In this paper, we have suggested the STATCOM
(STATic synchronous COMpensator) to connect PV-solar (or
wind) frame to the power system for the Hassia industrial city
which we chose as a case study. This frame will provide the city
with the required power, improve the power quality and inject
the redundant to the power system.
This paper presents a new technique based on artificial neural networks (ANNs) to
correct power factor. A synchronous motor controlled by the neural controller was used to
handle the problem of reactive power compensation of the system, in order to
correct
power factor.
In this paper, the electrical system and the neural controller were simulated using
MATLAB. The results have shown that the presented technique overcomes the problems
in conventional compensators (using static capacitors) such as time delay and step changes
of reactive power besides to the fast compensation compared to the technique with
capacitors groups.
This paper proposes a new approach to control a Shunt active filter (SAF) to
eliminate harmonic currents and compensate reactive power , this approach called
Predictive Direct Power Control (P-DPC) where the Direct Power Control is combined
with a
Predictive Control , PDC controls active and reactive power to get an unity power
factor and when it combined with Predictive Control , the controller can predict future
behavior for all possible voltage vectors , and the best vector is chosen for the next sample
by minimizing a cost function . we connect this filter with a nonlinear load to the grid and
simulate this systemusing Matlab , Simulink and Simpower , the results shows that P-DPC
decrease Total Harmonic Distortion (THD%) of line current and make it sinusoidal and
improve the power factor .
