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  • Textbook
  • © 2014

Integrating Renewables in Electricity Markets

Operational Problems

  • First book to offer operations modeling of renewable electricity sources like wind and solar
  • Conejo is the most prominent name in the field of electricity modeling
  • End of chapter exercises, with ancillaries on the web
  • Includes supplementary material: sn.pub/extras

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 205)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xvi
  2. Introduction

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 1-13
  3. Renewable Energy Sources—Modeling and Forecasting

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 15-56
  4. Clearing the Day-Ahead Market with a High Penetration of Stochastic Production

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 57-100
  5. Balancing Markets

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 101-136
  6. Managing Uncertainty with Flexibility

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 137-171
  7. Impact of Stochastic Renewable Energy Generation on Market Quantities

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 173-203
  8. Trading Stochastic Production in Electricity Pools

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 205-242
  9. Virtual Power Plants

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 243-287
  10. Facilitating Renewable Integration by Demand Response

    • Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
    Pages 289-329
  11. Back Matter

    Pages 331-429

About this book

This addition to the ISOR series addresses the analytics of the operations of electric energy systems with increasing penetration of stochastic renewable production facilities, such as wind- and solar-based generation units.

As stochastic renewable production units become ubiquitous throughout electric energy systems, an increasing level of flexible backup provided by non-stochastic units and other system agents is needed if supply security and quality are to be maintained.

Within the context above, this book provides up-to-date analytical tools to address challenging operational problems such as:

• The modeling and forecasting of stochastic renewable power production.
• The characterization of the impact of renewable production on market outcomes.
• The clearing of electricity markets with high penetration of stochastic renewable units.
• The development of mechanisms to counteract the variability and unpredictability of stochastic renewable units so that supply security is not at risk.
• The trading of the electric energy produced by stochastic renewable producers.
• The association of a number of electricity production facilities, stochastic and others, to increase their competitive edge in the electricity market.
• The development of procedures to enable demand response and to facilitate the integration of stochastic renewable units.

This book is written in a modular and tutorial manner and includes many illustrative examples to facilitate its comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, applied mathematics and economics. Practitioners in the electric energy sector will benefit as well from the concepts and techniques explained in this book.

Authors and Affiliations

  • DTU Compute, Technical University of Denmark, Lyngby, Denmark

    Juan M. Morales, Henrik Madsen, Pierre Pinson, Marco Zugno

  • University of Castilla - La Mancha, Ciudad Real, Spain

    Antonio J. Conejo

About the authors

Juan M. Morales received his M.Sc. degree in Industrial Engineering from the University of Málaga and his Ph.D. in Electrical Engineering from the University of Castilla – La Mancha, Spain. Since 2013 he is an associate professor in Stochastic Optimization in Energy Systems in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark. His research interests include mathematical programming and techniques of optimization under uncertainty, decision making, hierarchical optimization, renewable energies and energy economics.

Antonio J. Conejo received the M.S. degree from Massachusetts Institute of Technology, Cambridge, MA, in 1987 and the Ph.D. degree from the Royal Institute of Technology, Stockholm, Sweden, in 1990. He is currently Professor of Electrical Engineering at the Universidad de Castilla – La Mancha, Ciudad Real, Spain.

Henrik Madsen received his M.Sc. (1982) and PhD (1986) in Statistics from the Technical University of Denmark (DTU). His research interests include forecasting of wind and solar power, time series analysis, and estimation of parameters in stochastic differential equations for physical modeling. Since 1999 he has been a full professor in Stochastic Dynamical Systems.

Pierre Pinson received his M.Sc. in Applied Mathematics from the National Institute of Applied Sciences, Toulouse, and his Ph.D. in Energetics from the Ecole des Mines de Paris. He is the Professor in Modelling of Electricity Markets at the Technical University of Denmark, Dpt. of Electrical Engineering. His research interests include statistical modelling; forecasting; stochastic optimization; decision making under uncertainty; renewable energies; meteorology; energy management; and energy trading.

Marco Zugno received the M.Sc. degree in Electrical Engineering from the Technical University of Denmark (DTU) and the M.Sc. degree in Automation Engineering from the University of Padua, Italy. He holdsa Ph.D. degree obtained from the department of Applied Mathematics and Computer Science at DTU. He is currently a postdoctoral researcher with the same department. His research interests include electricity market modeling; stochastic programming; robust optimization; and hierarchical optimization.

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access