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Energy harvesting from the PV Hybrid Power Source

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  • Bizon, Nicu

Abstract

In this paper it is proposed a Maximum Power Point (MPP) tracking technique for the photovoltaic (PV) system based on an advanced Extremum Seeking (aES) control that improves both basic performances of the ES control schemes: guaranteed convergence and proved internal robustness. Beside these features that are necessary in case of unmodeled dynamics, other features such as higher search speed and improved accuracy of the MPP tracking process are demonstrated. Thus, different irradiance sequences are used to test the performances of the MPP tracking process, where each of them could represent a worse scenario than in reality. Analysis in the frequency domain reveals the main relationships between the aES control parameters (the values of closed loop gain and dither amplitude) and the performance indicators (the search speed and tracking accuracy). If the dither amplitude is set to be proportional with the magnitude of the first harmonic of the PV power processed in the ES control loop, then the aES control will exhibit a negligible power ripple after the MPP was caught. Therefore, the proposed aES control outperforms all ES control schemes in overall power efficiency.

Suggested Citation

  • Bizon, Nicu, 2013. "Energy harvesting from the PV Hybrid Power Source," Energy, Elsevier, vol. 52(C), pages 297-307.
    • Handle: RePEc:eee:energy:v:52:y:2013:i:c:p:297-307
    DOI: 10.1016/j.energy.2013.02.006
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    1. Singh, Rajinesh & Kearney, Michael P. & Manzie, Chris, 2013. "Extremum-seeking control of a supercritical carbon-dioxide closed Brayton cycle in a direct-heated solar thermal power plant," Energy, Elsevier, vol. 60(C), pages 380-387.
    2. Bizon, Nicu, 2018. "Optimal operation of fuel cell/wind turbine hybrid power system under turbulent wind and variable load," Applied Energy, Elsevier, vol. 212(C), pages 196-209.
    3. Bizon, Nicu, 2016. "Global Maximum Power Point Tracking (GMPPT) of Photovoltaic array using the Extremum Seeking Control (ESC): A review and a new GMPPT ESC scheme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 524-539.
    4. Bizon, Nicu & Thounthong, Phatiphat, 2018. "Real-time strategies to optimize the fueling of the fuel cell hybrid power source: A review of issues, challenges and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1089-1102.
    5. Ehsan, M. Monjurul & Guan, Zhiqiang & Gurgenci, Hal & Klimenko, Alexander, 2020. "Feasibility of dry cooling in supercritical CO2 power cycle in concentrated solar power application: Review and a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    6. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.

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