Total Harmonic Distortion Index Research Articles

Study of Harmonic Minimization in Pulp and Paper Mill using Hybrid Active Filter -A Case Study

Increased power electronics-based nonlinear loads have harmed distribution system power quality. Variable speed drives, switched-mode power supply, and DC drives impair power quality and affect customers and utilities. Many variable-speed drives in the paper mill cause harmonic distortion, a power quality issue. This study investigates the impact of nonlinear electric drives on supply current distortion in Padmavati Pulp and Paper Mill, Ambarnath, Thane, India. Harmonic analysis is done at PCC, that is, at the secondary side of the transformer, with the help of a power quality analyzer fluke-434. Based on detailed analysis, a suitable harmonic reduction method is identified. passive filters, are the simplest solution for lowering harmonic currents but it has shortcomings like bulk size and cause resonance. In recent years active filter has been applied as an effective solution for harmonic reduction. This study suggests a hybrid filter as an economical solution to take advantage of a passive and active harmonic filter. This work present design and simulation of cascade H- bridge multilevel inverter-based hybrid filter for medium and high-power distribution system. The system for the case study is developed in MATLAB Simulink platform with suitable harmonic mitigation techniques and performance is evaluated in terms of total Harmonic Distortion Index (THDi).

Simulation design and analysis 9-level H-bridge single phase stepdown cyclo inverter

This DC-to-AC voltage converter is designed for output frequency controlled by a 9-level cascade H-bridge cyclo inverter with pulse width adjustment. The aim of the study was to determine the pattern and format of the voltage, output frequency, and Total Harmonic Distortion index of a 9-level IGBT cyclo inverter. The method used is to build a unidirectional power converter design modeling into 9 alternating levels with cyclo converter-controlled frequency settings using the Simulink MATLAB tool. The cyclo converter section is constructed with two P and N converters in a parallel arrangement. The frequency and trigger pulse width of both converters control the output voltage and frequency format of the cyclo inverter. The test results show a series of ladder waves with an output frequency, of (1/2f, 1/3f, 1/4f, 1/5f, 1/6f, 1/7f, 1/8f, 1/9f, and 1/10f). The simulation results show that the nth input frequency divider waveform is characterized by the emergence of a number of step pulses of n positive half cycles and negative half cycles. The Total Harmonic Distortion Index gets bigger when the system circuit is designed at a low frequency. This modeling can be implemented into a prototype that is used for variable-speed DC motor drivers.

Time-Frequency Analysis and Neural Networks for Detecting Short-Circuited Turns in Transformers in Both Transient and Steady-State Regimes Using Vibration Signals

Transformers are vital elements in electrical networks, but they are prone to various faults throughout their service life. Among these, a winding short-circuit fault is of particular concern to researchers, as it is a crucial and vulnerable component of the transformers. Therefore, if this fault is not addressed at an early stage, it can increase costs for users and affect industrial processes as well as other electrical machines. In recent years, the analysis of vibration signals has emerged as one of the most promising solutions for detecting faults in transformers. Nonetheless, it is not a straightforward process because of the nonstationary properties of the vibration signals and their high-level noise, as well as their different features when the transformer operates under different conditions. Based on the previously mentioned points, the motivation of this work is to contribute a methodology that can detect different severities of short-circuited turns (SCTs) in transformers in both transient and steady-state operating regimes using vibration signals. The proposed approach consists of a wavelet-based denoising stage, a short-time Fourier transform (STFT)-based analysis stage for the transient state, a Fourier transform (FT)-based analysis stage for the steady-state, the application of two fault indicators, i.e., the energy index and the total harmonic distortion index, and two neural networks for automatic diagnosis. To evaluate the effectiveness of the proposed methodology, a modified transformer is used to experimentally reproduce different levels of SCTs, i.e., 0-healthy, 5, 10, 15, 20, 25, and 30 SCTs, in a controlled way. The obtained results show that the proposed approach can detect the fault condition, starting from an initial stage for consolidation and a severe stage to accurately assess the fault severity, achieving accuracy values of 90%.

An application of improved space vector strategy based in digital direct synthesizers for a high-performance inverter

When performing commutation at induction motors based in PWM, a change in the switching frequency can take several clock cycles to be reflected in the windings generating harmonics that could damage the motor or generate an erroneous modulation. Most of the high-performance inverters use the Space Vector PWM given its minor switching losses and its capability to reduce the harmonics in the output signals. Nonetheless, the SVPWM requires complex calculation in online operation, which is the major concern for real-time implementations. Even that there are problems related to the development of technology that does not use the sine waveform to drive an induction motor and considering the availability and capability of Direct Digital Synthesizers (DDS) technology, we developed a hardware–software system to propose a modulation strategy called Space Vector DDS. The SVDDS can synthesize any digital waveform besides the sine waveform, becoming a more versatile approach. This proposal is the first one to couple the DDS in the commutation of an induction motor. As summary, the main features of our SVDDS system are its capability to synthesize any discrete waveform, improvement of control response parameters (13% for a load test and 12% for a speed test, compared with SVPWM), a low value of the total harmonic distortion index (4.88%) and reduction of the mathematical processing (system response of 21.364 ns).

