IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v86y2016icp760-769.html
   My bibliography  Save this article

Photovoltaic (PV) performance modelling in the absence of onsite measured plane of array irradiance (POA) and module temperature

Author

Listed:
  • Copper, J.K.
  • Sproul, A.B.
  • Jarnason, S.

Abstract

In this study, the outputs from a simple PV performance model were compared to measurements of AC power for three PV systems located across Sydney, Australia. The study aimed to investigate the level of uncertainty and bias of the model when onsite measurements of plane of array (POA) irradiance and module temperature were not available. The results demonstrated that the simple PV performance model estimated the AC performance with a low level of model bias (NBME = ±3.2%) and uncertainty (NRMSE < 6%) when onsite measurements of POA irradiance and module temperatures were available. For POA irradiance, the results indicated that modelling uncertainty increased significantly (NRMSE < 13%) when alternative methods to estimate POA irradiance were utilised. For module temperature, the results indicated that the choice of model coefficients had a significant impact on the performance of the module temperature models. In particular, for the three parallel roof mounted PV systems studied, the results suggested that the open rack/free standing or well ventilated module temperature coefficients should be used within the module temperature models investigated. This selection of coefficients was not directly evident given the PV systems investigated were parallel roof mounted PV systems, not free standing rack mounted arrays.

Suggested Citation

  • Copper, J.K. & Sproul, A.B. & Jarnason, S., 2016. "Photovoltaic (PV) performance modelling in the absence of onsite measured plane of array irradiance (POA) and module temperature," Renewable Energy, Elsevier, vol. 86(C), pages 760-769.
    • Handle: RePEc:eee:renene:v:86:y:2016:i:c:p:760-769
    DOI: 10.1016/j.renene.2015.09.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148115302846
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2015.09.005?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. Skoplaki, E. & Palyvos, J.A., 2009. "Operating temperature of photovoltaic modules: A survey of pertinent correlations," Renewable Energy, Elsevier, vol. 34(1), pages 23-29.
    2. Ayompe, L.M. & Duffy, A. & McCormack, S.J. & Conlon, M., 2010. "Validated real-time energy models for small-scale grid-connected PV-systems," Energy, Elsevier, vol. 35(10), pages 4086-4091.
    3. Torres, J.L. & De Blas, M. & García, A. & de Francisco, A., 2010. "Comparative study of various models in estimating hourly diffuse solar irradiance," Renewable Energy, Elsevier, vol. 35(6), pages 1325-1332.
    4. David, Mathieu & Lauret, Philippe & Boland, John, 2013. "Evaluating tilted plane models for solar radiation using comprehensive testing procedures, at a southern hemisphere location," Renewable Energy, Elsevier, vol. 51(C), pages 124-131.
    5. Noorian, Ali Mohammad & Moradi, Isaac & Kamali, Gholam Ali, 2008. "Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces," Renewable Energy, Elsevier, vol. 33(6), pages 1406-1412.
    6. Copper, J.K. & Sproul, A.B., 2012. "Comparative study of mathematical models in estimating solar irradiance for Australia," Renewable Energy, Elsevier, vol. 43(C), pages 130-139.
    7. Ridley, Barbara & Boland, John & Lauret, Philippe, 2010. "Modelling of diffuse solar fraction with multiple predictors," Renewable Energy, Elsevier, vol. 35(2), pages 478-483.
    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. Adel Alblawi & M. H. Elkholy & M. Talaat, 2019. "ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance," Sustainability, MDPI, vol. 11(23), pages 1-24, November.
    2. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    3. Alami Merrouni, Ahmed & Elwali Elalaoui, Fakhreddine & Mezrhab, Ahmed & Mezrhab, Abdelhamid & Ghennioui, Abdellatif, 2018. "Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco," Renewable Energy, Elsevier, vol. 119(C), pages 863-873.
    4. Haghdadi, Navid & Copper, Jessie & Bruce, Anna & MacGill, Iain, 2017. "A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data," Renewable Energy, Elsevier, vol. 108(C), pages 390-400.
    5. Nacer, T. & Hamidat, A. & Nadjemi, O. & Bey, M., 2016. "Feasibility study of grid connected photovoltaic system in family farms for electricity generation in rural areas," Renewable Energy, Elsevier, vol. 96(PA), pages 305-318.
    6. Moslehi, Salim & Reddy, T. Agami & Katipamula, Srinivas, 2018. "Evaluation of data-driven models for predicting solar photovoltaics power output," Energy, Elsevier, vol. 142(C), pages 1057-1065.

