Abstract: Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.
Abstract: This paper presents a novel control strategy of a threephase
four-wire Unified Power Quality (UPQC) for an improvement
in power quality. The UPQC is realized by integration of series and
shunt active power filters (APFs) sharing a common dc bus capacitor.
The shunt APF is realized using a thee-phase, four leg voltage source
inverter (VSI) and the series APF is realized using a three-phase,
three leg VSI. A control technique based on unit vector template
technique (UTT) is used to get the reference signals for series APF,
while instantaneous sequence component theory (ISCT) is used for
the control of Shunt APF. The performance of the implemented
control algorithm is evaluated in terms of power-factor correction,
load balancing, neutral source current mitigation and mitigation of
voltage and current harmonics, voltage sag and swell in a three-phase
four-wire distribution system for different combination of linear and
non-linear loads. In this proposed control scheme of UPQC, the
current/voltage control is applied over the fundamental supply
currents/voltages instead of fast changing APFs currents/voltages,
there by reducing the computational delay and the required sensors.
MATLAB/Simulink based simulations are obtained, which support
the functionality of the UPQC. MATLAB/Simulink based
simulations are obtained, which support the functionality of the
UPQC.