No abstract

No abstract

The power transmission system is essential for the power scheme to transfer the energy from generators to consumers. The short circuit problem repeatedly occurs in the transmission system, and the main problem is to separate the sources from users. This research has applied two hybrid techniques to predict fault location. The first hybrid technique has involved the Discrete Wavelet Transformation (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS), while the second hybrid technique is for DWT grouping and Support Vector Machine (SVM). These hybrid techniques are intended to estimate the fault location of each fault category in a transmission system. The DWT was applied to both D8 and D9 level at the 50 kHz sample frequency. The root mean square (RMS) values of the D8 and D9 coefficients were used for training using ANFIS and SVM techniques. After that, ANFIS and SVM were utilised to detect faults in the phase and ground lines. Several types of fault have been simulated, i.e. fault location, fault resistance, and original point of view. The RMS results from the two hybrid techniques were compared to find the best results. The tests of error estimation were performed for the three bus systems. The comparison of error estimation of the two methods shows that both hybrid techniques can be applied to predict fault locations.

No abstract

No abstract

This paper present improved Walsh function (IWF) algorithm as an alternative approach for active and reactive power measurement in linear and nonlinear, balanced and unbalanced sinusoidal three phase load system. It takes advantage of Walsh function unified approach and its intrinsic high level accuracy as a result of coefficient characteristics and energy behaviour representation. The developed algorithm was modeled on the Matlab Simulink software; different types of load, linear and nonlinear were also modeled based on practical voltage and current waveforms and tested with the proposed improved Walsh algorithm. The IEEE standard 1459-2000 which is based on fast Fourier transform FFT approach was used as benchmark for the linear load system while a laboratory experiment using Fluke 435 power quality analyzer PQA which complies with IEC/EN61010-1-2001standards was used to validate the improved algorithm for nonlinear load measurement. The results showed that the algorithm has the potential to effectively measure three phase power components under different load conditions.

This paper presents the coordination between the Automatic Voltage Regulator (AVR) and Power System Stabilizers (PSS) to increase the system damping over a wide range of systems’ operating conditions in order to improve the transient stability performance and steady state performance of the system. The coordinated design problem is formulated as an optimization problem which is solved using Iteration Particle Swarm Optimization (IPSO). The application of IPSO technique is proposed to optimize the parameters of the AVR and PSS to minimize the oscillations in power system during disturbances in a single machine infinite bus system (SMIB). The performance of the proposed IPSO technique is compared with the traditional PSO technique. The comparison considered is in terms of parameter accuracy and computational time. The results of the time domain simulations and eigenvalue analysis show that the proposed IPSO method provides a better optimization technique as compared to the traditional PSO technique.

No abstract