Accurate harmonic source identification using S-transform

This paper introduces the accurate identification of harmonic sources in the power distribution system using time-frequency distribution (TFD) analysis, which is S-transform. The S-transform is a very applicable method to represent signals parameters in time-frequency representation (TFR) such as TFR impedance (ZTFR) and the main advantages of S-transform it can provide better frequency resolution for low frequency components and also offers better time resolution for high-frequency components. The identification of multiple harmonic sources are based on the significant relationship of spectral impedances (ZS) that extracted from the ZTFR, consist of the fundamental impedance (Z1) and harmonic impedance (Zh). To verify the accuracy of the proposed method, MATLAB simulations carried out several unique cases on IEEE 4-bus test feeder cases. It is proven that the proposed method is superior, with 100% correct identification of harmonic source location. It is proven that the method is accurate, fast and cost-efficient to localize harmonic sources in the power distribution system

An Identification of Multiple Harmonic Sources in a Distribution System by Using Spectrogram

The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement

Load characterization and revenue metering under non-sinusoidal and asymmetrical operation

This paper proposes an approach to load characterization and revenue metering, which accounts for the influence of supply deterioration and line impedance. It makes use of the Conservative Power Theory and aims at characterizing the load from the measurements done at the point of common coupling. Despite the inherent limitations of a single-point measurement, the proposed methodology enables evaluation of power terms, which clarify the effects of reactivity, asymmetry and distortion, and attempts to depurate the power consumption accounted to the load from those terms deriving from supply nonidealities

Determination of location and capacity of distributed generations with reconfiguration in distribution systems for power quality improvement

The use of non-linear loads and the integration of renewable energy in electricity network can cause power quality problems, especially harmonic distortion. It is a challenge in the operation and design of the radial distribution system. This can happen because harmonics that exceed the limit can cause interference to equipment and systems. This study will discuss the determination of the optimal location and capacity of distributed generation (DG) and network reconfiguration in the radial distribution system to improve the quality of electric power, especially the suppression of harmonic distribution. This study combines the optimal location and capacity of DG and network reconfiguration using the particle swarm optimization method. In addition, this research method is implemented in the distribution system of Bandar Lampung City by considering the effect of using nonlinear loads to improve power quality, especially harmonic distortion. The inverter-based DG type used considers the value of harmonic source when placed. The combination of the proposed methods provides an optimal solution. Increased efficiency in reducing power losses up to 81.17% and %total harmonic distortion voltage (THDv) is below the allowable limit

Localization of Multiple Harmonic Sources for Inverter Loads Utilizing Periodogram

This paper introduces a new technique to localize the multiple harmonic sources that caused by power inverter loads in power distribution system utilizing periodogram technique with single-point measurement approach at the point of common coupling (PCC). The periodogram technique is used to analyzed and distinguish multiple harmonic sources location in power system whether at downstream, upstream or both stream by their impedances characteristics. The proposed localization of multiple harmonic sources method is based on the correlational relationship between fundamental impedance (Z1) and harmonic impedance (Zh) in order to identify the suspected buses. The adequacy of the proposed methodology is tested and verified on distribution system for several different cases

A Fast Localization Of Multiple Harmonic Sources For Rectifier Loads By Utilizing Periodogram

This paper introduces a fast method to localize the multiple harmonic sources (MHS) for rectifier based loads in power distribution system by utilizing periodogram technique with a single-point measurement approach at the point of common coupling (PCC). The periodogram is a fast and accurate technique for analyzing and distinguishing MHS location in power system. Matlab simulation is carried out several unique cases on IEEE test feeder cases due to validate the proposed method. The identification of MHS location is based on the significant relationship of spectral impedance which are fundamental impedance (Z1) and harmonic impedance (Zh) that's extracted from an impedance power spectrum. It is verified that the proposed method is fast, accurate, and cost efficient in localizing MHS. In addition, this method also contributes 100% correct identification of MHS location

COMPRESSIVE SENSING-BASED METHODOLOGIES FOR SMART GRID MONITORING

Modern distribution networks, commonly known as Smart Grids, will be characterized by strictly requirements in terms of reliability and efficiency of the power supply. This will require a high empowerment in the management of the distribution, and transmission, networks by the system operators. Problems such as the identification of the prevailing harmonic sources and the fault location are characterized by criticality which must be appropriately taken into account, in order to fully exploit the capabilities of the Smart Grids. The analysis of both phenomena requires an appropriate monitoring of the networks, which are currently characterized by the availability of a limited number of measurements. This increase the complexity of the analysis of distribution networks, and the necessity of developing ad-hoc algorithms and solutions aimed at supporting the system operators while managing the networks. In this thesis, Compressive Sensing-based algorithms for detecting the main harmonic polluting sources, and for identifying the location of faults occurring in distribution systems have been presented. With reference to the identification of the main harmonic sources, two algorithms have been proposed: one for detailed analysis, with reference to a specific harmonic order, and one for more general analysis, which allows to investigate multiple harmonic orders simultaneously. The performed tests have proved how both methodologies are robust with respect to the measurement uncertainties, underlying the different capabilities of the two methods. Contrarily, the performance of the fault location algorithms are more influenced by the higher uncertainties in measuring the dynamic signals involved during the fault. The analysis performed considering the proper uncertainty scenarios have underlined how the use of modern devices for branch current measurements allow to increase the performance of the fault location algorithms; providing additional information which are useful for locating the fault