Ramizi Mohamed

Development of a DSP-Based Power Quality Monitoring Instrumentfor Real-Time Detection of Power Disturbances

Current trends of power quality monitoring instruments are based on digital signal processors (DSP), which are used to record waveforms and harmonics and comes with software for collecting data and viewing monitoring results. The variations in the DSP based instruments are in the way algorithms that are developed for processing the real-time power quality waveforms. At present, all of the available power quality monitoring instruments are not capable of troubleshooting and diagnosing power quality problems. Therefore, a DSP-based power quality monitoring instrument is proposed for real-time disturbance recognition and source detection. The proposed instrument uses the Texas Instruments TMS320C6711DSP starter kit with a TI ADS8364EVM analog digital converter mounted on the daughter card. The instrument architecture and the software implementation are discussed in the paper. Preliminary experimental results displaying the fast Fourier transform analysis of the real-time voltage signals are included

Model building of thermoelectric generator exposed to dynamic transient sources

This paper presents the modeling of thermal and power generation behavior of a thermoelectric generator (TEG) exposed to transient sources. Most of the previous research concerned the analysis for steady-state behavior which only involves constant temperature value. However, in practice, the temperature of the TEG input fluctuates with time. Therefore this research will look into a focal point on transient heat sources that is being supplied to the hot junction with natural convection cooling process at the cold junction for single and multiple configuration of TEG. The model obtained the data from existing experiments with predicted various conditions of temperature, heat gradient, internal resistance and current attribute of TEG. Transient analysis on single TEG has shown that the value of Seebeck coefficient, thermal conductivity and figure-of-merit vary with the value of cold side temperature. When the ratio between the load and the internal resistance increases, the voltage increases. By considering the multiple TEGs, the matched voltage shows different values when the number of cascaded TEGs is varied. The simulation results have proven that the variation in the number of cascaded TEGs can be used to determine the output power characteristics of a TEG.

An optimization of rectangular shape piezoelectric energy harvesting cantilever beam for micro devices

The vibration based piezoelectric energy harvester system is considered as an alternative solution for micro-devices, especially for remote area. This paper presents an optimization approach to determine the optimal cantilever beam of a rectangular shape piezoelectric energy harvester to run the micro devices in which power is unavailable. In this study, PZT-5H material has been utilized. The motivation behind this research is to maximize the power behavior by optimizing the cantilever beam’s length, width and thickness. Therefore, the proposed rectangular cantilever beam has been optimized by using modified particle swarm optimization (MPSO) algorithm and designed in COMSOL software. Finally, the optimization results of MPSO are compared with other technique to validate the outcomes. The findings show that the performance of the proposed technique is better than other technique in terms of quality and convergence speed.

Locating partial discharge sources in high voltage transformer windings

The analysis of partial discharge (PD) measurement data obtained using radio frequency current transducers (RFCT) incorporated into the external earthing connections (i.e bushing tap points and neutral to earth connections) offers the possibility of on-line condition monitoring of large transformers. A method for locating PD sources in windings has been developed, based on analysis of differential equations that model the propagation of PD signals from the source to the measurement point. Analysis reveals that if the discharge at the source is assumed to be impulse-like, then the form of the response at the measurement points can be simulated as a function of source location along the winding. If all parameters of the winding are known then it is possible to model the response, however, in the field this is often not the case. So the method developed here uses information from the PD measurements themselves to estimate the unknown coefficients required to simulate the likely discharge currents. With these estimates it is then possible to compare PD measurement information with simulation data in order to identify the most likely location of a PD source. An experiment based on a section of high voltage winding has been used to produce PD measurement data and to validate the proposed approach.

Comparing the harmonic characteristics of typical single-phase nonlinear loads

Harmonic distortion in electric distribution system is increasingly growing due to the widespread use of nonlinear loads. Large concentrations of these loads have the potential to raise harmonic voltages and currents in an electrical distribution system to unacceptable high levels that can adversely affect the system. Hence there is need to study the impact of nonlinear loads in the system. This paper presents a method based on bispectrum analysis to characterize typical single phase nonlinear loads by analyzing the harmonic currents produced by these loads. Measurements are conducted using a power quality monitor to record the harmonic current waveforms, individual harmonic distortion levels and total harmonic distortion. To investigate the harmonic characteristics of these loads, the fast Fourier transform technique and the advance signal processing technique such as the bispectrum analysis are used. The results of harmonic characteristics obtained from these loads are compared so as to investigate the effectiveness of the bispectrum analysis in characterizing the various nonlinear loads.

