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Predictive Control of Power Electronics Converters in Renewable Energy Systems

Author

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  • Jiefeng Hu

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Ka Wai Eric Cheng

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

Abstract

Predictive control has attracted much attention and has been widely used in power electronics and electric drives. However, further developments for applications in the field of renewable energy systems are still under investigation. In this paper, the principles of predictive control are studied with a focus on model predictive control (MPC) and vector-sequence-based predictive control (VPC). Based on these techniques, two control strategies for flexible power supply are developed. They are implemented in the most promising renewable energy systems, namely solar photovoltaic (PV) systems and wind generators, respectively. The experimental results based on a laboratory prototype show that the active and reactive powers supplied by the PV and wind generator can be controlled flexibly with excellent steady-state and transient performance. As the penetration level of the renewable energy sources in electricity network continues to rise, predictive control tends to be an attractive and powerful technique for power electronics converters in renewable energy systems.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:515-:d:95443
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    References listed on IDEAS

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    Cited by:

    1. Bo Chen & Ping Wang & Yifeng Wang & Wei Li & Fuqiang Han & Shuhuai Zhang, 2017. "Comparative Analysis and Optimization of Power Loss Based on the Isolated Series/Multi Resonant Three-Port Bidirectional DC-DC Converter," Energies, MDPI, vol. 10(10), pages 1-26, October.
    2. Ramon Guzmán & Luís García de Vicuña & Miguel Castilla & Jaume Miret & Antonio Camacho, 2017. "Finite Control Set Model Predictive Control for a Three-Phase Shunt Active Power Filter with a Kalman Filter-Based Estimation," Energies, MDPI, vol. 10(10), pages 1-14, October.
    3. Cheng-Shan Wang & Wei Li & Yi-Feng Wang & Fu-Qiang Han & Bo Chen, 2017. "A High-Efficiency Isolated LCLC Multi-Resonant Three-Port Bidirectional DC-DC Converter," Energies, MDPI, vol. 10(7), pages 1-22, July.
    4. Yaqi Wang & Zhigang Liu, 2018. "Suppression Research Regarding Low-Frequency Oscillation in the Vehicle-Grid Coupling System Using Model-Based Predictive Current Control," Energies, MDPI, vol. 11(7), pages 1-21, July.
    5. 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.
    6. Yiwang Wang & Chun Gan & Kai Ni & Xinhua Li & Houjun Tang & Yong Yang, 2017. "A Multifunctional Isolated and Non-Isolated Dual Mode Converter for Renewable Energy Conversion Applications," Energies, MDPI, vol. 10(12), pages 1-17, November.
    7. Muhammad M. Fayyaz & Irtaza M. Syed & Yi Meng & Muhammad N. Aman, 2023. "Comprehensive Predictive Control Model for a Three-Phase Four-Legged Inverter," Energies, MDPI, vol. 16(6), pages 1-18, March.
    8. Huakun Bi & Ping Wang & Zhishuang Wang, 2018. "Common Grounded H-Type Bidirectional DC-DC Converter with a Wide Voltage Conversion Ratio for a Hybrid Energy Storage System," Energies, MDPI, vol. 11(2), pages 1-22, February.
    9. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    10. Feras Alasali & Stephen Haben & Victor Becerra & William Holderbaum, 2017. "Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems," Energies, MDPI, vol. 10(10), pages 1-18, October.

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