IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4777-d413005.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4777/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/18/4777/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vargas Gil, Gloria Milena & Bittencourt Aguiar Cunha, Rafael & Giuseppe Di Santo, Silvio & Machado Monaro, Renato & Fragoso Costa, Fabiano & Sguarezi Filho, Alfeu J., 2020. "Photovoltaic energy in South America: Current state and grid regulation for large-scale and distributed photovoltaic systems," Renewable Energy, Elsevier, vol. 162(C), pages 1307-1320.
    2. Mohamed Salem & Anna Richelli & Khalid Yahya & Muhammad Najwan Hamidi & Tze-Zhang Ang & Ibrahim Alhamrouni, 2022. "A Comprehensive Review on Multilevel Inverters for Grid-Tied System Applications," Energies, MDPI, vol. 15(17), pages 1-40, August.
    3. Walmsley, Timothy Gordon & Philipp, Matthias & Picón-Núñez, Martín & Meschede, Henning & Taylor, Matthew Thomas & Schlosser, Florian & Atkins, Martin John, 2023. "Hybrid renewable energy utility systems for industrial sites: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    4. 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.
    5. Jihed Hmad & Azeddine Houari & Allal El Moubarek Bouzid & Abdelhakim Saim & Hafedh Trabelsi, 2023. "A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids," Energies, MDPI, vol. 16(13), pages 1-41, June.
    6. Protopapadaki, Christina & Saelens, Dirk, 2017. "Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties," Applied Energy, Elsevier, vol. 192(C), pages 268-281.
    7. Mostafa Ahmed & Mohamed Abdelrahem & Ibrahim Harbi & Ralph Kennel, 2020. "An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems," Energies, MDPI, vol. 13(24), pages 1-25, December.
    8. Amir, Asim & Amir, Aamir & Che, Hang Seng & Elkhateb, Ahmad & Rahim, Nasrudin Abd, 2019. "Comparative analysis of high voltage gain DC-DC converter topologies for photovoltaic systems," Renewable Energy, Elsevier, vol. 136(C), pages 1147-1163.
    9. Ding, Kun & Chen, Xiang & Weng, Shuai & Liu, Yongjie & Zhang, Jingwei & Li, Yuanliang & Yang, Zenan, 2023. "Health status evaluation of photovoltaic array based on deep belief network and Hausdorff distance," Energy, Elsevier, vol. 262(PB).
    10. Guillermo Almonacid-Olleros & Gabino Almonacid & David Gil & Javier Medina-Quero, 2022. "Evaluation of Transfer Learning and Fine-Tuning to Nowcast Energy Generation of Photovoltaic Systems in Different Climates," Sustainability, MDPI, vol. 14(5), pages 1-15, March.
    11. Dhimish, Mahmoud & Holmes, Violeta & Dales, Mark, 2017. "Parallel fault detection algorithm for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 113(C), pages 94-111.
    12. Silverman, Rochelle E. & Flores, Robert J. & Brouwer, Jack, 2020. "Energy and economic assessment of distributed renewable gas and electricity generation in a small disadvantaged urban community," Applied Energy, Elsevier, vol. 280(C).
    13. Huda, A.S.N. & Živanović, R., 2017. "Large-scale integration of distributed generation into distribution networks: Study objectives, review of models and computational tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 974-988.
    14. Kurz, Konstantin & Bock, Carolin & Knodt, Michèle & Stöckl, Anna, 2022. "A Friend in Need Is a Friend Indeed? Analysis of the Willingness to Share Self-Produced Electricity During a Long-lasting Power Outage," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136773, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    15. Dhimish, Mahmoud & Holmes, Violeta & Mehrdadi, Bruce & Dales, Mark & Mather, Peter, 2017. "Photovoltaic fault detection algorithm based on theoretical curves modelling and fuzzy classification system," Energy, Elsevier, vol. 140(P1), pages 276-290.
    16. Alemu Moges Belay & Sanket Puranik & Ramon Gallart-Fernández & Heidi Tuiskula & Joaquim Melendez & Ilias Lamprinos & Francisco Díaz-González & Miha Smolnikar, 2021. "Developing Novel Technologies and Services for Intelligent Low Voltage Electricity Grids: Cost–Benefit Analysis and Policy Implications," Energies, MDPI, vol. 15(1), pages 1-25, December.
    17. Muttqi, Kashem M. & Aghaei, Jamshid & Askarpour, Mohammad & Ganapathy, Velappa, 2017. "Minimizing the steady-state impediments to solar photovoltaics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1329-1345.
    18. Shahnazari, Mahdi & Bahri, Parisa A. & Parlevliet, David & Minakshi, Manickam & Moheimani, Navid R., 2017. "Sustainable conversion of light to algal biomass and electricity: A net energy return analysis," Energy, Elsevier, vol. 131(C), pages 218-229.
    19. Larbi Chrifi-Alaoui & Saïd Drid & Mohammed Ouriagli & Driss Mehdi, 2023. "Overview of Photovoltaic and Wind Electrical Power Hybrid Systems," Energies, MDPI, vol. 16(12), pages 1-35, June.
    20. Vale, A.M. & Felix, D.G. & Fortes, M.Z. & Borba, B.S.M.C. & Dias, B.H. & Santelli, B.S., 2017. "Analysis of the economic viability of a photovoltaic generation project applied to the Brazilian housing program “Minha Casa Minha Vida”," Energy Policy, Elsevier, vol. 108(C), pages 292-298.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4777-:d:413005. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.