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Virtual Power Plants and Electricity Markets : Decision Making Under Uncertainty

By: Luis Baringo (Author) , Morteza Rahimiyan (Author)

Extended Catalogue

Ksh 15,950.00

Format: Paperback or Softback

ISBN-10: 3030476049

ISBN-13: 9783030476045

Edition statement: 2020 ed.

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 4th, 2021

Publication Status: Active

Product extent: 381 Pages

Weight: 960.00 grams

Dimensions (height x width x thickness): 27.90 x 20.80 x 2.40 cms

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This textbook provides a detailed analysis of operation and planning problems faced by virtual power plants participating in different electricity markets.

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.



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