基于深层次挖掘算法的台区供电相位分析方法

在台区供电相位分析中,传统的分析方法面对由杂乱数据过多造成的频率密集、含有偶次谐波或间谐波的情况,稳定性极差。为此提出基于深层次挖掘算法的台区供电相位分析方法。利用挖掘算法挖掘出台区用电数据关联规则,清除无用数据,使用数据信号频率合成技术合成信号;利用傅里叶变换获得全相位输入数据,通过相移量补偿相位差,再计算出振幅、相位和频率,实现台区供电相位分析。实验结果表明,在相同的实验条件下,设计的基于深层次挖掘算法的台区供电相位分析方法抗噪声性能强,参数误差小,稳定性高,适合应用在实际项目中。

Phase analysis method of power supply in substation area based on deep mining algorithm

For the phase analysis of power supply in substation area,the stability of the traditional analysis method is very poor when the frequency is dense and even harmonics or interharmonics are contained due to too much random data.Therefore,a phase analysis method based on deep mining algorithm is proposed.The mining algorithm is used to mine the association rules of power consumption data in the issued area,eliminate the useless data,and use the data signal frequency synthesis technology to synthesize the signal;the Fourier transform is used to obtain all phase input data,and the phase difference is compensated by the phase shift,and then the amplitude,phase and frequency are calculated to realize the phase analysis of power supply in the substation area.The experimental results show that,under the same experimental conditions,the power supply phase analysis method based on deep mining algorithm has strong anti-noise performance,small parameter error and high stability,which is suitable for practical projects.