Analysis and Classification of Energy Requirement Situations Using Kohonen Feature Maps within a Forecasting System

  • Steffen Heine
  • Ingo Neumann
Part of the Advances in Industrial Control book series (AIC)


Improving the accuracy of the electrical energy demand forecasting in the short term range up to seven days can decrease the operation costs of the energy system significantly by the following optimising of the energy management. Because of the different objectives of energy management in different energy systems a considerable amount of engineering power is necessary to build a forecast model for each application case. The efficiency of using the Kohonen Feature Map for a stepwise automatisation of this process is discussed by means of two application cases. Finally, the embedding of the new analysis capability in a modular-constructed forecasting system is presented.


Artificial Neural Network Input Space Forecast System Unit Commitment Load Demand 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 1995

Authors and Affiliations

  • Steffen Heine
    • 1
  • Ingo Neumann
    • 1
  1. 1.Best Data Engineering GmbH BerlinBerlinGermany

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