IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v154y2020icp175-186.html
   My bibliography  Save this article

The Dutch PV portal 2.0: An online photovoltaic performance modeling environment for the Netherlands

Author

Listed:
  • Schepel, Veikko
  • Tozzi, Arianna
  • Klement, Marianne
  • Ziar, Hesan
  • Isabella, Olindo
  • Zeman, Miro

Abstract

This paper describes the core model that lies behind an online modeling environment for photovoltaic (PV) energy generation in the Netherlands, called the Dutch PV Portal 2.0 (PVP 2.0). PVP 2.0 realizes three functionalities: (i) a real-time system efficiency breakdown figure, (ii) an estimate of national solar electricity production, and (iii) an economic analysis for small-scale to large scale PV systems. The unique and novel aspects of this website are the dynamically updated climate database, the rainfall-dependent soiling loss calculation, and the orientation-dependent inverter sizing factor. This paper also justifies the PVP 2.0 capabilities in large scale studies. First, the PVP 2.0 modeling approach was validated by yield comparison with 26 real PV systems distributed over the Netherlands. The validation resulted in −11% to +5.5% deviation from measured data. Then, a back-end sensitivity study found that a rain-free summer in the Netherlands results in an AC energy loss of 3.4% in that period, while a change in wind speed or ambient temperature could lead to losses around 2–4.5 GWh/year (0.58%–1.16%) on province scale. The core of the approach presented in this paper can be used to develop similar websites for other countries of interest with adapted add-ons depending on the target climate condition. Such study tools could eventually provide more quantitative insights about the impact of climate change (by applying probable scenarios) on the renewable energy production of the World.

Suggested Citation

  • Schepel, Veikko & Tozzi, Arianna & Klement, Marianne & Ziar, Hesan & Isabella, Olindo & Zeman, Miro, 2020. "The Dutch PV portal 2.0: An online photovoltaic performance modeling environment for the Netherlands," Renewable Energy, Elsevier, vol. 154(C), pages 175-186.
    • Handle: RePEc:eee:renene:v:154:y:2020:i:c:p:175-186
    DOI: 10.1016/j.renene.2019.11.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119317148
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2019.11.033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Diane Palmer & Ian Cole & Tom Betts & Ralph Gottschalg, 2017. "Interpolating and Estimating Horizontal Diffuse Solar Irradiation to Provide UK-Wide Coverage: Selection of the Best Performing Models," Energies, MDPI, vol. 10(2), pages 1-23, February.
    2. Bendib, Boualem & Belmili, Hocine & Krim, Fateh, 2015. "A survey of the most used MPPT methods: Conventional and advanced algorithms applied for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 637-648.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huxley, O.T. & Taylor, J. & Everard, A. & Briggs, J. & Tilley, K. & Harwood, J. & Buckley, A., 2022. "The uncertainties involved in measuring national solar photovoltaic electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).

    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. Abbes Kihal & Fateh Krim & Billel Talbi & Abdelbaset Laib & Abdeslem Sahli, 2018. "A Robust Control of Two-Stage Grid-Tied PV Systems Employing Integral Sliding Mode Theory," Energies, MDPI, vol. 11(10), pages 1-21, October.
    2. Yi Jin & Wenhui Hou & Guiqiang Li & Xiao Chen, 2017. "A Glowworm Swarm Optimization-Based Maximum Power Point Tracking for Photovoltaic/Thermal Systems under Non-Uniform Solar Irradiation and Temperature Distribution," Energies, MDPI, vol. 10(4), pages 1-13, April.
    3. Md Ohirul Qays & Yonis Buswig & Md Liton Hossain & Ahmed Abu-Siada, 2020. "Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System," Energies, MDPI, vol. 13(13), pages 1-16, July.
    4. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    5. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    6. Jong-Chan Kim & Jun-Ho Huh & Jae-Sub Ko, 2020. "Optimization Design and Test Bed of Fuzzy Control Rule Base for PV System MPPT in Micro Grid," Sustainability, MDPI, vol. 12(9), pages 1-25, May.
    7. Sarmiento, Nilsa & Belmonte, Silvina & Dellicompagni, Pablo & Franco, Judith & Escalante, Karina & Sarmiento, Joaquín, 2019. "A solar irradiation GIS as decision support tool for the Province of Salta, Argentina," Renewable Energy, Elsevier, vol. 132(C), pages 68-80.
    8. Yilmaz, Unal & Kircay, Ali & Borekci, Selim, 2018. "PV system fuzzy logic MPPT method and PI control as a charge controller," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 994-1001.
    9. Sheik Mohammed, S. & Devaraj, D. & Imthias Ahamed, T.P., 2016. "A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system," Energy, Elsevier, vol. 112(C), pages 1096-1106.
    10. Victor Andrean & Pei Cheng Chang & Kuo Lung Lian, 2018. "A Review and New Problems Discovery of Four Simple Decentralized Maximum Power Point Tracking Algorithms—Perturb and Observe, Incremental Conductance, Golden Section Search, and Newton’s Quadratic Int," Energies, MDPI, vol. 11(11), pages 1-25, November.
    11. Ahmad M. A. Malkawi & Abdallah Odat & Ahmad Bashaireh, 2022. "A Novel PV Maximum Power Point Tracking Based on Solar Irradiance and Circuit Parameters Estimation," Sustainability, MDPI, vol. 14(13), pages 1-14, June.
    12. Bong-Gi Choi & Byeong-Chan Oh & Sungyun Choi & Sung-Yul Kim, 2020. "Selecting Locations of Electric Vehicle Charging Stations Based on the Traffic Load Eliminating Method," Energies, MDPI, vol. 13(7), pages 1-20, April.
    13. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2017. "Comprehensive overview of grid interfaced solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 316-332.
    14. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    15. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    16. Nguyen Van Tan & Nguyen Binh Nam & Nguyen Huu Hieu & Le Kim Hung & Minh Quan Duong & Le Hong Lam, 2020. "A Proposal for an MPPT Algorithm Based on the Fluctuations of the PV Output Power, Output Voltage, and Control Duty Cycle for Improving the Performance of PV Systems in Microgrid," Energies, MDPI, vol. 13(17), pages 1-21, August.
    17. Baldwin Cortés & Roberto Tapia & Juan J. Flores, 2021. "System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles," Energies, MDPI, vol. 14(16), pages 1-18, August.
    18. Poompavai, T. & Kowsalya, M., 2019. "Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 108-122.
    19. Daniela Malcangio & Claudio Donvito & Nicola Ungaro, 2018. "Statistical Analysis of Bathing Water Quality in Puglia Region (Italy)," IJERPH, MDPI, vol. 15(5), pages 1-15, May.
    20. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).

    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:eee:renene:v:154:y:2020:i:c:p:175-186. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.