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Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems

Author

Listed:
  • João Martins

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, DK-9220 Aalborg, Denmark)

  • Sergiu Spataru

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, DK-9220 Aalborg, Denmark)

  • Dezso Sera

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, DK-9220 Aalborg, Denmark)

  • Daniel-Ioan Stroe

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, DK-9220 Aalborg, Denmark)

  • Abderezak Lashab

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, DK-9220 Aalborg, Denmark)

Abstract

The high variability of solar irradiance, originated by moving clouds, causes fluctuations in Photovoltaic (PV) power generation, and can negatively impact the grid stability. For this reason, grid codes have incorporated ramp-rate limitations for the injected PV power. Energy Storage Systems (ESS) coordinated by ramp-rate (RR) control algorithms are often applied for mitigating these power fluctuations to the grid. These algorithms generate a power reference to the ESS that opposes the PV fluctuations, reducing them to an acceptable value. Despite their common use, few performance comparisons between the different methods have been presented, especially from a battery status perspective. This is highly important, as different smoothing methods may require the battery to operate at different regimes (i.e., number of cycles and cycles deepness), which directly relates to the battery lifetime performance. This paper intends to fill this gap by analyzing the different methods under the same irradiance profile, and evaluating their capability to limit the RR and maintain the battery State of Charge (SOC) at the end of the day. Moreover, an analysis into the ESS capacity requirements for each of the methods is quantified. Finally, an analysis of the battery cycles and its deepness is performed based on the well-established rainflow cycle counting method.

Suggested Citation

  • João Martins & Sergiu Spataru & Dezso Sera & Daniel-Ioan Stroe & Abderezak Lashab, 2019. "Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems," Energies, MDPI, vol. 12(7), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1342-:d:220875
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    1. Jian Chen & Jiaqi Li & Yicheng Zhang & Guannan Bao & Xiaohui Ge & Peng Li, 2018. "A Hierarchical Optimal Operation Strategy of Hybrid Energy Storage System in Distribution Networks with High Photovoltaic Penetration," Energies, MDPI, vol. 11(2), pages 1-20, February.
    2. Bernhard Faessler & Michael Schuler & Markus Preißinger & Peter Kepplinger, 2017. "Battery Storage Systems as Grid-Balancing Measure in Low-Voltage Distribution Grids with Distributed Generation," Energies, MDPI, vol. 10(12), pages 1-14, December.
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    14. Luis Gerardo González & Rommel Chacon & Bernardo Delgado & Dario Benavides & Juan Espinoza, 2020. "Study of Energy Compensation Techniques in Photovoltaic Solar Systems with the Use of Supercapacitors in Low-Voltage Networks," Energies, MDPI, vol. 13(15), pages 1-15, July.
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    16. Lappalainen, Kari & Valkealahti, Seppo, 2022. "Sizing of energy storage systems for ramp rate control of photovoltaic strings," Renewable Energy, Elsevier, vol. 196(C), pages 1366-1375.
    17. Felipe Ramos & Aline Pinheiro & Rafaela Nascimento & Washington de Araujo Silva Junior & Mohamed A. Mohamed & Andres Annuk & Manoel H. N. Marinho, 2022. "Development of Operation Strategy for Battery Energy Storage System into Hybrid AC Microgrids," Sustainability, MDPI, vol. 14(21), pages 1-26, October.
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