    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. Chinchilla, Monica & Santos-Martín, David & Carpintero-Rentería, Miguel & Lemon, Scott, 2021. "Worldwide annual optimum tilt angle model for solar collectors and photovoltaic systems in the absence of site meteorological data," Applied Energy, Elsevier, vol. 281(C).
    2. Lin, Chun-Tin & Chang, Keh-Chin & Chung, Kung-Ming, 2023. "Re-modeling the solar diffuse fraction in Taiwan on basis of a typical-meteorological-year data," Renewable Energy, Elsevier, vol. 204(C), pages 823-835.
    3. Every, Jeremy P. & Li, Li & Dorrell, David G., 2020. "Köppen-Geiger climate classification adjustment of the BRL diffuse irradiation model for Australian locations," Renewable Energy, Elsevier, vol. 147(P1), pages 2453-2469.
    4. Haghdadi, Navid & Copper, Jessie & Bruce, Anna & MacGill, Iain, 2017. "A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data," Renewable Energy, Elsevier, vol. 108(C), pages 390-400.
    5. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    6. Copper, J.K. & Sproul, A.B., 2013. "Comparative building simulation study utilising measured and estimated solar irradiance for Australian locations," Renewable Energy, Elsevier, vol. 53(C), pages 86-93.
    7. Copper, J.K. & Sproul, A.B., 2012. "Comparative study of mathematical models in estimating solar irradiance for Australia," Renewable Energy, Elsevier, vol. 43(C), pages 130-139.
    8. Watts, David & Valdés, Marcelo F. & Jara, Danilo & Watson, Andrea, 2015. "Potential residential PV development in Chile: The effect of Net Metering and Net Billing schemes for grid-connected PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1037-1051.
    9. Kuo, Chia-Wei & Chang, Wen-Chey & Chang, Keh-Chin, 2014. "Modeling the hourly solar diffuse fraction in Taiwan," Renewable Energy, Elsevier, vol. 66(C), pages 56-61.
    10. Pérez-Burgos, Ana & Román, Roberto & Bilbao, Julia & de Miguel, Argimiro & Oteiza, Pilar, 2015. "Reconstruction of long-term direct solar irradiance data series using a model based on the Cloud Modification Factor," Renewable Energy, Elsevier, vol. 77(C), pages 115-124.
    11. Marques Filho, Edson P. & Oliveira, Amauri P. & Vita, Willian A. & Mesquita, Francisco L.L. & Codato, Georgia & Escobedo, João F. & Cassol, Mariana & França, José Ricardo A., 2016. "Global, diffuse and direct solar radiation at the surface in the city of Rio de Janeiro: Observational characterization and empirical modeling," Renewable Energy, Elsevier, vol. 91(C), pages 64-74.
    12. Moretón, R. & Lorenzo, E. & Pinto, A. & Muñoz, J. & Narvarte, L., 2017. "From broadband horizontal to effective in-plane irradiation: A review of modelling and derived uncertainty for PV yield prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 886-903.
    13. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    14. Savvakis, Nikolaos & Tsoutsos, Theocharis, 2015. "Performance assessment of a thin film photovoltaic system under actual Mediterranean climate conditions in the island of Crete," Energy, Elsevier, vol. 90(P2), pages 1435-1455.
    15. Raptis, P.I. & Kazadzis, S. & Psiloglou, B. & Kouremeti, N. & Kosmopoulos, P. & Kazantzidis, A., 2017. "Measurements and model simulations of solar radiation at tilted planes, towards the maximization of energy capture," Energy, Elsevier, vol. 130(C), pages 570-580.
    16. Qin, Jun & Jiang, Hou & Lu, Ning & Yao, Ling & Zhou, Chenghu, 2022. "Enhancing solar PV output forecast by integrating ground and satellite observations with deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. Hafez, A.Z. & Soliman, A. & El-Metwally, K.A. & Ismail, I.M., 2017. "Tilt and azimuth angles in solar energy applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 147-168.
    18. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C. & Chan, Wilco W.H., 2016. "Prediction of diffuse solar irradiance using machine learning and multivariable regression," Applied Energy, Elsevier, vol. 181(C), pages 367-374.
    19. Liu, Yujun & Yao, Ling & Jiang, Hou & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2022. "Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data," Renewable Energy, Elsevier, vol. 189(C), pages 1249-1258.
    20. Weatherford, Vergil C. & (John) Zhai, Zhiqiang, 2015. "Affordable solar-assisted biogas digesters for cold climates: Experiment, model, verification and analysis," Applied Energy, Elsevier, vol. 146(C), pages 209-216.

    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:86:y:2016:i:c:p:760-769. 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.