Electric Power Systems: Advanced Forecasting Techniques and Optimal Generation Scheduling, 1st Edition (Paperback) book cover

Electric Power Systems

Advanced Forecasting Techniques and Optimal Generation Scheduling, 1st Edition

Edited by João P. S. Catalão

CRC Press

462 pages | 152 B/W Illus.

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Paperback: 9781138073982
pub: 2017-03-29
Hardback: 9781439893944
pub: 2012-03-07
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pub: 2017-12-19
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Electric Power Systems: Advanced Forecasting Techniques and Optimal Generation Scheduling helps readers develop their skills in modeling, simulating, and optimizing electric power systems. Carefully balancing theory and practice, it presents novel, cutting-edge developments in forecasting and scheduling. The focus is on understanding and solving pivotal problems in the management of electric power generation systems.

Methods for Coping with Uncertainty and Risk in Electric Power Generation

Outlining real-world problems, the book begins with an overview of electric power generation systems. Since the ability to cope with uncertainty and risk is crucial for power generating companies, the second part of the book examines the latest methods and models for self-scheduling, load forecasting, short-term electricity price forecasting, and wind power forecasting.

Toward Optimal Coordination between Hydro, Thermal, and Wind Power

Using case studies, the third part of the book investigates how to achieve the most favorable use of available energy sources. Chapters in this section discuss price-based scheduling for generating companies, optimal scheduling of a hydro producer, hydro-thermal coordination, unit commitment with wind generators, and optimal optimization of multigeneration systems.

Written in a pedagogical style that will appeal to graduate students, the book also expands on research results that are useful for engineers and researchers. It presents the latest techniques in increasingly important areas of power system operations and planning.

Table of Contents

Overview of Electric Power Generation Systems

Cláudio Monteiro

Uncertainty and Risk in Generation Scheduling

Rabih A. Jabr

Short-Term Load Forecasting

Alexandre P. Alves da Silva and Vitor H. Ferreira

Short-Term Electricity Price Forecasting

Nima Amjady

Short-Term Wind Power Forecasting

Gregor Giebel and Michael Denhard

Price-Based Scheduling for Gencos

Govinda B. Shrestha and Songbo Qiao

Optimal Self-Schedule of a Hydro Producer under Uncertainty

F. Javier Díaz and Javier Contreras

Hydrothermal Producer Self-Scheduling

Christos K. Simoglou, Pandelis N. Biskas, and Anastasios G. Bakirtzis

Unit Commitment and Economic Dispatch for Operations Planning of Power Systems with Significant Installed Wind Power Capacity

Barry G. Rawn, Madeleine Gibescu, Bart C. Ummels, Engbert Pelgram, and Wil L. Kling

Operational Optimization of Multigeneration Systems

Pierluigi Mancarella and Gianfranco Chicco


About the Editor

João P.S. Catalão received an MSc degree from the Instituto Superior Tecnico (IST), Lisbon, Portugal, in 2003 and a PhD from the University of Beira Interior (UBI), Covilha, Portugal, in 2007. He is currently a professor at UBI and a director of the Master Program in Electromechanical Engineering. His scientific area of interest at the Center for Innovation in Electrical and Energy Engineering (CIEEE), IST, is related to power and energy systems. He coordinates a research group in renewable energies and sustainability at UBI. He is an IEEE and an IET member, a senior member of the Portuguese Council of Engineers, and a member of the IASTED Technical Committee on Energy and Power Systems. He is the author/coauthor of more than 160 scientific papers, including 50 papers in international journals and 100 papers in conference proceedings. He is an editor of IEEE Transactions on Sustainable Energy, and an editorial board member of Electric Power Components and Systems.

For more information about Professor Catalão, see his web page at UBI.

Subject Categories

BISAC Subject Codes/Headings:
TECHNOLOGY & ENGINEERING / Electronics / General
TECHNOLOGY & ENGINEERING / Power Resources / Alternative & Renewable
TECHNOLOGY & ENGINEERING / Power Resources / Electrical