【作者】 高瑛；

【导师】 杨洪耕；

【作者基本信息】 四川大学 ， 电力系统及其自动化， 2005， 硕士

【摘要】 随着我国现代工业技术和国民经济的飞速发展,电能质量已经成为电力系统发、供、用电部门十分关注,并且去刻意完善的重要指标。随着我国电力市场化改革的积极推进与逐步形成,电力部门不但要满足用户对电力数量的不断增长的需求,还必须满足较高电能质量的要求。 为了有效提高电能质量,我们必须对电能质量扰动源进行研究。对各种电能质量扰动现象进行分析,是采取适当措施降低扰动带来影响的前提。因此对电力系统扰动现象的分析、识别和分类具有重要的理论意义和现实意义。本文提出了一种新的电能质量的时频域综合分析方法。,根据频域的小波分析法和时域的瞬时负荷特性法对电力系统电能质量扰动现象进行有效、准确识别和分类。 作为最经典的信号处理手段的傅立叶分析,对被分析信号的幅值变化相当的敏感。根据这一特点,本文运用快速傅立叶变换(FFT)对波形失真的电力系统扰动现象进行傅立叶分析,可以准确对其类型进行识别。与此同时,还对短时电压扰动、长时电压扰动初步的提取其幅值特征。 类似电压凹陷、电压膨胀、欠电压等电力系统短时电压扰动、长时电压扰动,其主要特征信息集中在幅值和持续时间上,所以适合运用时域分析法对其进行特征信息分量的提取。本文主要采用了瞬时负荷特性法对短时电压扰动、长时电压扰动进行时域分析,通过计算瞬时负荷的模拟参数(模拟电阻R及模拟电抗L),然后计算出由模拟参数重构出的计算电压;比较计算电压与实际采样电压信号。求取信号的偏离因子。通过对偏离因子的分析对扰动出现的起、止位置进行准确判定,从而对扰动信号进行准确的分类。 电力系统电磁暂态扰动信号往往表现为奇异信号,其主要特征集中表现在更多还原

【Abstract】 With the rapid development of industrial technology and national economics, power quality has become an important index that every department of electrical companies pays much attention to. With the forming and boosting of electricity market reformation, the utility must meet the increasing requirement of not only power quantity but also power quality from customer.To effectively improve the power quality, we need to research on the disturbance phenomena. The identification and classification of disturbance is the premise to depress the wicked influences produced by them. This paper proposes an appropriate combination of time-domain and frequency-domain analysis method to research on power quality events. In time-domain, the analysis method on characters of instantaneous load is taken. In frequency-domain, the wavelet transform is used in this thesis. The result of the simulation indicates the usefulness and veracity of this new method.Fourier Transform, the most classical signal processing analysis method, is ideal for the calculation of magnitude of sinusoidal signals in their steady state. Based on this, this thesis brings out a exertion of Fast Fourier Transform (FFT) to detect the wave distortion disturbance. By the way, it also extracts of the magnitude features of short-term disturbance and long-term disturbance.The characteristic features of short-term disturbance and long-term disturbance, such as voltage sag and voltage swell, are concentrated on magnitude and time duration. Therefore, it is suitable to be analyzed in time-domain area. This paper innovates the characters of instantaneousload to analyze these disturbance events. After calculating the deviation factor by accounting the imitation resistance and imitation inductance, we can point the onset and the end time of the disturbance by rule and line. Then the idiographic type of the disturbance can be given out.In power system, the transient disturbance signal always represents as the singular signal. The characteristic features of them are mainly distributed in frequency domain area. Wavelet transform, an efficient mathematical tool for singularity detection, can offer plentiful time-frequency information on the signal processing. In this paper, a method using multiresolution analysis and modulus maximum based on wavelet transform is presented, bywhich the singularity and the main frequency containing can be accurately achieved.The practicality of the proposed algorithm in this thesis is validated by four digital simulations, which are voltage fluctuation, voltage sag, voltage swell, and impulsive disturbance. The results of the simulation show that the new analysis method based on the combination of time-domain and frequency-domain, in which the entropy is used as feature extraction, possesses efficiency and feasibility.更多还原