discussed.

What is New to This Edition :

Provides two new chapters on Diesel Engine Power Plants and Power System Restructuring to make the students aware of the changes taking place in the power system industry.

Includes more solved and unsolved problems in each chapter to enhance the problem solving skills of the students.

Primarily designed as a text for the undergraduate students of electrical engineering, the book should also be of great value to power system engineers.

Об авторе

S. N. Singh (M.Tech. and Ph.D. in Electrical Engineering from IIT Kanpur) is Professor in the Department of Electrical Engineering, IIT Kanpur. Earlier, he taught at the University of Roorkee (now IIT Roorkee), Asian Institute of Technology, Bangkok, and Denmark Technical University. He is a recipient of the Humboldt Fellowship of Germany and Otto Mønsted Fund of Denmark Research. His research interests include power system restructuring, FACTS, power system optimization and control, security analysis, power system planning, artificial neural network, genetic algorithms and power system transient stability.