Genetically Evolved Fuzzy Predictor for Photovoltaic Power Output Estimation

P. Krömer, V. Snás̃el, J. Platoš, A. Abraham, L. Prokop, S. Mišák
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引用次数: 20

Abstract

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.
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光伏发电输出估计的遗传进化模糊预测器
模糊集和模糊逻辑可以用于有效的数据挖掘、分类和价值预测。我们提出了一个遗传进化模糊预测器来估计光伏电站的输出。光伏电站被归类为电能供应不稳定的电力能源。为保证电网的稳定运行,需要从光伏电站中备份电能。通过建立可靠的预测模型,确定备用功率的最优值,可以显著提高电网的鲁棒性,从而有助于智能电网的建设。
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