• DocumentCode
    3578584
  • Title

    Predicting power output of photovoltaic systems with solar radiation model

  • Author

    Lurwan, Sabo Mahmoud ; Mariun, Norman ; Hizam, Hashim ; Radzi, Mohd Amran Mohd ; Zakaria, Azmi

  • Author_Institution
    Centre for Adv. Power & Energy Res. (CAPER), Univ. Putra Malaysia, Serdang, Malaysia
  • fYear
    2014
  • Firstpage
    304
  • Lastpage
    308
  • Abstract
    Predicting of solar resource in general is momentous for preparation of the operations of power plants which transform renewable energies to electricity. In particular, the possibility to predict the solar irradiance (up to one day or even more) can become of significant interest with reference to Grid connected Photovoltaic (PV) Plants, stand alone and hybrid system. In this paper, a MATLAB/SIMULINK simulation based model for predicting hourly solar radiation using modified Hottel´s radiation model is presented. The proposed modified Hottel´s model makes it possible to predict solar radiation on hourly basis using current values of day type and geography of the location. While predicting power output, the model requires information of the weather forecast of the day to be predicted, some data from solar module datasheet is use and predicted radiation. The predicted results are compared with outdoor data collected by horizontal mount pyranometer at coordinates (2.945N, 101.728E) on 24th, June 2012. The results indicated the proposed model performed well after comparison with field data, having a correlation coefficient of 97%, also recorded 96% and 76% with Hottel´s and Ashrae model respectively.
  • Keywords
    load forecasting; photovoltaic power systems; power grids; renewable energy sources; solar radiation; Ashrae model; Hottels radiation model; MATLAB/SIMULINK simulation; grid connected photovoltaic plants; horizontal mount pyranometer; hybrid system; photovoltaic systems; predicting hourly solar radiation; renewable energies; solar irradiance; solar radiation model; stand alone; weather forecast; Atmospheric modeling; Data models; Mathematical model; Meteorology; Photovoltaic systems; Predictive models; Solar radiation; Photovoltaic systems; Power; Prediction; solar radiation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy (PECon), 2014 IEEE International Conference on
  • Print_ISBN
    978-1-4799-7296-8
  • Type

    conf

  • DOI
    10.1109/PECON.2014.7062461
  • Filename
    7062461