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Photovoltaic Power Station Electromagnetic Environment Complexity Evaluation Utilizing Logarithmic Morphological Gradient Spectrum
Frontiers in Energy Research ( IF 2.6 ) Pub Date : 2021-06-23 , DOI: 10.3389/fenrg.2021.713501
Hua-chen Xi , Bing Li , Wen-hui Mai , Xiong Xu , Ya Wang

In this paper, a feature extraction method for evaluating the complexity of the Electromagnetic Environment (EME) of the photovoltaic power station is presented by using logarithmic morphological gradient spectrum (LMGS) based on the mathematical morphological theory. We use LMGS to evaluate electromagnetic environment signals. We also explored the impact of structure element (SE) on the MS, MGS and LMGS. Three types of SE, mean the line SE, square SE and diamond SE, are utilized and compared for computing the LMGS. EME signals with four complexity degrees are simulated to evaluate the effectiveness of the presented method. The experimental results have shown that the feature extraction scheme proposed in this paper is a reasonable method to classify the complexity of EME.

中文翻译:

基于对数形态梯度谱的光伏电站电磁环境复杂度评价

本文基于数学形态学理论,提出了一种利用对数形态梯度谱(LMGS)评估光伏电站电磁环境(EME)复杂性的特征提取方法。我们使用 LMGS 来评估电磁环境信号。我们还探讨了结构元素 (SE) 对 MS、MGS 和 LMGS 的影响。三种类型的 SE,即直线 SE、方形 SE 和菱形 SE,用于计算 LMGS 并进行比较。模拟具有四个复杂度的 EME 信号以评估所提出方法的有效性。实验结果表明,本文提出的特征提取方案是一种合理的EME复杂度分类方法。
更新日期:2021-06-23
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