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Power quality evaluation in smart grids considering modern distortion in electric power systems

机译：考虑现代电力系统失真的智能电网电能质量评估

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摘要

High power quality level is required in smart grids especially for non-stationary situations due to increased use of nonlinear loads and PQ disturbances such as dips, swells, transients and interruptions. Many power quality indices (PQIs) are available. In this paper a new fuzzy-wavelet packet transform-based power quality Index (FWPTPQI) is developed to amalgamate existing power quality indices as the output of a fuzzy based module based on fuzzy inference systems, knowledge base and existing PQ.I as input. Fuzzy systems allow handling the uncertainties associated with the electric power quality evaluation. The proposed approach has been applied to two case studies; stationary balanced and non-stationary unbalanced three-phase systems. The results are compatible with prevalent situations. The new index gives significant sense of the quality of transmitted electrical power. A comparative study of using different wavelet basis functions is considered and results indicate that Daubechies 10 and Daubechies 15 could be considered as the overall best wavelet basis functions. Since the new index represents an amalgamation of the PQ indices with less number of wavelet coefficients, it helps reduce the size of data processed which is required in smart grid applications.
机译：由于越来越多地使用非线性负载和PQ干扰（例如骤降，骤升，瞬变和中断），在智能电网中特别是在非平稳情况下需要高电能质量等级。许多电能质量指数（PQI）可用。本文基于模糊推理系统，知识库和现有的PQ.I作为输入，开发了一种新的基于模糊小波包变换的电能质量指标（FWPTPQI），以融合现有的电能质量指标作为基于模糊的模块的输出。模糊系统允许处理与电能质量评估相关的不确定性。提议的方法已应用于两个案例研究；固定的平衡和非平稳的不平衡三相系统。结果与普遍情况兼容。新指标使人们对所传输的电能的质量有了极大的了解。考虑使用不同的小波基函数的比较研究，结果表明，道贝基斯10和道贝基斯15可以被认为是总体上最佳的小波基函数。由于新索引表示PQ索引的合并，而小波系数的数量较少，因此有助于减小智能电网应用程序所需处理数据的大小。

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