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Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems

Author

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  • Javier Marcos

    (Department of Electrical and Electronic Engineering, Public University of Navarre (UPNa), Campus Arrosadia s/n, Edificio de los Pinos, Pamplona 31006, Spain)

  • Iñigo De la Parra

    (Department of Electrical and Electronic Engineering, Public University of Navarre (UPNa), Campus Arrosadia s/n, Edificio de los Pinos, Pamplona 31006, Spain)

  • Miguel García

    (Department of Electrical and Electronic Engineering, Public University of Navarre (UPNa), Campus Arrosadia s/n, Edificio de los Pinos, Pamplona 31006, Spain)

  • Luis Marroyo

    (Department of Electrical and Electronic Engineering, Public University of Navarre (UPNa), Campus Arrosadia s/n, Edificio de los Pinos, Pamplona 31006, Spain)

Abstract

The variations in irradiance produced by changes in cloud cover can cause rapid fluctuations in the power generated by large photovoltaic (PV) plants. As the PV power share in the grid increases, such fluctuations may adversely affect power quality and reliability. Thus, energy storage systems (ESS) are necessary in order to smooth power fluctuations below the maximum allowable. This article first proposes a new control strategy (step-control), to improve the results in relation to two state-of-the-art strategies, ramp-rate control and moving average. It also presents a method to quantify the storage capacity requirements according to the three different smoothing strategies and for different PV plant sizes. Finally, simulations shows that, although the moving-average (MA) strategy requires the smallest capacity, it presents more losses (2–3 times more) and produces a much higher number of cycles over the ESS (around 10 times more), making it unsuitable with storage technologies as lithium-ion. The step-control shown as a better option in scenery with exigent ramp restrictions (around 2%/min) and distributed generation against the ramp-rate control in all ESS key aspects: 20% less of capacity, up to 30% less of losses and a 40% less of ageing. All the simulations were based on real PV production data, taken every 5 s in the course of one year (2012) from a number of systems with power outputs ranging from 550 kW to 40 MW.

Suggested Citation

  • Javier Marcos & Iñigo De la Parra & Miguel García & Luis Marroyo, 2014. "Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems," Energies, MDPI, vol. 7(10), pages 1-27, October.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:10:p:6593-6619:d:41226
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    References listed on IDEAS

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    16. Gonzalez-Moreno, A. & Marcos, J. & de la Parra, I. & Marroyo, L., 2022. "A PV ramp-rate control strategy to extend battery lifespan using forecasting," Applied Energy, Elsevier, vol. 323(C).
    17. Wei Ma & Wei Wang & Xuezhi Wu & Ruonan Hu & Fen Tang & Weige Zhang, 2019. "Control Strategy of a Hybrid Energy Storage System to Smooth Photovoltaic Power Fluctuations Considering Photovoltaic Output Power Curtailment," Sustainability, MDPI, vol. 11(5), pages 1-22, March.
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    19. Duchaud, Jean-Laurent & Notton, Gilles & Darras, Christophe & Voyant, Cyril, 2018. "Power ramp-rate control algorithm with optimal State of Charge reference via Dynamic Programming," Energy, Elsevier, vol. 149(C), pages 709-717.

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