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A power system restoration method using voltage source converter–high-voltage direct current technology, aided by time-series neural network with firefly algorithm

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Abstract

Voltage source converter (VSC)–high-voltage direct current (HVDC) has become a new trend for achieving an efficient and reliable bulk power transmission. The main challenges in VSC-HVDC link are the “soft-start-up” or the restoration of power after the system blackout, with over voltage and less response delay. In this paper, VSC-HVDC link with firefly Levenberg–Marquardt-trained artificial neural network (ANN), termed as ANN-FLM, is proposed to restore the power quickly. The simulation is performed by creating blackout in the system through the introduction of a three-phase fault. The performance analysis is made on VSC-HVDC with ANN-FLM in existing proportional integral controller. The simulated results provide faster restoration and independent control of real and reactive powers. The proposed method minimizes the over voltage to 98% in maximum point, 84% in phase A, 61% in phase B and 82% in phase C, when simulated.

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Authors and Affiliations

  1. A1 Global Institute of Engineering and Technology, Markapur, Andhra Pradesh, India

    Jan Bhasha Shaik

  2. JNTUACEP, Pulivendula, Andhra Pradesh, India

    V. Ganesh

Authors
  1. Jan Bhasha Shaik
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  2. V. Ganesh
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Correspondence to Jan Bhasha Shaik.

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Communicated by V. Loia.

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Shaik, J.B., Ganesh, V. A power system restoration method using voltage source converter–high-voltage direct current technology, aided by time-series neural network with firefly algorithm. Soft Comput 24, 9495–9506 (2020). https://doi.org/10.1007/s00500-019-04459-5

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