Certain Investigation of Real power flow control of Artificial Neural Network based Matrix converter-Unified Power Flow Controller in IEEE 14 Bus system

  • Boopalan C C. Abdul Hakeem College of Engineering & Technology, Vellore, Tamil Nadu, India.
  • Saravanan V. Department of EEE, Arunai Engineering College, Tiruvannamalai, Tamil Nadu India.
Keywords: MC-UPFC, FACTS, Proportional Integral derivative, Artificial Neural Network

Abstract

The power consumption is rapid increased due to ASD (Adjustable Speed Drives) and automation in industries and large consumption of electricity in domestic regions increased the concern of the power quality. The quality of the power received in the Distribution system is altered because of the losses in the transmission system. The losses in the transmission system is mitigated using the FACTS (Flexible AC Transmission System)controller among these controllers UPFC (Unified Power Flow Controller) plays a vital role in controlling the shunt and series reactive powers in the bus of the power system. The conventional topology of the UPFC consists of AC-DC converter and energy stored in the DC link and DC-AC converter injected a voltage in series to the bus which as to be controlled. Whereas a new topology based on matrix converter can replace the dual converters and perform the required task. The construction of 2-bus, 7-bus and IEEE-14-bus power system is designed and modeled. MC-UPFC (Matrix Converter Based Unified Power Flow Controller) is designed and constructed. The MC-UPFC is the rich topology in the FACTS which is capable of controlling both the transmission parameters simultaneously with the switching technique of Direct power control by the smooth sliding control which gives less ripple in the injecting control parameters such as control voltage [Vc] and voltage angle [α]. By implementing MC-UPFC the real and reactive power can be controlled simultaneously and independently. The control techniques were designed based on the Proportional Integral derivative(PID) with sliding surface power control, FLC (Fuzzy Logic Controller) and ANN (Artificial Neural Network)  and  the performance of  Vc and α of the controllers are investigated. Hence the sliding surface and relevant control switching state of the MC can be controlled by the FLC which gives the robust and autonomous decision making in the selection of the appropriate switching state for the effective real power control in the power system. The work has been carried out in the MATLAB Simulink simulator which gives the finest controlling features and simple design procedures and monitoring of the output.

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Published
2020-10-30
How to Cite
C, B., & V., S. (2020). Certain Investigation of Real power flow control of Artificial Neural Network based Matrix converter-Unified Power Flow Controller in IEEE 14 Bus system. International Journal of Computer Communication and Informatics, 2(2), 54-81. https://doi.org/10.34256/ijcci2026



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