Volume 8 Issue 2 - March 2017

  • 1. Evaluate the performance of power energy output forecasting in photovoltaic cell

    Authors : Dr. Sreeja Mole S S, Shiju Thankappan

    Pages : 67-71

    DOI : http://dx.doi.org/10.21172/1.82.010

    Keywords : Energy forecasting, Error Back Propagation

    Abstract :

    This paper illustrates an adaptive approach based on Artificial Neural Network (ANN) for power energy output forecasting of photovoltaic (PV) modules. Solar energy has the greatest energy potential and PV array permit to produce electric power directly from sunlight. ANN training is performed with error Back Propagation algorithm and feed forward network is used as network structure. The output power of solar photovoltaic cell is predicted on hourly basis. The dataset was collected from GECAD photovoltaic system. The accuracy of prediction can be done by using various error measurement criteria and performance is noted.

    Citing this Journal Article :

    Dr. Sreeja Mole S S, Shiju Thankappan, "Evaluate the performance of power energy output forecasting in photovoltaic cell", https://www.ijltet.org/journal_details.php?id=911&j_id=3659, Volume 8 Issue 2 - March 2017, 67-71, #ijltetorg