Flicker contribution evaluation in electric power systems

The power quality disturbances such as sag-swell, harmonics, inter-harmonics, and flicker have come into focus since last decades into electric power systems. Among these disturbances, the flicker is one of the serious power quality issues for both power system operators and users. In addition to direct effects on human life such as the influence of discomfort caused by visual affection, headache and tiredness, the flicker may cause malfunction and incorrect operations of electrical devices. Furthermore, finding a dominant flicker source in order to mitigate it and supply high quality voltage to users are the main purposes of the network operators. Flicker is expressed as the impression of discomfort caused by visual affection as a result of light stimulus whose luminance varies with time. The light flicker or in other words voltage flicker arises due to the fluctuation of voltage. Voltage flicker can be stated as voltage amplitude modulation with a modulation frequency between 0.5 Hz to 35 Hz. In electric power systems, various types of flicker generating sources can be seen. Besides well-known flicker sources such as arc furnaces and welding machines, wind turbines, solar power plants and variable frequency drives, are also accepted as flicker sources. The effect of each generating source on the flicker disturbance depends on the frequency and the magnitude of the voltage variation. The flicker level can be determined by a flicker meter depending on both the frequency and the magnitude of the signal. The flicker level measurement is performed by a meter explained in the IEC 61000-4-15. The voltage signal is applied to the input of this meter and instantaneous flicker sensation (Pinst) and two discrete flicker severity indices called short term flicker (Pst) and long term flicker (Plt) are obtained as outputs. By considering Pst and Plt values, the planning and compatibility levels of fluctuating installations for the flicker evaluation in the Medium Voltage (MV), High Voltage (HV), and Extra High Voltage (EHV) systems are defined in IEC 61000-3-7 and IEEE 1453. The measurement of the flicker level is defined in the IEC 61000-4-15 standard by a flicker meter which deals only with voltage signals and is not sufficient to understand the contribution of the load and background power systems separately. Moreover, the investigations for finding root cause of flicker based on only the result of IEC flicker meter causes misinterpretations. Therefore, a new method is proposed in this study for flicker contribution evaluation of both load and power system as well flicker source detection. In our study, wavelet analysis, which is applied for various application areas, has been used. The main advantage of Wavelet Analysis compared to other signal analysis methods is analysing the signal in different frequencies and resolutions. The Fourier Transform gives only frequency information of signal and lacking of giving time information. The Short Time Fourier has constant time-frequency resolution and and it is not possible to get better time and frequency resolution. In Multi-Resolution Wavelet Analysis, the signal is analysed at different frequencies with different resolutions. Multi Resolution Analysis is applied to give good time resolution and poor frequency resolution at high frequencies and good frequency resolution and poor time resolution at low frequencies. This approach makes sense especially when the signal has high frequency components for short duration and low frequency components for long duration. Since the signal in flicker analysis contains low frequency components for long duration, Wavelet Analysis has been chosen for this study. With the help of Multi Resolution Analysis, coefficients corresponding to related flicker frequency range have been obtained and information theory based Wavelet Energy Entropy values are then calculated accordingly. Wavelet Energy Entropy is expressed as a combination of Shannon's information entropy and wavelet transform. Unlike Fourier Transform, Wavelet Transform can locate the changes in the signal and the analysis of the signal in both time domain and frequency domain can be easily achieved. With the help of multi-resolution wavelet analysis, the signal can be decomposed in different levels and the reflection of the energy distribution of signal and the information about any change of the signal in the time domain can be obtained accordingly. According to the information entropy, if the signal's state changes from stationary to nonstationary because of any disturbance, the entropy value will change. In a case of a disturbance, magnitude and frequency of the signal will change and it will result a change in entropy as well. Since flicker is described as a power quality disturbance with an amplitude modulation with a modulation frequency, in order to determine flicker responsibility approach multi-resolution wavelet analysis based wavelet energy entropy method is used. When the power system changes from normal state to disturbance, voltage and current signals will change and its information entropy value will change accordingly. When a disturbance occurs, the signals' magnitude and frequency will change and its entropy will change as well. Thus, disturbances can be detected and analysed by the change in entropy value. The real time data gathered from electric power systems contain the complexity and uncertainty of the system. The applicable and interpretable information obtained from these complexity and uncertainty has great importance. The entropy is described as a measure of uncertainty provided by the discrete probability distributions. The information entropy is an important index which shows the quantity of information contained in the signal. Therefore, Wavelet Energy Entropy approach has been used in this study to get the amount of information from the signal with flicker. In this study, data have been obtained from a simulation model containing flicker source created in simulation program and real field measurements performed in different iron and steel factories in the Marmara and Ege region in Turkey have been used. Wavelet Energy Entropy values are calculated by using simulated and real data for both cases of the load is operating and the load is not operating in order to evaluate the disturbance contribution of the load and remaining power system. A new index has been introduced by using Wavelet Energy Entropy values for flicker disturbance contribution evaluation. The proposed index has been compared with the Short Circuit Ratio and Short Circuit Voltage Depression parameters used for flicker emission analysis and the results seem promising. In this manner, it is planned to apply this proposed method to power quality analysers. Thus, disturbance mitigation solution obligation according to regulations can be clearly addressed and the possible conflict between power system operators and users can be settled by deciding the most feasible solution.