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Performance Assessment of Large Photovoltaic (PV) Plants Using an Integrated State-Space Average Modeling Approach

Author

Listed:
  • Giovanni Nobile

    (Department of Electrical, Electronics Engineering and Computer Science (DIEEI), University of Catania, 95100 Catania, Italy)

  • Ester Vasta

    (Department of Electrical, Electronics Engineering and Computer Science (DIEEI), University of Catania, 95100 Catania, Italy)

  • Mario Cacciato

    (Department of Electrical, Electronics Engineering and Computer Science (DIEEI), University of Catania, 95100 Catania, Italy)

  • Giuseppe Scarcella

    (Department of Electrical, Electronics Engineering and Computer Science (DIEEI), University of Catania, 95100 Catania, Italy)

  • Giacomo Scelba

    (Department of Electrical, Electronics Engineering and Computer Science (DIEEI), University of Catania, 95100 Catania, Italy)

  • Agnese Giuseppa Federica Di Stefano

    (ENEL Green Power SpA, 95100 Catania, Italy)

  • Giuseppe Leotta

    (ENEL Green Power SpA, 95100 Catania, Italy)

  • Paola Maria Pugliatti

    (ENEL Green Power SpA, 95100 Catania, Italy)

  • Fabrizio Bizzarri

    (ENEL Green Power SpA, 95100 Catania, Italy)

Abstract

Distributed power converters represent a technical solution to improve the performance of large or utility-scale photovoltaic (PV) plants. Unfortunately, evaluation of the yield obtained in large PV fields by using distributed converters is a difficult task because of recurring partial unavailability, inaccuracy of power analyzers, operating constraints imposed by the Power Plant Controller and so on. To overcome such issues in real operating scenarios, a new modeling strategy has been introduced and validated in terms of computational complexity and accuracy. This approach is based on the state-space averaging technique which is applied to large PV plants with multiple conversion stages by performing some elaborations in order to get a final integrated model. The new modeling strategy has been tested in MatLab Simulink environment using data coming from a 300 MW PV plant located in Brazil representing the case study of this work. In this plant, one subfield is equipped with central inverters while another is with string inverters. The proposed model, whose accuracy is in the range from 2.2 to 2.7% with respect to the measured energy, effectively supports data analysis leading to a consistent performance assessment for the distributed conversion system. Final results highlight that string inverters ensure a gain of about 2% in terms of produced energy.

Suggested Citation

  • Giovanni Nobile & Ester Vasta & Mario Cacciato & Giuseppe Scarcella & Giacomo Scelba & Agnese Giuseppa Federica Di Stefano & Giuseppe Leotta & Paola Maria Pugliatti & Fabrizio Bizzarri, 2020. "Performance Assessment of Large Photovoltaic (PV) Plants Using an Integrated State-Space Average Modeling Approach," Energies, MDPI, vol. 13(18), pages 1-27, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4777-:d:413005
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    References listed on IDEAS

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    1. Li, Y. & Chen, X.M. & Zhao, B.Y. & Zhao, Z.G. & Wang, R.Z., 2017. "Development of a PV performance model for power output simulation at minutely resolution," Renewable Energy, Elsevier, vol. 111(C), pages 732-739.
    2. Obi, Manasseh & Bass, Robert, 2016. "Trends and challenges of grid-connected photovoltaic systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1082-1094.
    3. Guerrero-Perez, J. & De Jodar, E. & Gómez-Lázaro, E. & Molina-Garcia, A., 2014. "Behavioral modeling of grid-connected photovoltaic inverters: Development and assessment," Renewable Energy, Elsevier, vol. 68(C), pages 686-696.
    4. Zeb, Kamran & Uddin, Waqar & Khan, Muhammad Adil & Ali, Zunaib & Ali, Muhammad Umair & Christofides, Nicholas & Kim, H.J., 2018. "A comprehensive review on inverter topologies and control strategies for grid connected photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1120-1141.
    5. Trujillo, C.L. & Santamaría, F. & Gaona, E.E., 2016. "Modeling and testing of two-stage grid-connected photovoltaic micro-inverters," Renewable Energy, Elsevier, vol. 99(C), pages 533-542.
    6. Ali, Zunaib & Christofides, Nicholas & Hadjidemetriou, Lenos & Kyriakides, Elias & Yang, Yongheng & Blaabjerg, Frede, 2018. "Three-phase phase-locked loop synchronization algorithms for grid-connected renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 434-452.
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