IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v108y2013icp429-438.html
   My bibliography  Save this article

Dynamical optimal positioning of a photovoltaic panel in all weather conditions

Author

Listed:
  • Gulin, Marko
  • Vašak, Mario
  • Perić, Nedjeljko

Abstract

In this paper we develop and verify a model predictive control algorithm for photovoltaic panel orientation with the aim to maximize the photovoltaic system netto power production. Thereby we take into account local weather forecast with its uncertainty, thermal behavior of the panel, and the positioning system energy consumption with its technical constraints. The model predictive control synthesis procedure comprises two basic steps: (i) identification of solar irradiance model and development of the photovoltaic system model and (ii) development of predictive control algorithm for the photovoltaic panel active surface orientation, based on the obtained models. Performance of the developed algorithm is verified through year-scale simulations based on a large number of solar irradiance and other weather data patterns. It turns out that the proposed algorithm is fully competitive with the mostly used sun tracking or maximum irradiance seeking controls, and that it outperforms them. The other advantages of the proposed algorithm are: (i) the positioning system is controlled smoothly and (ii) prediction of energy yield one day ahead is available together with its uncertainty for easier photovoltaic system integration into the electricity distribution network.

Suggested Citation

  • Gulin, Marko & Vašak, Mario & Perić, Nedjeljko, 2013. "Dynamical optimal positioning of a photovoltaic panel in all weather conditions," Applied Energy, Elsevier, vol. 108(C), pages 429-438.
    • Handle: RePEc:eee:appene:v:108:y:2013:i:c:p:429-438
    DOI: 10.1016/j.apenergy.2013.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191300192X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.03.006?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. Chaabene, Maher & Ammar, Mohsen Ben & Elhajjaji, Ahmed, 2007. "Fuzzy approach for optimal energy-management of a domestic photovoltaic panel," Applied Energy, Elsevier, vol. 84(10), pages 992-1001, October.
    2. Janjai, S. & Sricharoen, K. & Pattarapanitchai, S., 2011. "Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics," Applied Energy, Elsevier, vol. 88(12), pages 4749-4755.
    3. Su, Yan & Chan, Lai-Cheong & Shu, Lianjie & Tsui, Kwok-Leung, 2012. "Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems," Applied Energy, Elsevier, vol. 93(C), pages 319-326.
    4. Wong, L. T. & Chow, W. K., 2001. "Solar radiation model," Applied Energy, Elsevier, vol. 69(3), pages 191-224, July.
    5. Maatallah, Taher & El Alimi, Souheil & Nassrallah, Sassi Ben, 2011. "Performance modeling and investigation of fixed, single and dual-axis tracking photovoltaic panel in Monastir city, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 4053-4066.
    6. Pandey, Chanchal Kumar & Katiyar, A.K., 2009. "A note on diffuse solar radiation on a tilted surface," Energy, Elsevier, vol. 34(11), pages 1764-1769.
    7. Ranganathan, Raghuram & Mikhael, Wasfy & Kutkut, Nasser & Batarseh, Issa, 2011. "Adaptive sun tracking algorithm for incident energy maximization and efficiency improvement of PV panels," Renewable Energy, Elsevier, vol. 36(10), pages 2623-2626.
    8. Dorvlo, Atsu S. S. & Jervase, Joseph A. & Al-Lawati, Ali, 2002. "Solar radiation estimation using artificial neural networks," Applied Energy, Elsevier, vol. 71(4), pages 307-319, April.
    9. Ammar, Mohsen Ben & Chaabene, Maher & Elhajjaji, Ahmed, 2010. "Daily energy planning of a household photovoltaic panel," Applied Energy, Elsevier, vol. 87(7), pages 2340-2351, July.
    10. Chang, Tian Pau, 2009. "Output energy of a photovoltaic module mounted on a single-axis tracking system," Applied Energy, Elsevier, vol. 86(10), pages 2071-2078, October.
    11. Mousazadeh, Hossein & Keyhani, Alireza & Javadi, Arzhang & Mobli, Hossein & Abrinia, Karen & Sharifi, Ahmad, 2009. "A review of principle and sun-tracking methods for maximizing solar systems output," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1800-1818, October.
    12. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    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. Nsengiyumva, Walter & Chen, Shi Guo & Hu, Lihua & Chen, Xueyong, 2018. "Recent advancements and challenges in Solar Tracking Systems (STS): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 250-279.
    2. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    3. Gulin, Marko & Pavlović, Tomislav & Vašak, Mario, 2016. "Photovoltaic panel and array static models for power production prediction: Integration of manufacturers’ and on-line data," Renewable Energy, Elsevier, vol. 97(C), pages 399-413.
    4. Li, Qian & Wu, Zhou & Xia, Xiaohua, 2018. "Estimate and characterize PV power at demand-side hybrid system," Applied Energy, Elsevier, vol. 218(C), pages 66-77.
    5. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Photovoltaic power stations in Germany and the United States: A comparative study by data envelopment analysis," Energy Economics, Elsevier, vol. 42(C), pages 271-288.
    6. 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.
    7. Sato, Daisuke & Yamagata, Yuki & Hirata, Kenji & Yamada, Noboru, 2020. "Mathematical power-generation model of a four-terminal partial concentrator photovoltaic module for optimal sun-tracking strategy," Energy, Elsevier, vol. 213(C).
    8. Yilmaz, Saban & Riza Ozcalik, Hasan & Dogmus, Osman & Dincer, Furkan & Akgol, Oguzhan & Karaaslan, Muharrem, 2015. "Design of two axes sun tracking controller with analytically solar radiation calculations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 997-1005.
    9. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.

