Neural network based enhancement of power quality in distribution system

Author

Nayar, Priya ; Singh, Bhim ; Mishra, Sukumar

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., New Delhi, New Delhi, India

fYear

2014

Firstpage

1

Lastpage

5

Abstract

An application of artificial intelligence is presented in solving power quality problems using a distribution static compensator (DSTATCOM) in the distribution system involving lagging pf loads. A set of three nonlinear neurons is used to obtain the three phase compensating currents. Another set of three layered feed-forward neural network controls the compensating currents. The developed model works accurately under varying load conditions and provides good dynamic response to the step changes in the load currents. A real time performance is achieved using SIMULINKR/Sim-powersystem (SPS) toolboxes and simulated results adhere to the IEEE-519 standard for improvement of power quality.

Keywords

IEEE standards; artificial intelligence; distribution networks; dynamic response; electric current control; feedforward neural nets; power engineering computing; power supply quality; static VAr compensators; DSTATCOM; IEEE-519 standard; SPS; Sim-powersystem; artificial intelligence; distribution static compensator; distribution system; dynamic response; feedforward neural network based power quality enhancement; load lagging; three nonlinear neuron; three phase compensating current control; Capacitors; Harmonic analysis; Neural networks; Power harmonic filters; Power quality; Reactive power; Voltage control; ANN; DSTATCOM; PCC; Power quality; power factor regulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics (IICPE), 2014 IEEE 6th India International Conference on

Print_ISBN

978-1-4799-6045-3

Type

conf

DOI

10.1109/IICPE.2014.7115752

Filename

7115752