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This paper deals with the Fault Detection and Diagnosis of steam boiler using developed artificial Neural networks model. Water low level trip of steam boiler is artificially monitored and analyzed in this study, using two different interpretation algorithms. The Broyden-Fletcher-Goldfarb-Shanno quasi-Newton and Levenberg-Marquart are adopted as training algorithms of the developed neural network...
Artificial Neural Networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of a simple ANN topology for load forecasting model with much improved accuracy for the Regional Power Control Centre of Saudi Electricity Company. The proposed system is based on optimising the initial random...
This paper presents a novel ANN based technique for improving the performance of distance relays against open circuit faults in transmission networks. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open conductor condition in HVTL but also to locate the place of this fault regardless the value of the pre-fault current loading. Detailed...
This paper presents artificial neural networks and particle swarm optimization (ANN-PSO) based short-term load forecasting model with improved generalization technique for the regional power control center of Saudi Electricity Company, Western Operation Area (SEC-WOA) of Saudi Arabia. Weather, load demand, wind speed, wind direction, heat, sunlight, etc. are quite different in a desert land than other...
The paper presents a reliable method to generate on line pulse width modulation (PWM) signals with selected harmonic elimination (SHE) by using field programmable gate array (FPGA). These signals is used to drive voltage source inverter. Due to the complexity of solving the nonlinear equations, and impossibility to achieve the solution in real time and on line, therefore the solution is obtained off...
In this paper the correlation between dielectric strength, the water content and oil CO2/CO ratio with insulation resistance in oil-filled power transformers is studied using artificial neural networks. This correlation allows and improves the condition assessment of transformer insulation using the Megger test. This is because dielectric strength, water content and CO2/CO ratio are important parameters...
Intelligent techniques of harmonic detection or estimation are nowadays of a great interest in power system applications, their ability to deal with high non-linearities attract researchers to investigate the performance of these methods mainly based on artificial intelligence namely using artificial neural networks (ANNs). In the literature many harmonic detection or estimation methods were presented,...
This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation...
Long-term load forecasting has a vital role in generation, transmission and distribution network planning. Traditional studies for long-term load forecasting were based on regression method, which could not provide a true representation of power system behavior in a volatile electricity market. The purpose of this paper is to introduce two approaches based regression method and artificial neural network...
In order to succeed harmonic mitigation in electrical circuits, it's very important to estimate or extract the compensating harmonic references. Any failure in this last procedure will cause failure in the harmonic elimination. In fact, in the literature many harmonic detection or estimation methods were presented, in this paper we focus on a new idea to apply artificial intelligence methods namely...
Lightning surge is actually being considered as one of the most dangerous events in power distribution systems. Basically, it hits the overhead distribution line then propagates to the other network components, such as underground cables and transformers. Due to lightning strokes, insulation failure of such components could occur. The failure risk can be determined on the basis of network configuration,...
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