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The quality of data and the accuracy of energy generation forecast by artificial neural networks

Kwiatkowski, BogdanBartman, JacekMazur, Damian
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Agustus 2020
DOI10.11591/ijece.v10i4.pp3957-3966

Abstrak

The paper presents the issues related to predicting the amount of energy generation, in a particular wind power plant comprising five generators located in south-eastern Poland. The location of wind power plant, the distribution and type of applied generators, and topographical conditions were given and the correlation between selected weather parameters and the volume of energy generation was discussed. The primary objective of the paper was to select learning data and perform forecasts using artificial neural networks. For comparison, conservative forecasts were also presented. Forecasts results obtained shaw that Artificial Neural Networks are more universal than conservative method. However their forecast accuracy of forecasts strongly depends on the selection of explanatory data

Kata Kunci

Electrical engeenering, Informaticsforecastingwind energy generationartificial neural networkswind farmprediction

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The quality of data and the accuracy of energy generation forecast by artificial neural networks | International Journal of Electrical and Computer Engineering (IJECE) | Publiora