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Forecasting of solar energy with application for a growing economy like India: Survey and implication

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  • Mohanty, Sthitapragyan
  • Patra, Prashanta K.
  • Sahoo, Sudhansu S.
  • Mohanty, Asit

Abstract

Solar energy is going to play a measure role in the future global energy supply. Its acceptance has already been on rise in developing countries like India, where there is acute shortage of energy due to economic and other climatic reasons. Forecasting or predicting the future output of solar energy is a much needed step to integrate high insolation of solar energy to the nation's power grid. Due to the fluctuating nature of solar energy, an efficient use is possible depending on reliable forecast information and its availability in various time and spatial scales. The current status of forecasting of solar irradiance for energy generation proposes a review of solar radiation prediction and its application in a rapidly increasing economy like India. Various models are developed for analysis which can be developed either by empirical, soft computing or by simulation approach.

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  • Mohanty, Sthitapragyan & Patra, Prashanta K. & Sahoo, Sudhansu S. & Mohanty, Asit, 2017. "Forecasting of solar energy with application for a growing economy like India: Survey and implication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 539-553.
    • Handle: RePEc:eee:rensus:v:78:y:2017:i:c:p:539-553
    DOI: 10.1016/j.rser.2017.04.107
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    1. Chattopadhyay, Deb, 2014. "Modelling renewable energy impact on the electricity market in India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 9-22.
    2. Parishwad, G.V. & Bhardwaj, R.K. & Nema, V.K., 1997. "Estimation of hourly solar radiation for India," Renewable Energy, Elsevier, vol. 12(3), pages 303-313.
    3. Soni, M.S. & Gakkhar, Nikhil, 2014. "Techno-economic parametric assessment of solar power in India: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 326-334.
    4. Chandel, S.S. & Nagaraju Naik, M. & Chandel, Rahul, 2015. "Review of solar photovoltaic water pumping system technology for irrigation and community drinking water supplies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1084-1099.
    5. Mohanty, Sthitapragyan & Patra, Prashanta Kumar & Sahoo, Sudhansu Sekhar, 2016. "Prediction and application of solar radiation with soft computing over traditional and conventional approach – A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 778-796.
    6. Fei Wang & Zengqiang Mi & Shi Su & Hongshan Zhao, 2012. "Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters," Energies, MDPI, vol. 5(5), pages 1-16, May.
    7. Chen, S.X. & Gooi, H.B. & Wang, M.Q., 2013. "Solar radiation forecast based on fuzzy logic and neural networks," Renewable Energy, Elsevier, vol. 60(C), pages 195-201.
    8. Shrimali, Gireesh & Rohra, Sunali, 2012. "India’s solar mission: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 6317-6332.
    9. Pandey, Chanchal Kumar & Katiyar, A.K., 2011. "A comparative study of solar irradiation models on various inclined surfaces for India," Applied Energy, Elsevier, vol. 88(4), pages 1455-1459, April.
    10. Beerbaum, S & Weinrebe, G, 2000. "Solar thermal power generation in India—a techno–economic analysis," Renewable Energy, Elsevier, vol. 21(2), pages 153-174.
    11. Kumar Sahu, Bikash, 2015. "A study on global solar PV energy developments and policies with special focus on the top ten solar PV power producing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 621-634.
    12. Sharma, Vikrant & Chandel, S.S., 2013. "Performance analysis of a 190 kWp grid interactive solar photovoltaic power plant in India," Energy, Elsevier, vol. 55(C), pages 476-485.
    13. Sharma, Atul, 2011. "A comprehensive study of solar power in India and World," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1767-1776, May.
    14. Khare, Vikas & Nema, Savita & Baredar, Prashant, 2013. "Status of solar wind renewable energy in India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 1-10.
    15. Wu, Ji & Chan, Chee Keong & Zhang, Yu & Xiong, Bin Yu & Zhang, Qing Hai, 2014. "Prediction of solar radiation with genetic approach combing multi-model framework," Renewable Energy, Elsevier, vol. 66(C), pages 132-139.
    16. Zhijian Liu & Hao Li & Xinyu Zhang & Guangya Jin & Kewei Cheng, 2015. "Novel Method for Measuring the Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters Based on Artificial Neural Networks and Support Vector Machine," Energies, MDPI, vol. 8(8), pages 1-21, August.
    17. Quitzow, Rainer, 2015. "Assessing policy strategies for the promotion of environmental technologies: A review of India's National Solar Mission," Research Policy, Elsevier, vol. 44(1), pages 233-243.
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