Abstract
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.
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© 1995 Springer-Verlag London Limited
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Heine, S., Neumann, I. (1995). Analysis and Classification of Energy Requirement Situations Using Kohonen Feature Maps within a Forecasting System. In: Hunt, K.J., Irwin, G.R., Warwick, K. (eds) Neural Network Engineering in Dynamic Control Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-3066-6_11
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DOI: https://doi.org/10.1007/978-1-4471-3066-6_11
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