Dynamic voltage restorers (DVRs) are used to protect sensitive loads from the effects of voltage sags on the distribution feeder. This paper presents and verifies a novel voltage sag detection technique for use in conjunction with the main control system of a DVR. In all cases it is necessary for the DVR control system to not only detect the start and end of a voltage sag but also to determine the sag depth and any associated phase shift. The DVR, which is placed in series with a sensitive load, must be able to respond quickly to a voltage sag if end users of sensitive equipment are to experience no voltage sags. A problem arises when fast evaluation of the sag depth and phase shift is required, as this information is normally embedded within the core of a main DVR control scheme and is not readily available to either users monitoring the state of the grid or parallel controllers. Previous research presented an additional controller, which required phase and sag depth information to manipulate the injection voltage vector returned by the main controller in order to prevent the DVR injection transformers from saturating. Typical standard information tracking or detection methods such as the Fourier transform or phase-locked loop (PLL) are too slow in returning this information, when either applied to the injection voltage vector, or to the supply voltages directly. As a result of this the voltage sag detection method in this paper proposes a new matrix method, which is able to compute the phase shift and voltage reduction of the supply voltage much quicker than the Fourier transform or a PLL. The paper also illustrates that the matrix method returns results that can be directly interpreted, whereas other methods such as the wavelet transform return results that can be difficult to interpret.

Voltage sag detection technique for a dynamic voltage restorer

The fundamental voltage, current, and phase angle are required for a wide variety of power system applications. An algorithm that is capable of calculating or estimating these quantities in real time, in the presence of distorted waveforms, finds application in diverse areas of power systems. Techniques to detect voltage sag include the root mean square (rms), Fourier transform, and peak voltage detection methods. The problem with these methods is that they use a windowing technique and can therefore be too slow when applied to detect voltage sags for mitigation since they use historical data. Recent work in the field of signal processing has led to an algorithm that can extract a single non-stationary sinusoidal signal out of a given multi-component input signal. The algorithm is capable of estimating the amplitude, phase and frequency. In this paper, the algorithm is compared to existing methods of sag detection

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A New Method of Voltage Sag and Swell Detection

In the few years, wavelet-based methodologies have been proposed as a good alternative for real-time fault detection. However, these methodologies usually fail to detect faults with overdamped transients and they are highly influenced by the choice of the mother wavelet, presenting time delay in the real-time analysis. By using the discrete wavelet transform (DWT) or the maximal overlap discrete wavelet transform (MODWT), the wavelet coefficient energy has been also used for fault analysis and presents the same drawbacks of the wavelet coefficient analysis. However, this paper presents a novel wavelet-based methodology for real-time detection of fault-induced transients in transmission lines, where the wavelet coefficient energy takes into account the border effects of the sliding windows. As a consequence, the performance of the proposed energy analysis is not affected by the choice of the mother wavelet, presenting no time delay in real-time fault detection, and the fault detection is scarcely influenced to the fault inception angle, fault resistance, and fault location, even if in critical situations where there are no fault-induced transients. The performance of the proposed methodology was assessed by using actual and simulated data. Some records were reproduced to be analyzed in real time with a digital signal processor.

Fault-Induced Transient Detection Based on Real-Time Analysis of the Wavelet Coefficient Energy

This paper proposes a fault-location method based on smart feeder meters with voltage sag monitoring capability. The main idea is to explore voltage measurements from monitors placed in different buses of distribution systems to estimate the fault location. The estimation is achieved by relating the voltage deviation measured by each meter to the fault current calculated based on the bus impedance matrix, considering the fault in different points. In order to improve the method accuracy, the loads are represented by constant impedance models and included into the bus impedance matrix. The performance of the proposed method is demonstrated by using a real distribution system. Sensitivity studies results show that the method is robust since it has good performance for different values of fault resistance, quantity, and location of the smart meters.

Fault Location in Distribution Systems Based on Smart Feeder Meters

A method to determine the origin of voltage sag disturbance is proposed in this paper. Its principle is to estimate the equivalent impedance of the nondisturbance side by utilizing the voltage and current changes caused by the disturbance. The sign of the real part of the estimated impedance can reveal if the disturbance is from upstream or downstream. The proposed method can be easily implemented into power quality meters for troubleshooting applications or into digital revenue meters to document the responsibility for disturbances. Extensive field and laboratory test results have proven the effectiveness and robustness of the proposed method.

A resistance sign-based method for voltage sag source detection

While existing techniques are capable of automatically identifying and classifying various types of distribution-level power quality disturbances, they do not provide any information about the locations of the disturbance sources. This paper shows that it is possible to use sampled voltage and current waveforms to determine on which side of a recording device a disturbance originates. This is accomplished by examining the energy flow and peak instantaneous power for both capacitor energizing and voltage sag disturbances. The authors demonstrate the technique by testing it on both ATP-generated waveforms and actual field disturbance data. In both cases, they are able to accurately determine on which side of a recording device the disturbance originates. If enough recording devices are available in a network, the individual readings can be collectively used to pinpoint the locations of disturbance sources.

A direction finder for power quality disturbances based upon disturbance power and energy

Voltage sag disturbances are characterized by several parameters, including but not limited to sag duration and depth. An accurate determination of fault inception and clearing times is needed to properly determine these and other characterizing parameters, such as point-on-wave, and to verify proper breaker operation. This paper presents a discrete wavelet-based approach for determining the beginning and end times of sags. Several types of wavelets are compared using recorded transmission sag data. A recommendation is made for the best overall wavelet choice. The procedure is fully described, and the results are compared with other methods for determining sag duration, such as the specified RMS voltage and waveform envelope methods.

A wavelet-based procedure for automatically determining the beginning and end of transmission system voltage sags

While existing techniques are capable of automatically identifying and classifying various types of distribution-level power quality disturbances, they do not provide any information about the locations of the disturbance sources. This paper shows that it is possible to use sampled voltage and current waveforms to determine on which side of a recording device a disturbance originates. This is accomplished by examining the energy flow and peak instantaneous power for both capacitor energizing and voltage sag disturbances. We demonstrate the technique by testing it on both ATP-generated waveforms and actual field disturbance data. In both cases, we are able to accurately determine on which side of a recording device the disturbance originates. If enough recording devices are available in a network, the individual readings can be collectively used to pinpoint the locations of disturbance sources.

E.J. Powers

Papers

A direction finder for power quality disturbances based upon disturbance power and energy

A wavelet-based procedure for automatically determining the beginning and end of transmission system voltage sags

A direction finder for power quality disturbances based upon disturbance power and energy