Ahmad Farid Abidin

A new tracking method of symmetrical fault during Power Swing Based on S-Transform

Current distance relay is accommodated with Power Swing Blocking (PSB) scheme. However, this blocking scheme prove to vulnerable to distance relay operation as it could block the trip signals if the symmetrical fault occur during power swing. Hence, it is important to develop the proper fault detection scheme during power swing to avoid such undesirable circumstances. This paper presents a new detection technique to detect symmetrical fault during power swing by using S-Transform analysis based on the current, voltage, and three-phase active and reactive power signals waveform. To evaluate the effectiveness of the proposed technique, testing has been conducted under IEEE 9 bus test system. Simulation results show that the proposed technique can reliably detect symmetrical fault occurring during power swing.

Economic load dispatch with valve-point loading effect by using Differential Evolution Immunized Ant Colony optimization technique

Economic load dispatch is conducted by the utilities in order to determine the best generation level at the most feasible operating cost. In order to guarantee satisfying energy delivery to the consumer, a precise calculation of generation level is required. In order to achieve accurate and practical solution, several considerations such as prohibited operating zones, valve-point effect and ramp-rate limit need to be taken into account. However, these considerations cause the optimization to become complex and difficult to solve. This research focuses on the valve-point effect that causes ripple in the fuel-cost curve. This paper also proposes Differential Evolution Immunized Ant Colony Optimization (DEIANT) in solving economic load dispatch problem with valve-point effect. Comparative studies involving DEIANT, EP and ACO are conducted on IEEE 30-Bus RTS for performance assessments. Results indicate that DEIANT is superior to the other compared methods in terms of calculating lower operating cost and power loss.

Intelligent Power Swing Detection Scheme to Prevent False Relay Tripping Using S-Transform

Abstract Distance relay design is equipped with out-of-step tripping scheme to ensure correct distance relay operation during power swing. The out-of-step condition is a consequence result from unstable power swing. It requires proper detection of power swing to initiate a tripping signal followed by separation of unstable part from the entire power system. The distinguishing process of unstable swing from stable swing poses a challenging task. This paper presents an intelligent approach to detect power swing based on S-Transform signal processing tool. The proposed scheme is based on the use of S-Transform feature of active power at the distance relay measurement point. It is demonstrated that the proposed scheme is able to detect and discriminate the unstable swing from stable swing occurring in the system. To ascertain validity of the proposed scheme, simulations were carried out with the IEEE 39 bus system and its performance has been compared with the wavelet transform–based power swing detection scheme.

The use of S-Transform for distance relay's power swing detection

This paper presents an intelligent approach for detecting power swing for distance relay operation. The proposed scheme uses time-frequency transform known S-Transform for feature extraction. It is based on S-Transform analysis on the active power measured at distance relay point in transmission line. The proposed scheme overcomes the traditional relay scheme drawback, by detecting and discriminating the unstable from stable swing occurring in the system. To ascertain validity of the proposed scheme, simulations were carried out with the IEEE 39 bus system. Test results show that the proposed scheme can reliably be used for detecting unstable swing from stable swing.

S-Transform based technique to detect high resistance symmetrical fault during power swing

Distance relay is designed to operate when fault occurs in the system, but still should block the operation when power swing occurs in the system. However, this blocking scheme prove to vulnerable to distance relay operation as it could block the trip signals when a genuine fault occurs in the system during power swing. Hence, it is desired to develop the proper fault detection technique during power swing to avoid such circumstances. This paper presents S-Transform based detection technique to detect symmetrical fault with high resistance up to 200 Ω during power swing. The proposed scheme is based on S-Transform analysis on the current and voltage waveforms. The effectiveness of the proposed scheme was verified with the IEEE 14 bus test system and simulations results show that the proposed technique can detect high resistance symmetrical fault occurring during power swing from 5 Ω up to 200 Ω.