Dynamic modeling and simulation of a thermoelectric-solar hybrid energy system using an inverse dynamic analysis input shaper

This study presents the behavioral model of thermal temperature and power generation of a thermoelectric-solar hybrid energy system exposed to dynamic transient sources. In the development of thermoelectric-solar hybrid energy system, studies have focused on the regulation of both systems separately. In practice, a separate control system affects hardware pricing. In this study, an inverse dynamic analysis shaping technique based on exponential function is applied to a solar array (SA) to stabilize output voltage before this technique is combined with a thermoelectric module (TEM). This method can be used to estimate the maximum power point of the hybrid system by initially shaping the input voltage of SA. The behavior of the overall system can be estimated by controlling the behavior of SA, such that SA can follow the output voltage of TEM as the time constant of TEM is greater than that of SA. Moreover, by employing a continuous and differentiable function, the acquired output behavior of the hybrid system can be attained. Data showing the model is obtained from current experiments with predicted values of temperature, internal resistance, and current attributes of TEM. The simulation results show that the proposed input shaper can be used to trigger the output voltage of SA to follow the TEM behavior under transient conditions.

A Rule Based Expert System for Identification of Harmonics Originating from Single Phase Nonlinear Loads

Presently, there is still a critical shortage of experts to interpret and diagnose problems associated with power system harmonics. Thus, the use of a rule based expert system is proposed for the identification of harmonic sources originating from various single phase nonlinear loads such as uninterruptible power supply, personal computer, fluorescent lamp with magnetic and electronic ballasts, PC monitor and oscilloscope. Identification of harmonics originating from single phase nonlinear loads is implemented by first analyzing the harmonic current waveforms using fractal and fast Fourier transform analyses so as to characterize the harmonic signatures of the different types of nonlinear loads. Then, a rule-based expert system is developed in which the system identifies and classifies the different types of nonlinear loads from the input current waveforms. The expert system with its user interface has been developed in MATLAB and it has been verified with real current measurements. The results obtained prove that the system enables accurate identification of nonlinear loads.

Characterizing nonlinear load harmonics using fractal analysis

Power quality has become a major concern to both utilities and their consumers because equipments currently are more sensitive to power quality related disturbances. One of the power quality concerns that have received most attention is the problem of harmonics which are generated by widely dispersed nonlinear loads. In order to fully understand the problem of harmonic distortion, an effective means of identifying the harmonic patterns generated by different types of nonlinear loads considered. This paper presents the application of fractal analysis for analyzing the various harmonic current waveforms generated by typical nonlinear loads such as personal computers, fluorescent lights, UPS, oscilloscope, monitor and laser jet printer. The fractal technique provides both time and spectral information of the nonlinear load harmonic patterns. The analysis results shows that the various harmonic current waveforms can be easily identified from the characteristics of the fractal features. This investigation proves that the fractal technique is useful tool for identifying harmonic current waveforms and forms a basis towards the development of the harmonic load recognition system.

Determining harmonic characteristics of typical single phase non-linear loads

Harmonic distortion in typical commercial office buildings is growing due to the widespread use of single phase nonlinear loads. This paper presents a method for developing various non-linear load models so as to analyze the current harmonic waveform characteristics of these loads. The electromagnetic transient simulation program (PSCAD/EMTDC) was used in modeling some of the non-linear loads such as personal computers, uninterruptible power supply and fluorescent lamp with electronic ballast. Simulation results provide the estimate of the harmonic currents in terms of the total harmonic distortion and the individual harmonic current components. The results obtained from simulations are then verified by the experimental results.

Performance of oil palm kernel shell gasification using a medium-scale downdraft gasifier

ABSTRACT This article focused on the performance of oil palm kernel shell (PKS) gasification using a medium-scale downdraft gasifier with a feedstock capacity of 500 kg at a temperature range of 399–700°C and at a feed rate of 177 kg/h. This article is important for evaluating the reliability of PKS gasification for commercial power generation activities from biomass. The process performance was evaluated based on the syngas calorific value (CV), syngas flow rate, and its cold gas efficiency (CGE). The syngas flow rates and CVs were measured using a gas flow meter and a gas analyzer in real time. The data obtained were then analyzed to evaluate the performance of the process. The results showed that the CGE of the process was moderately high (51%) at 681°C, with a high syngas CV (4.45–4.89 MJ/Nm3) which was ideal for gas engine applications. The PKS gasification performance increased when the reactor temperature increased. Projections were made for the CGE and the syngas CV for the PKS gasification with increased reactor temperatures and it was found that these values could be increased up to 80% and 5.2 MJ/Nm3, respectively at a reactor temperature of 900°C. In addition, the estimated power that could be generated was about 600 kWe at a maximum operation of 500 kg/h of feed rate. Based on the analysis, a medium-scale PKS gasification is observed to be a promising process for power generation from biomass due to the favorable performance of the process.