Abstract
Nonlinear loads produce current harmonics. The harmonic current flowing through the nonzero impedance of the electrical network, produce harmonics in supply voltage. Harmonics in power systems cause many ill effects and economic losses. To minimise the losses, IEEE: 519- 1992 has specified limits on voltage and current harmonics. Inductive loads like induction motors produce lagging power factor of less than unity. Capacitors are often used to improve the power factor by adding them in shunt with inductive loads. When high frequency harmonic currents flow through the network, due to the combination of inductive and capacitive loads (which are linear), resonance occurs. This causes an amplification of harmonics. Consequently, the increased harmonics affect the linear loads and produce more losses. This paper explains the results of harmonics measurements by a class of neural network, ADALINE implemented on a digital signal processor. Measurements were carried out when capacitors were grouped in one place and after their relocation nearer to the linear loads. The results show that, relocation of capacitors have minimised both voltage and current harmonics significantly. This methodology is very economical since it does not require any additional equipment for filtering of harmonics.
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