基于前馈神经网络的电网基波高精度检测High Precision Detection of Fundamental of Power Grid Based on Back Propagation Neural Network
王勇;付志红;张淮清;王好娜;侯兴哲;
摘要(Abstract):
电网基波是电能计量和电能质量评估的重要指标,提出了基于前馈神经网络的电网基波频率和幅值的高精度检测方法。根据数学推导得出:正弦信号过零点与其两侧对称两点的连线与时间轴交点的时间差,同频率满足单调关系,但并非严格的线性关系,而且与幅值无关,据此用前馈神经网络建立该时间差与频率的映射关系。Matlab仿真表明,提出的算法对频率的检测精度达到10?4级,幅值的检测精度高达10?5级,远远高于快速傅里叶变换和Hanning窗的插值算法;随机噪声和谐波对前馈神经网络测量精度的影响很小,该算法具有较强的抗干扰能力。
关键词(KeyWords): 电网基波;前馈神经网络;基波频率;基波幅值
基金项目(Foundation): 国家自然科学基金项目(40874094)~~
作者(Author): 王勇;付志红;张淮清;王好娜;侯兴哲;
Email:
DOI: 10.13335/j.1000-3673.pst.2011.08.007
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