Artificial Neural Network Model of a 25 kW (Peak) Grid Connected Solar Photovoltaic Power Plant

Vol.1 No.3

Year: 2008

Issue: Jan-Mar

Title: Artificial Neural Network Model of a 25 kW (Peak) Grid Connected Solar Photovoltaic Power Plant   

Author Name: M. Rizwan Khan, Atif Iqbal , Imtiaz Ashraf   

Synopsis:

   This paper present an artificial neural network (ANN) approach for forecasting the electric energy output from a 25-kWp grid connected solar photovoltaic power plant (SPVPP) installed at Vibhuti Khand, Lucknow, Utter Pardesh, India. The main aim is to develop a model of the system using artificial neural network (ANN) that can accurately forecast electrical energy output generated from the grid connected solar PV system. The ANN interpolates among the solar PV generation output and relevant parameters such as average solar insolation, average module temperature and average humidity . In this study, an ANN model is implemented and validated with reasonable accuracy on real electric energy generation output data. The physical layout and salient features of the power plant is also reported. The proposed ANN method can be extended to any solar photovoltaic power plant (SPVPP) for forecasting energy generation.

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