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Long-Term Solar Irradiance Forecast Using Artificial Neural Network: Application for Performance Prediction of Indian Cities

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Applications of Artificial Intelligence Techniques in Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 697))

Abstract

Solar radiation data is extremely useful for utilizing solar energy in applications like solar power plants and solar heating. As the fossil fuel resources are degrading, renewable sources of energy like solar energy can reduce our dependence on fossil fuels. Solar energy is also a clean form of energy. In this paper, we have made use of Artificial Neural Network (ANN) for Solar Radiation Prediction (SRP). The ANN network used is Feed Forward with Backpropagation (FFBP), Backpropagation being the learning algorithm. A three-layer network has been used with one hidden layer. The data used was from 67 cities in India, which was further divided in two sets, namely—training and testing. The testing data was not used to train the network. There were 19 input parameters for the network with one output parameter solar radiation.

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Correspondence to Hasmat Malik .

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Malik, H., Garg, S. (2019). Long-Term Solar Irradiance Forecast Using Artificial Neural Network: Application for Performance Prediction of Indian Cities. In: Malik, H., Srivastava, S., Sood, Y., Ahmad, A. (eds) Applications of Artificial Intelligence Techniques in Engineering . Advances in Intelligent Systems and Computing, vol 697. Springer, Singapore. https://doi.org/10.1007/978-981-13-1822-1_26

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