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Sizing of energy storage systems for ramp rate control of photovoltaic strings

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  • Lappalainen, Kari
  • Valkealahti, Seppo

Abstract

In this article, a comprehensive study on the sizing of energy storage systems (ESS) for ramp rate (RR) control of photovoltaic (PV) strings is presented. The effects of RR limit and inverter sizing, including their combined effect, on the sizing of the ESS are herein studied systematically for the first time. The study is based on 38 days of current–voltage curve measurements of a PV string of 23 PV modules. The results show that the daily irradiance profile has a crucial effect on the ESS power and energy requirements. It was found that an ESS power rating of 60% of the PV string nominal power is adequate to smooth almost all detected PV power ramps even with strict RR limits. With a typical DC/AC power ratio of 1.5, about 1.0 h of energy storage capacity is needed at the nominal power of the PV string to smooth all PV power ramps. The results illustrate that the set RR limit and the inverter sizing are important factors for sizing the ESS for PV RR control. Moreover, the results indicate that the needed ESS power capacity can be considerably reduced by smoothing the fastest upward power ramps by power curtailment.

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  • 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.
    • Handle: RePEc:eee:renene:v:196:y:2022:i:c:p:1366-1375
    DOI: 10.1016/j.renene.2022.07.069
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    1. Bridier, Laurent & Hernández-Torres, David & David, Mathieu & Lauret, Phillipe, 2016. "A heuristic approach for optimal sizing of ESS coupled with intermittent renewable sources systems," Renewable Energy, Elsevier, vol. 91(C), pages 155-165.
    2. Lappalainen, Kari & Wang, Guang C. & Kleissl, Jan, 2020. "Estimation of the largest expected photovoltaic power ramp rates," Applied Energy, Elsevier, vol. 278(C).
    3. Cirés, E. & Marcos, J. & de la Parra, I. & García, M. & Marroyo, L., 2019. "The potential of forecasting in reducing the LCOE in PV plants under ramp-rate restrictions," Energy, Elsevier, vol. 188(C).
    4. Wang, H.X. & Muñoz-García, M.A. & Moreda, G.P. & Alonso-García, M.C., 2018. "Optimum inverter sizing of grid-connected photovoltaic systems based on energetic and economic considerations," Renewable Energy, Elsevier, vol. 118(C), pages 709-717.
    5. Lappalainen, Kari & Valkealahti, Seppo, 2021. "Experimental study of the maximum power point characteristics of partially shaded photovoltaic strings," Applied Energy, Elsevier, vol. 301(C).
    6. 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.
    7. Shivashankar, S. & Mekhilef, Saad & Mokhlis, Hazlie & Karimi, M., 2016. "Mitigating methods of power fluctuation of photovoltaic (PV) sources – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1170-1184.
    8. Cabrera-Tobar, Ana & Bullich-Massagué, Eduard & Aragüés-Peñalba, Mònica & Gomis-Bellmunt, Oriol, 2016. "Review of advanced grid requirements for the integration of large scale photovoltaic power plants in the transmission system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 971-987.
    9. Lappalainen, Kari & Valkealahti, Seppo, 2017. "Output power variation of different PV array configurations during irradiance transitions caused by moving clouds," Applied Energy, Elsevier, vol. 190(C), pages 902-910.
    10. Chen, Xiaoyang & Du, Yang & Lim, Enggee & Wen, Huiqing & Yan, Ke & Kirtley, James, 2020. "Power ramp-rates of utility-scale PV systems under passing clouds: Module-level emulation with cloud shadow modeling," Applied Energy, Elsevier, vol. 268(C).
    11. Rampinelli, G.A. & Krenzinger, A. & Chenlo Romero, F., 2014. "Mathematical models for efficiency of inverters used in grid connected photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 578-587.
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    1. Fernando M. Camilo & Paulo Santos, 2023. "Technical-Economic Evaluation of Residential Wind and Photovoltaic Systems with Self-Consumption and Storage Systems in Portugal," Energies, MDPI, vol. 16(4), pages 1-21, February.
    2. Micke Talvi & Tomi Roinila & Kari Lappalainen, 2023. "Effects of Ramp Rate Limit on Sizing of Energy Storage Systems for PV, Wind and PV–Wind Power Plants," Energies, MDPI, vol. 16(11), pages 1-18, May.

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