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Renewable Energy: Forecasting and Risk Management

Paris, France, June 7-9, 2017

  • Philippe Drobinski
  • Mathilde Mougeot
  • Dominique Picard
  • Riwal Plougonven
  • Peter Tankov
Conference proceedings FRM 2017

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 254)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Renewable Energy: Modeling and Forecasting

    1. Front Matter
      Pages 1-1
    2. Bastien Alonzo, Riwal Plougonven, Mathilde Mougeot, Aurélie Fischer, Aurore Dupré, Philippe Drobinski
      Pages 23-44
    3. Mireille Bossy, Aurore Dupré, Philippe Drobinski, Laurent Violeau, Christian Briard
      Pages 45-71
    4. Jordi Badosa, Emmanuel Gobet, Maxime Grangereau, Daeyoung Kim
      Pages 73-93
    5. Mathilde Mougeot, Dominique Picard, Vincent Lefieux, Miranda Marchand
      Pages 95-118
    6. Andrés Castrillejo, Jairo Cugliari, Fernando Massa, Ignacio Ramirez
      Pages 119-136
    7. Jérôme Collet, Michael Richard
      Pages 147-166
  3. Renewable Energy: Risk Management

    1. Front Matter
      Pages 167-167
    2. Vera Silva, Miguel López-Botet Zulueta, Ye Wang, Paul Fourment, Timothee Hinchliffe, Alain Burtin et al.
      Pages 169-184 Open Access
    3. Jérôme Collet, Olivier Féron, Peter Tankov
      Pages 229-246

About these proceedings

Introduction

Gathering selected, revised and extended contributions from the conference ‘Forecasting and Risk Management for Renewable Energy FOREWER’, which took place in Paris in June 2017, this book focuses on the applications of statistics to the risk management and forecasting problems arising in the renewable energy industry. The different contributions explore all aspects of the energy production chain: forecasting and probabilistic modelling of renewable resources, including probabilistic forecasting approaches; modelling and forecasting of wind and solar power production; prediction of electricity demand; optimal operation of microgrids involving renewable production; and finally the effect of renewable production on electricity market prices. Written by experts in statistics, probability, risk management, economics and electrical engineering, this multidisciplinary volume will serve as a reference on renewable energy risk management and at the same time as a source of inspiration for statisticians and probabilists aiming to work on energy-related problems.

Keywords

Modeling / forecasting / statistics for wind and solar energy Risk management of renewable energy production Microgrid / storage management Probabilistic forecasting Spatio-temporal statistics Proceedings

Editors and affiliations

  • Philippe Drobinski
    • 1
  • Mathilde Mougeot
    • 2
  • Dominique Picard
    • 3
  • Riwal Plougonven
    • 4
  • Peter Tankov
    • 5
  1. 1.Laboratoire de Méteorologie DynamiqueCNRSPalaiseauFrance
  2. 2.UFR de MathématiquesUniversité Paris DiderotParisFrance
  3. 3.UFR de MathématiquesUniversité Paris DiderotParisFrance
  4. 4.Laboratoire de Météorologie DynamiqueEcole PolytechniquePalaiseauFrance
  5. 5.CREST—ENSAE Paris TechPalaiseauFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-99052-1
  • Copyright Information Springer Nature Switzerland AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-99051-4
  • Online ISBN 978-3-319-99052-1
  • Series Print ISSN 2194-1009
  • Series Online ISSN 2194-1017
  • Buy this book on publisher's site