Applied Sciences (Mar 2023)

Predictive Control for Current Distortion Mitigation in Mining Power Grids

  • Juan S. Gómez,
  • Alex Navas-Fonseca,
  • Freddy Flores-Bahamonde,
  • Luca Tarisciotti,
  • Cristian Garcia,
  • Felipe Nuñez,
  • Jose Rodriguez,
  • Aldo Z. Cipriano

DOI
https://doi.org/10.3390/app13063523
Journal volume & issue
Vol. 13, no. 6
p. 3523

Abstract

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Current distortion is a critical issue of power quality because the low frequency harmonics injected by adjustable speed drives increase heating losses in transmission lines and induce torque flickering in induction motors, which are widely used in mining facilities. Although classical active filtering techniques mitigate the oscillatory components of imaginary power, they may not be sufficient to clean the sensitive nodes of undesirable power components, some of which are related to real power. However, the usage of power electronic converters for distributed generation and energy storage, allows the integration of complementary power quality control objectives in electrical systems, by using the same facilities required for active power transferring. This paper proposes a predictive control-based scheme for mitigating the current distortion in the coupling node between utility grid and the mining facility power system. Instead of the classical approach of active filtering, this task is included as a secondary level objective control referred into the microgrid control hierarchy. Hardware-in-the-Loop simulation results showed that the proposed scheme is capable of bounding the current distortion, according to IEEE standard 1547, for both individual harmonics and the total rated current distortion, through inequality constraints of the optimization problem.

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