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Virtual Power Plants and Electricity Markets: Decision Making Under Uncertainty 2020 Edition
Contributor(s): Baringo, Luis (Author), Rahimiyan, Morteza (Author)
ISBN: 3030476014     ISBN-13: 9783030476014
Publisher: Springer
OUR PRICE:   $113.99  
Product Type: Hardcover
Published: September 2020
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Technology & Engineering | Machinery
- Technology & Engineering | Power Resources - Alternative & Renewable
- Business & Economics | Operations Research
Physical Information: 0.9" H x 8.5" W x 11.2" (2.40 lbs) 381 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

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.