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2nd CFP: EvoENERGY 2014

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  • Kaufmann Paul
    EvoENERGY 2014 Evolutionary Algorithms in Energy Applications 23-25 April 2014 - Baeza, Spain http://www.evostar.org INTRODUCTION Along with the worldwide
    Message 1 of 1 , Sep 23, 2013
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      EvoENERGY 2014
      Evolutionary Algorithms in Energy Applications
      23-25 April 2014 - Baeza, Spain
      http://www.evostar.org


      INTRODUCTION

      Along with the worldwide incentive to reduce fossil and nuclear based power
      generation, the number of distributed generators and other forms of
      distributed energy resources which are installed in power networks has been
      steadily increasing over the last years. This increased integration has
      triggered a transformation of the energy system and challenges the
      conventional operation of these networks.

      On a network level, this transformation requires new control and communication
      approaches, to guarantee the security of energy supplies as well as an optimal
      exploitation of available resources. On a generator level, advanced control
      strategies as well as morphological optimization (e.g., tuning of wind-blade
      design) can help to assure an optimal performance of the generator.

      EvoEnergy is intended as a platform for new, innovative computational
      intelligence and nature-inspired techniques in the domain of energy-related
      optimization research. We seek contributions ranging from new control concepts
      for decentralized generation, strategies for their coordination in the network
      to the morphological optimization of distributed generators.


      TOPICS

      Topics of interest include, but are not limited to, any of
      the following:
      - management of distributed generation and storage
      - evolutionary design and morphological optimization in energy systems
      - advanced distribution management system functionalities
      - Smart Grid monitoring and control
      - real time configurations of energy networks
      - distributed optimization in energy networks
      - grid planning and asset management
      - energy demand reduction through evolutionary design optimisation


      PUBLICATION DETAILS

      Accepted papers will appear in the proceedings of EvoStar, published in a
      volume of the Springer Lecture Notes in Computer Science, which will be
      available at the Conference.

      Submissions must be original and not published elsewhere. The submissions will
      be peer reviewed by at least three members of the program committee. The
      authors of accepted papers will have to improve their paper on the basis of
      the reviewers comments and will be asked to send a camera ready version of
      their manuscripts. At least one author of each accepted work has to register
      for the conference and attend the conference and present the work. The
      reviewing process will be double-blind, please omit information about the
      authors in the submitted paper.

      Submission format: Springer LNCS (see EvoENERGY web page)
      Page limit: 12 pages
      Submission page: http://myreview.csregistry.org/evoapps14/


      IMPORTANT DATES

      Submission deadline: 1 November 2013
      Notification:
      Camera ready:
      EvoENERGY: 23-25 April 2014


      CHAIRS

      Paul Kaufmann, University of Kassel, paul.kaufmann(at)gmail.com
      Kyrre Glette, University of Oslo, kyrrehg(at)ifi.uio.no


      CONFIRMED PROGRAM COMMITTEE

      Andy Tyrrell, University of York, UK
      Frank Neumann, University of Adelaide, AU
      Jan Ringelstein, Fraunhofer Institure for Wind Technology and Energy System Technology, Germany
      Kalyan Veeramachaneni, MIT Computer Science and Artificial Intelligence Laboratory, US
      Konrad Diwold, Fraunhofer Institure for Wind Technology and Energy System Technology, Germany
      Maizura Mokhtar, University of Central Lancashire, UK
      Martin Middendorf, University of Leipzig, Germany
      Peter Palensky, Austrian Institute of Technology, Austria
      Ralph Evins, Laboratory of Building Science and Technology, Empa, Switzerland
      Sanaz Mostaghim, Karlsruhe Institute of Technology, Germany
      Una-May O'Reilly, MIT Computer Science and Artificial Intelligence Laboratory, US
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