A parallel evaluation of the wind and wave energy resources along the Latin American and European coastal environments

Considering the trend to develop renewable projects in marine environment, the objective of the present work is to provide a comprehensive picture of the wind and wave energy for some significant coastal sites from Latin America and Europe. Thus, a reanalysis database that covers 17 years of wind and wave data (2000–2016) is considered, evaluating also some statistical parameters. In this way, we identified the most interesting sites for a marine project. At the same time, the performance of five wind turbines (Senvion 6.2M 126, BARD 5.0, SWT–3.6 –120, Vestas V90–3.0 and Vestas V80–2.0) and five wave energy converters (Wave Dragon, PPC, Pelamis, Aqua Buoy, Seabased AB) is also assessed. The results show that in Latin America, the coastal region located close to Tierra del Fuego presents the best wind resources, indicating a maximum wind power value of 1759 W/m2 (at 80 m height). This is relatively similar to the conditions encountered at the Carloway site, in Europe close to Ireland (1778 W/m2). As regards wave power, a maximum value of 82.59 kW/m is assessed for the Carloway site. According to the total harmonic distortion index, the best sites to develop a joint wind-wave project are in Latin America, where for this index most of the values are below the 0.8 limit. Looking at the performances of wind and wave generators, we notice a maximum power output of 4.26 MW for the Senvion 6.2M 126 turbine, compared to an expected electric power of 2.64 MW, which results for the Wave Dragon energy converter. The results show that the capacity factors of the wave systems are significantly smaller than in case of the wind turbines.

Exploring prospective benefits of electric vehicles for optimal energy conditioning in distribution networks

A potentially beneficial new opportunity is emerging around the exchange of energy between electric vehicles and the electrical energy grid, particularly as more low-carbon energy sources are connecting to the grid. Accordingly, this paper presents an optimization framework to activate the potential capabilities of electric vehicles equipped with bidirectional chargers for energy conditioning (including energy management and power quality improvement) of the future distribution networks. The proposed nonlinear optimization seeks to concurrently enhance the operation performance (using the network voltage deviation index) as well as power quality of the grid (using total harmonic distortion index). The proposed model is tested on a 33-bus distribution network to demonstrate its efficiency and performance.

Non‐linear adaptive hysteresis band pulse‐width modulation control for hybrid active power filters to reduce switching loss

Pulse-width modulations (PWMs) are widely investigated in active power filter (APF) applications. However, there are seldom PWMs proposed in hybrid APF (HAPF) applications because of their non-linear current characteristic. This study proposes a non-linear adaptive hysteresis band PWM controller for HAPFs to reduce the switching loss and keep the total harmonic distortion (THD) at an acceptable level. In contrast to previous studies, as the coupling LC impendence of an HAPF can yield a non-linear compensating current, the quasi-linear and non-linear regions are exploited to obtain a low switching frequency. In addition, an approximated THD index is proposed to assess THD in a simplified way in the control system, which results in a faster system response. Finally, the performance of the non-linear adaptive hysteresis band controller is verified by comparing simulation and experimental results with a state-of-the-art PWM for HAPFs.

Single‐harmonic active power line conditioner for harmonic distortion control in power networks

In this contribution, a novel alternative concept and solution procedure for single-harmonic active power line conditioner (SHAPLC) planning is proposed to control voltage harmonic distortion in power networks. The development of the proposed solution concept, defined and detailed in this paper, is based on seeking a proper solution to practical situations, taking into account the particular harmonic distortion pattern and configuration of the power system in question. The location of the SHAPLC's, for each harmonic h of interest is determined through feasibility and sensitivity analysis. Once the best location for the SHAPLCs is known, the injection currents are determined by solving a non-linear programming algorithm. The usefulness and novelty of the SHAPLC planning methodology is illustrated with a case study, where results show its effectiveness to control the harmonic distortion in the power system. The solution procedure proposed in this contribution is aimed to achieve and assure individual harmonic distortion and total harmonic distortion indices meet recommended limits by Std-519 IEEE using SHAPLCs devices. According with revised literature, this goal has only been approached with certainty and sufficiency (not trial and error) by considering multiple injection currents at different harmonic frequencies from the selected bus.

Detection and Classification of Single and Combined Power Quality Disturbances Using Neural Networks

The detection and classification of power quality (PQ) disturbances have become a pressing concern due to the increasing number of disturbing loads connected to the power line and the susceptibility of certain loads to the presence of these disturbances; moreover, they can appear simultaneously since, in any real power system, there are multiple sources of different disturbances. In this paper, a new dual neural-network-based methodology to detect and classify single and combined PQ disturbances is proposed, consisting, on the one hand, of an adaptive linear network for harmonic and interharmonic estimation that allows computing the root-mean-square voltage and total harmonic distortion indices. With these indices, it is possible to detect and classify sags, swells, outages, and harmonics-interharmonics. On the other hand, a feedforward neural network for pattern recognition using the horizontal and vertical histograms of a specific voltage waveform can classify spikes, notching, flicker, and oscillatory transients. The combination of the aforementioned neural networks allows the detection and classification of all the aforementioned disturbances even when they appear simultaneously. An experiment under real operating conditions is carried out in order to test the proposed methodology.