Modelling neutral to earth voltage (NTEV) on the commercial building

Power Quality (PQ) problems on distribution system (DS) can be categorized as voltage sag, voltage swell, harmonic, transient and others. Nowadays, due to the nonlinear loads, imbalanced loads, improper wiring and poor grounding on DS, the neutral to earth voltage (NTEV) become issue of the PQ problem. Generally, magnitude of the NTEV is zero value if the system is balance, however it changes to the nonzero value due many factor as mention above. Furthermore, in order to study the effect and factor of commercial building and DS, a reliable model need to be applied. The main contribution of this paper is to determine NTEV and NC magnitude and shape in the DS. Then, this paper presented the model of the three phase four-wire underground cable on the commercial building; the comparison of measurement data and simulation result on the NTEV and NC. This model using XLPE cable as the connection from the transformer to the load, CIM as the load at commercial building, and RLC ground electrode as the grounding system. In order to validated this simulation, the model is tested on the two different data of the commercial building. The simulation results are similar identical with the measurement, even the shape of the NTEV and NC are different. As the conclusion, the objective is to determine the magnitude and shape of the NTEV and NC are successfully done and this model can be used to determine the NTEV rise on the others commercial building and also can be used to study the factor contribution due to elevated of NTEV.

Classification of Power Quality Disturbance Based on Continuous S-Transform-Windowing Technique (CST-WT) and ANOVA as a Feature Selection

This paper was conducted in order to identify and classify the different types of Power Quality Disturbances (PQD) based on a new approach the Analysis Of Variance (ANOVA). ANOVA is used as feature selection for the PQD parameters. The datum of PQD from the PSCAD/EMTDC® simulation and Power Quality Monitoring has been validated before feature extraction analysis can be commenced. The obtained datum is then analyzed by using Windowing Technique (WT) based on Continuous S-Transform (CST) to extract the features and its characteristics. Moreover, the study focuses an important issue concerning the identification of PQD selection, detection and classification. The feature and characteristics of three types of signal such as sag, swell, and transient signal are obtained. The outcome of the analysis shows that a new approach framework ANOVA-Based Before and After Neural Network (NN) classification has a slightly increases to 15-25% in term of classification of PQD.

Modified Swarm Firefly Algorithm for Optimal Settings of Directional Overcurrent Relays

This paper presents a new approach known as Modified Swarm Firefly Algorithm (MSFA) technique in solving Directional Overcurrent Relays (DOCRs) coordination problem by minimizing the operating time of primary relays at near-end fault. DOCRs coordination requires the optimal values of Time Multiplier Setting (TMS) whereas the pickup current (Ip) values are based on load and data fault. The proposed technique is tested on IEEE 14-bus system and is compared with Particle Swarm Optimization (PSO). The simulation results revealed that the MSFA technique outperformed PSO in terms of minimizing fitness values.

Comparison of speech features for Arabic phonemes recognition system based Malay speakers

The selection of the proper feature extraction method is an essential issue for any Automatic Speech Recognition system. This has been conducted in order to choose the suitable feature extraction method for Arabic phoneme recognition system based Malay speakers. In this paper, the implementation of three feature extraction methods involves Frequency Cepstral Coefficients (MFCC), Linear Predictive Coefficients (LPC) and Perceptual Linear Prediction (PLP) has been done. And each feature extraction method is applied on Arabic phonemes in two cases the first case is; the signal is noisy and the second case is the signal is enhanced. The phoneme signals enhancement is achieved using wiener filter. Feed-Forward Neural Network is implemented as a recognizer. The outcome of this study shows that proposed system can give the highest recognition rate with MFCC. The recognition rate is 95.3% and 98.12% in the case of noisy phoneme signal and enhanced phoneme signal respectively. The evaluation and testing the feature extraction methods were based on Arabic phonemes corpus has collected from Malay speakers.

A New Reliable Algorithm for Identifying Types of Partial Discharge Detected through Ultrasonic Emission

This paper presents a simple, consistent and reliable technique to identify detected partial discharges (PD) using an acoustic ultrasonic method. A new reliable algorithm named ‘Simple Partial Discharge Identifier’ (SPDI) is proposed to perform identification process of the detected ultrasonic signals of PD. Experimental works based on recommended practices were setup and the ultrasonic signals of the PD were recorded. The PD data is then employed as the reference data. The SPDI developed has been tested against commonly used models in Neural Network (NN). Results from the SPDI algorithm shows more reliable results compared to NN models results. Comparison made on the mean square error (MSE) results shows SPDI produces the desired outcome with lower MSE in 97.17% of trials. Low error of SPDI indicates a high reliability to be applied in the identification of PD.