Virtual Power Plants and Electricity Markets: Decision Making Under Uncertainty

ISBN-13: 9783030476045 / Angielski / Miękka / 2021 / 396 str.

Luis Baringo; Morteza Rahimiyan

Opis

This textbook provides a detailed analysis of operation and planning problems faced by virtual power plants participating in different electricity markets. The chapters address in-depth, topics such as: optimization, market power, expansion, and modelling uncertainty in operation and planning problems of virtual power plants. The book provides an up-to-date description of decision-making tools to address challenging questions faced by virtual power plants such as:

• How can virtual power plants optimize their participation in electricity markets?
• How can a virtual power plant exercise market power?
• How can virtual power plants be optimally expanded?
• How can uncertainty be efficiently modelled in the operation and planning problems of virtual power plants?

The book is written in a tutorial style and modular format, and includes many illustrative examples to facilitate comprehension. It is intended for a diverse audience including advanced undergraduate and graduate students in the fields of electric energy systems, operations research, and economics. Practitioners in the energy sector will also benefit from the concepts and techniques presented in this book. In particular, this book:

• Provides students with the GAMS codes to solve the examples in the book; 
• Provides a basis for the formulation of decision-making problems under uncertainty;
• Contains a blend of theoretical concepts and practical applications that are developed as working algorithms.

Spis treści

Virtual Power Plants.- Virtual Power Plant Model.- Optimal Scheduling of a Risk-Neutral Virtual Power Plant in Energy Markets.- Optimal Scheduling of a Risk-Averse Virtual Power Plant in Energy Markets.- Optimal Scheduling of a Virtual Power Plant in Energy and Reserve Markets.- Price-Maker Virtual Power Plants.- Expansion Planning of Virtual Power Plants.- Optimization Problems.- Optimization Under Uncertainty.

O autorze

Luis Baringo, Associate Professor at the Universidad de Castilla-La Mancha, Ciudad Real, Spain,

received the Industrial Engineering degree and the Ph.D. in Electrical Engineering from the

Universidad de Castilla-La Mancha, Spain, in 2009 and 2013, respectively. In 2014, he was a

postdoctoral researcher at the Power Systems Laboratory, ETH Zurich, Switzerland. He has

published over 20 papers in SCI journals and is the author of two textbooks published by Springer.

He is an IEEE Senior Member.

 

Morteza Rahimiyan, Associate Professor at the Shahrood University of Technology, Shahrood,

Iran, received the B.Sc. degree from the Isfahan University of Technology, Isfahan, Iran, in

2003, as well as the M.Sc. and the Ph.D. (with honors) from the Ferdowsi University of

Mashhad, Mashhad, Iran in 2006 and 2011, respectively, all in electrical engineering. In 2010,

he was a visiting researcher at the Universidad de Castilla-La Mancha, Ciudad Real, Spain. He

has published more than 15 papers in SCI journals. He is an IEEE Member.