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Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter

Author

Listed:
  • Amit Kumer Podder

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Md. Habibullah

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Md. Tariquzzaman

    (Department of Electrical and Electronic Engineering, Jashore University of Science & Technology, Jashore 7408, Bangladesh)

  • Eklas Hossain

    (Department of Electrical Engineering & Renewable Energy, Oregon Renewable Energy Center (OREC), Oregon Institute of Technology, Klamath Falls, OR 97601, USA)

  • Sanjeevikumar Padmanaban

    (Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

Abstract

This paper presents a finite control-set model predictive control (FCS-MPC) based technique to reduce the switching loss and frequency of the on-grid PV inverter by incorporating a switching frequency term in the cost function of the model predictive control (MPC). In the proposed MPC, the control objectives (current and switching frequency) select an optimal switching state for the inverter by minimizing a predefined cost function. The two control objectives are combined with a weighting factor. A trade-off between the switching frequency (average) and total harmonic distortion (THD) of the current was utilized to determine the value of the weighting factor. The switching, conduction, and harmonic losses were determined at the selected value of the weighting factor for both the proposed and conventional FCS-MPC and compared. The system was simulated in MATLAB/Simulink, and a small-scale hardware prototype was built to realize the system and verify the proposal. Considering only 0.25% more current THD, the switching frequency and loss per phase were reduced by 20.62% and 19.78%, respectively. The instantaneous overall power loss was also reduced by 2% due to the addition of a switching frequency term in the cost function which ensures a satisfactory empirical result for an on-grid PV inverter.

Suggested Citation

  • Amit Kumer Podder & Md. Habibullah & Md. Tariquzzaman & Eklas Hossain & Sanjeevikumar Padmanaban, 2020. "Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter," Energies, MDPI, vol. 13(18), pages 1-26, September.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4669-:d:410457
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    References listed on IDEAS

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    1. Xiaotao Chen & Weimin Wu & Ning Gao & Jiahao Liu & Henry Shu-Hung Chung & Frede Blaabjerg, 2019. "Finite Control Set Model Predictive Control for an LCL-Filtered Grid-Tied Inverter with Full Status Estimations under Unbalanced Grid Voltage," Energies, MDPI, vol. 12(14), pages 1-22, July.
    2. Jiefeng Hu & Ka Wai Eric Cheng, 2017. "Predictive Control of Power Electronics Converters in Renewable Energy Systems," Energies, MDPI, vol. 10(4), pages 1-14, April.
    3. Roh Chan & Sangshin Kwak, 2017. "Model-Based Predictive Current Control Method with Constant Switching Frequency for Single-Phase Voltage Source Inverters," Energies, MDPI, vol. 10(11), pages 1-21, November.
    4. Rui Qin & Chunhua Yang & Hongwei Tao & Tao Peng & Chao Yang & Zhiwen Chen, 2019. "A Power Loss Decrease Method Based on Finite Set Model Predictive Control for a Motor Emulator with Reduced Switch Count," Energies, MDPI, vol. 12(24), pages 1-25, December.
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    Cited by:

    1. Paolo Mercorelli, 2022. "Model Predictive Control for Energy Optimization in Generators/Motors as Well as Converters and Inverters for Futuristic Integrated Power Networks," Energies, MDPI, vol. 15(16), pages 1-4, August.
    2. Jaime A. Rohten & Javier E. Muñoz & Esteban S. Pulido & José J. Silva & Felipe A. Villarroel & José R. Espinoza, 2021. "Very Low Sampling Frequency Model Predictive Control for Power Converters in the Medium and High-Power Range Applications," Energies, MDPI, vol. 14(1), pages 1-18, January.
    3. Amit Kumer Podder & Sayma Afroza Supti & Sayemul Islam & Maria Malvoni & Arunkumar Jayakumar & Sanchari Deb & Nallapaneni Manoj Kumar, 2021. "Feasibility Assessment of Hybrid Solar Photovoltaic-Biogas Generator Based Charging Station: A Case of Easy Bike and Auto Rickshaw Scenario in a Developing Nation," Sustainability, MDPI, vol. 14(1), pages 1-27, December.

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