A Dual Control Strategy for Phase Balancing in Three-Phase Four Wire Distribution Systems by Artificial Neural Network

Abstract

An electrical power system comprises of large number of large number electrical and electronic equipment. These are also used in much number of commercial and industrial applications. In the present scenario, the usage of AC loads in the industrial sector is improving which in turn leads to reactive power problems. Due to the usage of devices like arc furnaces, welding devices and other such instruments which causes flickering and voltage sag, the power quality gets reduced in the system. In this project, a power quality controller is used to mitigate the voltage sag problem in the network. DSTATCOM is used as a compensator here. The system efficiency is improved by training the network through Artificial Neural Network (ANN) algorithm. The proposed technique mitigates harmonic and reactive current problems and ensures balanced and sinusoidal source of current from the supply mains that are nearly in phase with the supply voltage and it also compensates neutral current under varying source and load conditions. The modified system is superior over conventional methods as it eliminates the sensors needed for sensing load current and coupling inductor current. ANN controllers are implemented to maintain voltage across the capacitor and to act as a compensator to compensate neutral current. The performance of the DSTATCOM is validated for all possible conditions of source and loads by analysing the simulation results obtained through MATLAB software and simulation results prove that the proposed control strategy is more efficient than the conventional control techniques.

Authors and Affiliations

Ms. S. Poorani S, Dr. G. Karthikeyan

Keywords

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  • EP ID EP23921
  • DOI http://doi.org/10.22214/ijraset.2017.4215
  • Views 275
  • Downloads 9

How To Cite

Ms. S. Poorani S, Dr. G. Karthikeyan (2017). A Dual Control Strategy for Phase Balancing in Three-Phase Four Wire Distribution Systems by Artificial Neural Network. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(4), -. https://europub.co.uk/articles/-A-23921