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A hierarchical predictive control for supercapacitor-retrofitted grid-connected hybrid renewable systems

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  • Masaki, Mukalu Sandro
  • Zhang, Lijun
  • Xia, Xiaohua

Abstract

This paper presents a two-layer control strategy designed for easy integration of supercapacitors in a grid-integrated solar photovoltaic-battery hybrid renewable system, initially controlled by a typical model predictive control method. To operate the upgraded energy system, either without or with little modifications of the pre-existing architecture, an additional control layer is applied at the bottom of the original control system. Considering the complementary characteristics of batteries and supercapacitors, the design of the new model predictive control layer and its coordination with the original one help to deliver a stable power flow between the hybrid renewable system and the utility grid, and remove fast variations from the battery power. Actual measurements of solar radiation in South Africa are used to test the effectiveness of the proposed strategy. Simulations carried out on a 1-MW photovoltaic plant confirm the benefits in terms of adherence to power quality regulations, improved conditioning of the power generated by the intermittent renewable sources, and lifetime extension of the battery.

Suggested Citation

  • Masaki, Mukalu Sandro & Zhang, Lijun & Xia, Xiaohua, 2019. "A hierarchical predictive control for supercapacitor-retrofitted grid-connected hybrid renewable systems," Applied Energy, Elsevier, vol. 242(C), pages 393-402.
    • Handle: RePEc:eee:appene:v:242:y:2019:i:c:p:393-402
    DOI: 10.1016/j.apenergy.2019.03.049
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    References listed on IDEAS

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    2. Arévalo, Paul & Benavides, Dario & Tostado-Véliz, Marcos & Aguado, José A. & Jurado, Francisco, 2023. "Smart monitoring method for photovoltaic systems and failure control based on power smoothing techniques," Renewable Energy, Elsevier, vol. 205(C), pages 366-383.
    3. Jura Arkhangelski & Pedro Roncero-Sánchez & Mahamadou Abdou-Tankari & Javier Vázquez & Gilles Lefebvre, 2019. "Control and Restrictions of a Hybrid Renewable Energy System Connected to the Grid: A Battery and Supercapacitor Storage Case," Energies, MDPI, vol. 12(14), pages 1-23, July.
    4. Lin, Dong & Zhang, Lijun & Xia, Xiaohua, 2021. "Model predictive control of a Venlo-type greenhouse system considering electrical energy, water and carbon dioxide consumption," Applied Energy, Elsevier, vol. 298(C).
    5. Clarke, Will Challis & Brear, Michael John & Manzie, Chris, 2020. "Control of an isolated microgrid using hierarchical economic model predictive control," Applied Energy, Elsevier, vol. 280(C).
    6. Nicu Bizon & Phatiphat Thounthong, 2020. "Energy Efficiency and Fuel Economy of a Fuel Cell/Renewable Energy Sources Hybrid Power System with the Load-Following Control of the Fueling Regulators," Mathematics, MDPI, vol. 8(2), pages 1-22, January.
    7. Long, Guimin & Ding, Fei & Zhang, Nong & Zhang, Jie & Qin, An, 2020. "Regenerative active suspension system with residual energy for in-wheel motor driven electric vehicle," Applied Energy, Elsevier, vol. 260(C).

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