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
Link To Document :
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