• DocumentCode
    3776379
  • Title

    Forecasting of 5MW solar photovoltaic power plant generation using generalized neural network

  • Author

    Vikas Pratap Singh;B. Ravindra;Vivek Vijay;M. Siddhartha Bhatt

  • Author_Institution
    Department of Mechanical, Indian Institute of Technology Jodhpur, Rajasthan, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The percentage of renewable energy sources such as solar, wind power and biomass in the energy mix of India is increasing every year. Solar power variability is an important issue for grid integration of solar photovoltaic power plants. The main objective of this paper is to forecast the power generated in a 5 MW solar PV plant owned by Gujarat Power Corporation Limited (GPCL) at Charanka solar park, Gujarat. Charanka is a location with an average of320 sunny days in a year. Average solar insolation available here is 5.7-6.0 kWh/m2 per day. Data obtained from 1st March 2014-31st August 2014 is used for analysis purposes. In this paper a two stage procedure is used referred to as GNN (Generalized Neural Network) model. In the primary stage pre-processing is done on the raw data followed by neural network model for forecasting.
  • Keywords
    "Artificial neural networks","Predictive models","Solar power generation","Forecasting","Biological neural networks","Training"
  • Publisher
    ieee
  • Conference_Titel
    Systems Conference (NSC), 2015 39th National
  • Type

    conf

  • DOI
    10.1109/NATSYS.2015.7489107
  • Filename
    7489107