    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. Okoye, Chiemeka Onyeka & Bahrami, Arian & Atikol, Ugur, 2018. "Evaluating the solar resource potential on different tracking surfaces in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1569-1581.
    2. 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.
    3. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    4. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
    5. Bahrami, Arian & Okoye, Chiemeka Onyeka & Atikol, Ugur, 2016. "The effect of latitude on the performance of different solar trackers in Europe and Africa," Applied Energy, Elsevier, vol. 177(C), pages 896-906.
    6. Purohit, Ishan & Purohit, Pallav, 2015. "Inter-comparability of solar radiation databases in Indian context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 735-747.
    7. Bahrami, Arian & Okoye, Chiemeka Onyeka & Atikol, Ugur, 2017. "Technical and economic assessment of fixed, single and dual-axis tracking PV panels in low latitude countries," Renewable Energy, Elsevier, vol. 113(C), pages 563-579.
    8. Kocifaj, Miroslav & Kómar, Ladislav, 2016. "Modeling diffuse irradiance under arbitrary and homogeneous skies: Comparison and validation," Applied Energy, Elsevier, vol. 166(C), pages 117-127.
    9. Shabani, Masoume & Mahmoudimehr, Javad, 2018. "Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system," Applied Energy, Elsevier, vol. 212(C), pages 84-108.
    10. Singh, Rajesh & Kumar, Suresh & Gehlot, Anita & Pachauri, Rupendra, 2018. "An imperative role of sun trackers in photovoltaic technology: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3263-3278.
    11. Nsengiyumva, Walter & Chen, Shi Guo & Hu, Lihua & Chen, Xueyong, 2018. "Recent advancements and challenges in Solar Tracking Systems (STS): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 250-279.
    12. Skouri, Safa & Ben Haj Ali, Abdessalem & Bouadila, Salwa & Ben Salah, Mohieddine & Ben Nasrallah, Sassi, 2016. "Design and construction of sun tracking systems for solar parabolic concentrator displacement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1419-1429.
    13. Rohani, Abbas & Taki, Morteza & Abdollahpour, Masoumeh, 2018. "A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I)," Renewable Energy, Elsevier, vol. 115(C), pages 411-422.
    14. Saranchimeg, Sainbold & Nair, Nirmal K.C., 2021. "A novel framework for integration analysis of large-scale photovoltaic plants into weak grids," Applied Energy, Elsevier, vol. 282(PA).
    15. Gönül, Ömer & Yazar, Fatih & Duman, A. Can & Güler, Önder, 2022. "A comparative techno-economic assessment of manually adjustable tilt mechanisms and automatic solar trackers for behind-the-meter PV applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    16. Furlan, Claudia & de Oliveira, Amauri Pereira & Soares, Jacyra & Codato, Georgia & Escobedo, João Francisco, 2012. "The role of clouds in improving the regression model for hourly values of diffuse solar radiation," Applied Energy, Elsevier, vol. 92(C), pages 240-254.
    17. Mohammadi, Kasra & Khorasanizadeh, Hossein, 2015. "A review of solar radiation on vertically mounted solar surfaces and proper azimuth angles in six Iranian major cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 504-518.
    18. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    19. Zervas, P.L. & Sarimveis, H. & Palyvos, J.A. & Markatos, N.C.G., 2008. "Prediction of daily global solar irradiance on horizontal surfaces based on neural-network techniques," Renewable Energy, Elsevier, vol. 33(8), pages 1796-1803.
    20. Kafka, Jennifer & Miller, Mark A., 2020. "The dual angle solar harvest (DASH) method: An alternative method for organizing large solar panel arrays that optimizes incident solar energy in conjunction with land use," Renewable Energy, Elsevier, vol. 155(C), pages 531-546.

    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:108:y:2013:i:c:p:429-438. 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.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.