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A Fuzzy Rule Base Approach for Intelligent Protection of Microgrids

机译：微电网智能保护的模糊规则库方法

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摘要

The proposed work develops a decision tree-induced fuzzy rule base intelligent protection scheme for fault detection and classification in a microgrid with multiple distributed generation interfaces. The proposed protection scheme retrieves one cycle post-fault current signal samples of each phase from fault inception at bus ends of the respective feeder to derive some differential features. The retrieved current samples are pre-processed using S-transform to obtain a time-frequency contour. The statistical features, such as energy, mean, standard deviation, and entropy, are computed from the time-frequency contour, which is further used to calculate the differential features. The differential features are used to build the fault classification tree. From the decision tree classification boundaries, the fuzzy membership functions are drawn, and further, the corresponding fuzzy rule base is generated for the final relaying decision. The proposed scheme is developed on a MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA) platform, including wide variations in faulted conditions, and the extensive test results indicate that the proposed intelligent relaying scheme can reliably provide protection measures for microgrids with different modes of operation.
机译：拟议的工作开发了决策树诱导的模糊规则库智能保护方案，用于在具有多个分布式生成接口的微电网中进行故障检测和分类。所提出的保护方案从相应馈线的总线端的故障开始检索每个相的一个周期的故障后电流信号样本，以得出一些差分特征。使用S变换对检索到的当前样本进行预处理，以获得时频轮廓。根据时频轮廓计算统计特征，例如能量，均值，标准差和熵，该统计特征可进一步用于计算微分特征。差异特征用于构建故障分类树。从决策树分类边界，绘制模糊隶属度函数，并进一步为最终的中继决策生成相应的模糊规则库。所提出的方案是在MATLAB / SIMULINK（美国马萨诸塞州内蒂克市的MathWorks公司）平台上开发的，其中包括故障条件的广泛变化，广泛的测试结果表明，所提出的智能中继方案可以可靠地为具有不同故障的微电网提供保护措施。操作模式。

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