With an increase of non-linear load in today’s electrical power systems, the rate of power quality drops and the voltage source and frequency deteriorate if not properly compensated with an appropriate device. Filters are most common techniques that employed to overcome this problem and improving power quality. In this paper an improved optimization technique of filter applies to the power system is based on a particle swarm optimization with using artificial neural network technique applied to the unified power flow quality conditioner (PSO-ANN UPQC). Design particle swarm optimization and artificial neural network together result in a very high performance of flexible AC transmission lines (FACTs) controller and it implements to the system to compensate all types of power quality disturbances. This technique is very powerful for minimization of total harmonic distortion of source voltages and currents as a limit permitted by IEEE-519. The work creates a power system model in MATLAB/Simulink program to investigate our proposed optimization technique for improving control circuit of filters. The work also has measured all power quality disturbances of the electrical arc furnace of steel factory and suggests this technique of filter to improve the power quality.
The modeling and calculation of a single phase-to-earth fault of 6 to 35 kV have specific features when compared with circuits with higher nominal voltages. In this paper, a mathematical analysis and modeling of a 3-phase overhead transmission line with distributed parameters consisting of several nominal T-shaped, 3-phase links with concentrated parameters replaced by 1 nominal T-shaped link were carried out. Further analysis showed that not accounting for the distributed nature of the line parameters did not cause significant errors in the assessment of the maximum overvoltage in the arc suppression in single phase-to-earth faults, and that sufficient accuracy insures the representation of the line by only 1 nominal T-shaped, 3-phase link. Such a modeling technique makes it impossible to identify the location of single-phase faults, which is the property of higher harmonic amplification of individual frequencies. Chain equivalent schemas with constant parameters are valid for a single frequency, thereby providing an opportunity to study the nature of the wave process by the discrete selection of parameters. Next in the mathematical representation, we consider the overhead transmission lines as lines with distributed parameters.
The LaGrange iterative method was construct to solve the problem of power losses reduction case to minimize the total fuel cost generation. It difficult to optimize nonlinearity cost functions of fuel generators in power systems with equality and inequality constraints. This paper presents an approach method of optimization for solving the economic load dispatch (ELD) problem with generator constraints and satisfying the load demand irrespective of transmission line losses. To verify the proposed work, an artificial neural network (ANN) based Lambda iterative optimization method with Matlab R2018a program is being apply to the test system. The numerical studies have been accomplished to IEEE model system (30-bus 6-generator, 41-line and 20-load). The results have manifests the effectiveness of the supposed algorithms because it can provide accurate dispatch solutions with wide range of load demand in minimum total cost. Further analyses indicate the total power losses in the system.
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