Harmonic Estimation Technique Research Articles

Novel hybrid arithmetic optimization algorithm-recursive least square approach for power system harmonic estimation

Abstract Accurate harmonic estimation is essential for effective power quality assessment, designing appropriate harmonic filters, and ensuring the reliable operation of electrical equipment. This article proposes a novel hybrid harmonic estimation technique combining recursive least square (RLS) and arithmetic optimization algorithm (AOA) for accurate estimation of harmonics, inter-harmonics and sub-harmonics. AOA is a new meta-heuristic method based on distribution behaviour of main arithmetic operators such as addition, subtraction, multiplication and division. RLS is used for estimation of amplitude of harmonics, whereas phase is estimated by AOA. The performance of AOA–RLS is investigated in detail for estimation of power system signals using two set of test signals buried with noise. The proposed AOA–RLS is proved to be efficient for estimating both phase and amplitude parameters under different signal to noise ratio (SNR) conditions with an estimation of error of E−3. The efficacy of AOA–RLS technique is demonstrated by comparing with competitive existing techniques. The performance of AOA–RLS also verified in experimental studies.

A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

Modern industrial and commercial devices that are fed by power electronics circuits and behave non-linearly tend to produce power quality issues in power systems including harmonics and interharmonics, swell, flicker, spikes, notches, and transient instabilities. Among them, harmonic emission is the most significant challenge to be overcome by the distribution networks. Unwanted current, overheating motors and transformers, equipment failure, and circuit breaker misoperation are some of the harmonic consequences. While it is important to employ the best methods to mitigate or suppress the harmonic distortions in power systems, it is even more essential to estimate these harmonics at the outset by developing smart, efficient, and accurate techniques. Due to their capability for learning, predicting, and identifying, researchers have turned to Artificial Intelligence technologies for harmonic estimation in distribution networks. Although the power system parameters (impedance/admittance model) and many harmonic monitors are prerequisites for traditional harmonic estimation methods, by utilizing Artificial Intelligence, these requirements are minimized. In this paper, a comprehensive review of traditional and modern (smart) harmonic estimation techniques are discussed.

A Novel Hybrid GWO-LS Estimator for Harmonic Estimation Problem in Time Varying Noisy Environment

The power quality of the Electrical Power System (EPS) is greatly affected by electrical harmonics. Hence, accurate and proper estimation of electrical harmonics is essential to design appropriate filters for mitigation of harmonics and their associated effects on the power quality of EPS. This paper presents a novel statistical (Least Square) and meta-heuristic (Grey wolf optimizer) based hybrid technique for accurate detection and estimation of electrical harmonics with minimum computational time. The non-linear part (phase and frequency) of harmonics is estimated using GWO, while the linear part (amplitude) is estimated using the LS method. Furthermore, harmonics having transients are also estimated using proposed harmonic estimators. The effectiveness of the proposed harmonic estimator is evaluated using various case studies. Comparing the proposed approach with other harmonic estimation techniques demonstrates that it has a minimum mean square error with less complexity and better computational efficiency.

Digital Real-Time Harmonic Estimator for Power Converters in Future Micro-Grids

One of the main challenges in future micro-grids is the presence of transients and fluctuations inevitably imposed by nonlinear loads. Therefore, real time identification of transients and fluctuations of the grid is essential for the future micro-grids. This identification can be used in different applications of “grid-connected” and “island” micro-grid such as grid synchronization, harmonic current injection for islanded mode micro-grids, etc. This paper focuses on developing a method to detect and monitor the disturbances and fluctuations in the utility grid. A novel real-time harmonic estimation technique is presented, which is able to quickly and precisely estimate dc component, and synchronous and asynchronous harmonic contents of the grid voltage despite of their unknown nature. The proposed technique can be used in the control system of power converters to potentially enhance the reliability and resiliency of future micro-grids. As a case study, the performance of the proposed harmonic estimator is evaluated in grid synchronization of the power converters. Simulation and experimental results from the case study show the ability of the converter to inject a smooth sinusoidal current in presence of disturbance and fluctuations in the grid voltage. These results verify the fast dynamic and accuracy of the proposed harmonic estimation technique.

Improvement in Power Quality using Hybrid Power Filters based on RLS Algorithm

In industrial and utility power system it has been observed that harmonics build a major role in reducing the quality of power. These harmonics are caused because of increasingly utilize of nonlinear loads connected to the power system. In this context, active power filters play a very significant role for improvement in power quality. Moreover, at transmission ground, there is a high requirement to control reactive power and voltage stability. Conventionally, passive and active filters (shunt and series filters) were used for the development of power quality. But, they suffered from the issues like resonance, fixed compensation, and other PQ problems. Therefore, to minimize these issues, a hybrid combination of filters using passive and active filters is designed. In this paper, a comparative study of two hybrid model of HAPF is done based on current control techniques like d-q and p-q theory under different operating conditions. These results are again compared with a new estimation technique proposed in this paper well known called as recursive least square (RLS) harmonic estimation technique. The amplitude and phase angle of both the fundamental and harmonic currents are estimated with the proposed RLS technique. At the point of common coupling (PCC) the signal which is composed with harmonics is estimated with and without HAPF. Finally, it is analysed from the observation that the load current and supply current is improved significantly with a decrease of total harmonic distortion (THD) under different operating scenarios.

