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Genetically Evolved Fuzzy Predictor for Photovoltaic Power Output Estimation

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6 Author(s)
Pavel Kromer ; Dept. of Comput. Sci., VSB Tech. Univ. of Ostrava, Ostrava, Czech Republic ; V´clav Snasel ; Jan Platos ; Ajith Abraham
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Fuzzy sets and fuzzy logic can be used for efficient data mining, classification, and value prediction. We propose a genetically evolved fuzzy predictor to estimate the output of a Photovoltaic Power Plant. Photovoltaic Power Plants (PVPPs) are classified as power energy sources with unstable supply of electrical energy. It is necessary to back up power energy from PVPPs for stable electric network operation. An optimal value of back up power can be set with reliable prediction models and significantly contribute to the robustness of the electric network and therefore help in the building of intelligent power grids.

Published in:

Intelligent Networking and Collaborative Systems (INCoS), 2011 Third International Conference on

Date of Conference:

Nov. 30 2011-Dec. 2 2011