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On the Performance Optimization of Two-Level Three-Phase Grid-Feeding Voltage-Source Inverters

Author

Listed:
  • Issam A. Smadi

    (Department of Electrical Engineering, Faculty of Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan)

  • Saher Albatran

    (Department of Electrical Engineering, Faculty of Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan)

  • Hamzeh J. Ahmad

    (Department of Electrical Engineering, Faculty of Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan)

Abstract

The performance optimization of the two-level, three-phase, grid-feeding, voltage-source inverter (VSI) is studied in this paper, which adopts an online adaptive switching frequency algorithm (OASF). A new degree of freedom has been added to the employed OASF algorithm for optimal selection of the weighting factor and overall system optimization design. Toward that end, a full mathematical formulation, including the impact of the coupling inductor and the controller response time, is presented. At first, the weighting factor is selected to favor the switching losses, and the controller gains are optimized by minimizing the integral time-weighted absolute error (ITAE) of the output active and reactive power. Different loading and ambient temperature conditions are considered to validate the optimized controller and its fast response through online field programmable gate array (FPGA)-in-the-loop. Then, the weighting factor is optimally selected to reduce the cost of the L-filter and the heat-sink. An optimization problem to minimize the cost design at the worst case of loading condition for grid-feeding VSI is formulated. The results from this optimization problem are the filter inductance, the thermal resistance of the heat-sink, and the optimal switching frequency with the optimal weighting factor. The VSI test-bed using the optimized parameters is used to verify the proposed work experimentally. Adopting the OASF algorithm that employs the optimal weighting factor for grid-feeding VSI, the percentages of the reductions in the slope of the steady state junction temperature profile compared to fixed frequencies of 10 kHz, 14.434 kHz, and 20 kHz are about 6%, 30%, and 18%, respectively.

Suggested Citation

  • Issam A. Smadi & Saher Albatran & Hamzeh J. Ahmad, 2018. "On the Performance Optimization of Two-Level Three-Phase Grid-Feeding Voltage-Source Inverters," Energies, MDPI, vol. 11(2), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:400-:d:130993
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    References listed on IDEAS

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    1. Meenakshi Jayaraman & Sreedevi VT, 2017. "Power Quality Improvement in a Cascaded Multilevel Inverter Interfaced Grid Connected System Using a Modified Inductive–Capacitive–Inductive Filter with Reduced Power Loss and Improved Harmonic Attenu," Energies, MDPI, vol. 10(11), pages 1-23, November.
    2. Fabio Di Napoli & Alessandro Magnani & Marino Coppola & Pierluigi Guerriero & Vincenzo D’Alessandro & Lorenzo Codecasa & Pietro Tricoli & Santolo Daliento, 2017. "On-Line Junction Temperature Monitoring of Switching Devices with Dynamic Compact Thermal Models Extracted with Model Order Reduction," Energies, MDPI, vol. 10(2), pages 1-14, February.
    3. Ke Ma & Frede Blaabjerg, 2012. "The Impact of Power Switching Devices on the Thermal Performance of a 10 MW Wind Power NPC Converter," Energies, MDPI, vol. 5(7), pages 1-19, July.
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    Cited by:

    1. Vijay Kumar Singh & Ravi Nath Tripathi & Tsuyoshi Hanamoto, 2018. "HIL Co-Simulation of Finite Set-Model Predictive Control Using FPGA for a Three-Phase VSI System," Energies, MDPI, vol. 11(4), pages 1-15, April.
    2. Juan R. Lopez & Jose de Jesus Camacho & Pedro Ponce & Brian MacCleery & Arturo Molina, 2022. "A Real-Time Digital Twin and Neural Net Cluster-Based Framework for Faults Identification in Power Converters of Microgrids, Self Organized Map Neural Network," Energies, MDPI, vol. 15(19), pages 1-25, October.

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