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Design Considerations for Parallel Differential Power Processing Converters in a Photovoltaic-Powered Wearable Application

Author

Listed:
  • Hyunji Lee

    (Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan 44919, Korea)

  • Katherine A. Kim

    (Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan 44919, Korea)

Abstract

Solar photovoltaic (PV) power is a widely used to supply power to the electric grid but can also be used in lower-power emerging applications, like in wearables or the internet of things. One fundamental challenge of using PV power in flexible wearable applications is that individual PV modules point at various angles, thus receiving different light intensities. Using a series configuration for the PV modules greatly decreases power utilization under uneven irradiance conditions. Parallel differential power processing (DPP) converters are employed to address this power reduction problem, while maintaining individual PV control and maximizing output power. Two parallel DPP configurations, with and without a front-end converter, are analyzed and compared for a target battery-charging application. The DPP system without a front-end converter shows consistently high performance and operates properly over a wider range of lighting conditions. Maximum power point tracking (MPPT) algorithms are also examined for parallel DPP systems. When the MPPT parameters are properly calibrated, simulation results indicate that voltage-offset resistive control is the most effective at maximizing PV power under unbalanced lighting conditions.

Suggested Citation

  • Hyunji Lee & Katherine A. Kim, 2018. "Design Considerations for Parallel Differential Power Processing Converters in a Photovoltaic-Powered Wearable Application," Energies, MDPI, vol. 11(12), pages 1-17, November.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3329-:d:186350
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    References listed on IDEAS

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    1. Carlos Olalla & Md. Nazmul Hasan & Chris Deline & Dragan Maksimović, 2018. "Mitigation of Hot-Spots in Photovoltaic Systems Using Distributed Power Electronics," Energies, MDPI, vol. 11(4), pages 1-16, March.
    2. Jena, Debashisha & Ramana, Vanjari Venkata, 2015. "Modeling of photovoltaic system for uniform and non-uniform irradiance: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 400-417.
    3. Mokhinabonu Mardonova & Yosoon Choi, 2018. "Review of Wearable Device Technology and Its Applications to the Mining Industry," Energies, MDPI, vol. 11(3), pages 1-14, March.
    4. Henrik Zsiborács & Nóra Hegedűsné Baranyai & András Vincze & István Háber & Gábor Pintér, 2018. "Economic and Technical Aspects of Flexible Storage Photovoltaic Systems in Europe," Energies, MDPI, vol. 11(6), pages 1-17, June.
    5. Henrik Zsiborács & Attila Bai & József Popp & Zoltán Gabnai & Béla Pályi & István Farkas & Nóra Hegedűsné Baranyai & Mihály Veszelka & László Zentkó & Gábor Pintér, 2018. "Change of Real and Simulated Energy Production of Certain Photovoltaic Technologies in Relation to Orientation, Tilt Angle and Dual-Axis Sun-Tracking. A Case Study in Hungary," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    6. Gábor Pintér & Nóra Hegedűsné Baranyai & Alec Wiliams & Henrik Zsiborács, 2018. "Study of Photovoltaics and LED Energy Efficiency: Case Study in Hungary," Energies, MDPI, vol. 11(4), pages 1-13, March.
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