IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v255y2019ics0306261919314941.html
   My bibliography  Save this article

Spatio-temporal PV forecasting sensitivity to modules’ tilt and orientation

Author

Listed:
  • Amaro e Silva, R.
  • Brito, M.C.

Abstract

Using deployed PV generation as inputs for spatio-temporal forecasting approaches has the potential for fast and scalable very short-term PV forecasting in the urban environment but one has to consider the effect of their tilt and orientation on the forecasting accuracy. To address this issue, tilted irradiance data sets were simulated using state of the art solutions on a horizontal irradiance data set from a pyranometer network deployed in Oahu, Hawaii, and used as inputs to train a 10-s ahead linear ARX model. Results showed that the mismatch in tilt/orientation degrades the forecast skill, justified by the difference in the diffuse fraction of each surface and, thus, how each reacts to changes in cloud cover. From 4000 simulated sets, it was shown that using information from more sites led to better forecasts and made the model performance less sensitive to the PV modules’ tilt and orientation. Forecast skill showed to be quite sensitive to the tilt and orientation ensemble when the inputs consisted of only rooftop or façade systems (between 18.1–29.6% and 8.2–19.4%, respectively). Forecasting a rooftop system with vertically tilted neighbors lead to considerably lower skill values (9.8–16.2%) and benefitted when all shared the same orientation. On the other hand, forecasting a vertically tilted system with rooftop neighbors had a lower impact (9.2–14.7%) and benefitted from diversely oriented neighbors.

Suggested Citation

  • Amaro e Silva, R. & Brito, M.C., 2019. "Spatio-temporal PV forecasting sensitivity to modules’ tilt and orientation," Applied Energy, Elsevier, vol. 255(C).
  • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919314941
    DOI: 10.1016/j.apenergy.2019.113807
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919314941
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.113807?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.

    Citations

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


    Cited by:

    1. Ahn, Hyeunguk, 2024. "A framework for developing data-driven correction factors for solar PV systems," Energy, Elsevier, vol. 290(C).
    2. Llinet Benavides Cesar & Rodrigo Amaro e Silva & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira, 2022. "Review on Spatio-Temporal Solar Forecasting Methods Driven by In Situ Measurements or Their Combination with Satellite and Numerical Weather Prediction (NWP) Estimates," Energies, MDPI, vol. 15(12), pages 1-23, June.
    3. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
    4. Rodrigo Amaro e Silva & Llinet Benavides Cesar & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira, 2024. "Impact of Stationarizing Solar Inputs on Very-Short-Term Spatio-Temporal Global Horizontal Irradiance (GHI) Forecasting," Energies, MDPI, vol. 17(14), pages 1-19, July.
    5. Rodríguez-Benítez, Francisco J. & López-Cuesta, Miguel & Arbizu-Barrena, Clara & Fernández-León, María M. & Pamos-Ureña, Miguel Á. & Tovar-Pescador, Joaquín & Santos-Alamillos, Francisco J. & Pozo-Váz, 2021. "Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery," Applied Energy, Elsevier, vol. 292(C).
    6. Sabadus, Andreea & Blaga, Robert & Hategan, Sergiu-Mihai & Calinoiu, Delia & Paulescu, Eugenia & Mares, Oana & Boata, Remus & Stefu, Nicoleta & Paulescu, Marius & Badescu, Viorel, 2024. "A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches," Renewable Energy, Elsevier, vol. 226(C).
    7. Lukač, Niko & Špelič, Denis & Štumberger, Gorazd & Žalik, Borut, 2020. "Optimisation for large-scale photovoltaic arrays’ placement based on Light Detection And Ranging data," Applied Energy, Elsevier, vol. 263(C).
    8. Llinet Benavides Cesar & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira & Ramon Alcarria, 2023. "CyL-GHI: Global Horizontal Irradiance Dataset Containing 18 Years of Refined Data at 30-Min Granularity from 37 Stations Located in Castile and León (Spain)," Data, MDPI, vol. 8(4), pages 1-21, March.
    9. Mayer, Martin János & Gróf, Gyula, 2021. "Extensive comparison of physical models for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 283(C).
    10. Chen, Xiaoyang & Du, Yang & Lim, Enggee & Fang, Lurui & Yan, Ke, 2022. "Towards the applicability of solar nowcasting: A practice on predictive PV power ramp-rate control," Renewable Energy, Elsevier, vol. 195(C), pages 147-166.

    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:appene:v:255:y:2019:i:c:s0306261919314941. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.