Paper Title :A Hybrid Artificial Neural Network And Particle Swarm Optimization (ANN-PSO) Algorithm To Predict Photovoltaic Power Plant Performance- A Case Study
Author :Kh. Hemmatpour, M.A. Behrang
Article Citation :Kh. Hemmatpour ,M.A. Behrang ,
(2016 ) " A Hybrid Artificial Neural Network And Particle Swarm Optimization (ANN-PSO) Algorithm To Predict Photovoltaic Power Plant Performance- A Case Study " ,
International Journal of Soft Computing And Artificial Intelligence (IJSCAI) ,
pp. 71-78,
Volume-4,Issue-1
Abstract : Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. While the solar
radiation that reaches the top of the layers of the atmosphere can be easily calculated, the solar irradiance that reaches the
ground level where solar collectors (thermal and photovoltaic) operate depends strongly on localized and complex
atmospheric conditions. In the first part of this study, ANN-PSO technique is applied to predict daily global solar radiation
(GSR) on a horizontal surface, based on meteorological variables. Daily maximum air temperature, minimum air
temperature, mean air temperature, maximum relative humidity, minimum relative humidity, mean relative humidity,
maximum possible sunshine duration, sunshine hours, cloud cover, evaporation and wind speed data between 2000 and 2011
provided by Safiabad station, located in Dezful city, Iran (32° 16' N, 48° 25' E), are used as inputs to neural network and
daily GSR used as output. The measured data between 2000 and 2008 are used to train the neural networks and the available
data (732 days) from 2009 (January) to 2011 (April) are used for testing. Sensitivity Analysis is investigated to show the
effect that each of the model inputs (i.e. meteorological variables) have on the model output (i.e. GSR). Eventually, In order
to show the accuracy of the proposed method (i.e. MLP-PSO), a comparison is made with Backpropagation trained Multi-
Layer Perceptron Neural Networks (MLP-BP) for same study. In the second part of the paper, monthly electricity generated
for a 20 MW photovoltaic (PV) power plant is considered.
Keywords- Global Solar Radiation (GSR), Multi-Layer Perceptron Neural Network (MLP), Particle Swarm Optimization
(PSO), Error Backpropagation (BP) Algorithm, Meteorological Variables, Modeling, RETScreen Software.
Type : Research paper
Published : Volume-4,Issue-1
DOIONLINE NO - IJSCAI-IRAJ-DOIONLINE-4629
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Copyright: © Institute of Research and Journals
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Published on 2016-06-09 |
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