Harmonic estimation using RLS algorithm and elimination with improved current control technique based SAPF in a distribution network

Abstract This paper presents the application of well known recursive least square (RLS) harmonic estimation technique and its elimination with improved current control technique based shunt active power filter (SAPF) in a distorted power network. The estimation of amplitude and phase angle of fundamental and harmonics is performed using RLS algorithm, known for their simplicity of computation, accuracy and good convergence properties. The estimates are updated recursively as samples of the harmonic signals are received. In order to eliminate harmonics produced by the nonlinear load connected in the distribution network, a three-phase SAPF with modified current control technique is employed. In this paper, based on the analysis and modeling of SAPF with closed-loop control, a feed forward compensation path of load current and a new pulse width modulation (PWM) control scheme is proposed to improve the dynamic performance of the SAPF. In this case the amplitude and phase angle of the converter AC voltage should be adjusted using PWM, thus producing either leading or lagging reactive power. Harmonic contented in the signal is estimated at the point of common coupling (PCC) with and without SAPF. The comparative results of amplitude and phase angle of fundamental and selected harmonics are determined considering installation of SAPF in the distribution network. The system is studied using MATLAB environment to justify the effectiveness of proposed control technique in comparison to the other techniques discussed in the recent literature.

Geodetic evidence on segmentation of Cascadia subduction zone based on episodic tremors and slips using multivariate harmonic analysis of GPS time series

Episodic tremor and slip (ETS) events with different recurrence intervals have been observed in abundance all along the Cascadia subduction zone margin. Analysis of seismic records as well as Global Positioning System (GPS) time series of the Pacific Northwest Geodetic Array (PANGA) has suggested three distinct coherent zones for the occurrence of these events. In this paper multivariate harmonic estimation has been deployed for further analysis of the segmentation in this area. Raw time series of 43 permanent GPS stations have been used for this purpose. The GPS stations have been geographically divided into three distinct groups including those in the northern, middle and southern parts of the study area. After the reduction of time series for the linear trend as well as annual and semiannual effects, the data series of each group has been analyzed using the multivariate harmonic estimation technique. Subsequently, different combinations of GPS stations including the stations located in the southern, northern and middle zones have been analyzed. Furthermore, the northern and middle, southern and middle as well as the northern and southern zone pair combinations have also been analyzed. The statistical measure devised for identifying the significant frequencies suggests common periods that are consistent with the recurrence intervals of the ETS events already reported for each of the above three geographic zones. Moreover, the method can provide geodetic evidence, in addition to geophysical ones, on the segmentation of ETSs, provided that the adopted time series are of a sufficient length. The geodetic evidence obtained in this research is consistent with the recurrence intervals as well as the boundaries obtained by the analysis of seismic records. Contrary to univariate harmonic estimation, multivariate approach using spatio-temporal correlation of the GPS time series is capable to detect those ETSs whose impacts on the time series are weak.

Geodetic constraints on the period of episodic tremors and slips using least squares harmonic estimation method with application to Cascadia subduction zone

It is expected that episodic tremors and slips (ETS) as a type of slow earthquakes with periodic property will be detected using harmonic estimation techniques. The principal goal of this paper is the detection of these kinds of earthquakes using least squares harmonic estimation (LSHE). To accomplish this, the raw time series of 38 permanent GPS stations of the Pacific Northwest Geodetic Array have been analyzed. Previously, some independent techniques could confirm the occurrences of the aforementioned quakes at these stations. However, the current research intends to evaluate the spectrum of each of the de-trended time series using the LS-HE method. In each station, the period of the detected harmonic with the maximum power spectrum is equivalent to the average period previously reported for these events. According to the obtained results, the recurrence interval of these events ranges from 9 months to 3 years. In sum, the study confirms this method being efficient for investigating the occurrences of ETSs when the length of the GPS time series is sufficiently large.

A Controlled Filtering Method for Estimating Harmonics of Off-Nominal Frequencies

The increasing use of power electronics in power systems causes a high injection of harmonic components which can in turn interfere with utility equipment and customer loads. Therefore, the correct estimation and measurement of harmonics have become an important issue. If the power frequency of the signal is steady and near the nominal value, the discrete Fourier transform (DFT) can be used and good estimation performance is achieved. However, there are considerable power frequency variations on isolated systems such as shipboard power systems, micro-grids and smart-grids. When these variations occur there may be significant errors in the estimates using the DFT. In order to deal with this problem, this work presents a novel technique based on demodulation of the power line signal and subsequent filtering for harmonics estimation. The main features of the proposed harmonic estimation technique are: precise and accurate estimation of harmonics of off-nominal frequencies and fast estimation of harmonics (about two cycles of the fundamental component). Simulation results show that the proposed technique performs well in comparison with the DFT and can be a good candidate to replace it in cases where the power frequency is subject to considerable variations.