Forecasting of Solar Radiation of an Area by Using Artificial Neural Network Technique through Matlab
Abstract
Over the years, solar radiation is the area of major concern. Most of the inventions done in last few years, are in renewable energy generation as conventional energy sources are not enough for years to come. There is a need of finding alternatives of nonrenewable sources. This study is totally based on solar energy to give some contribution to the development of renewable energy generation. In this paper, a detailed analysis has been made for forecasting of solar radiation by using Artificial Neural Network. In this Forecasting method the inputs are taken by using different sensors, which are connected by Ardunio UNO board. The collected data then stored in a excel sheet by a software called PLX-DAQ, which represents collected data into a graphical form for further studies. Now this data can be used for developing an ANN model into MATLAB by using ANN toolbox. The network that is developed in MATLAB can be trained and sufficient information can be extracted from it. Compressions can be carried out with the original data and trained data and the results now shows rate of error between both. This will also give the forecast accuracy i.e. obviously improved under variable weather conditions.
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Join, Cdric, ”Shortterm solar irradiance and irradiation forecasts via different time series techniques: A preliminary study.” Environmental Friendly Energies and Applications (EFEA), 2014 3rd International Symposium on. IEEE, 2014.
Cornaro, C., et al. ”Twenty-Four Hour Solar Irradiance Forecast Based on Neural Networks and Numerical Weather Prediction.” Journal of Solar Energy Engineering 137.3 (2015): 031011.
Nummikoski, J., et al. ”Adaptive rule generation for solar forecasting: Interfacing with a knowledge-base library.” Photovoltaic Specialists Con- ference (PVSC), 2013 IEEE 39th. IEEE, 2013.
Perez, Richard, et al. ”Validation of short and medium term operational solar radiation forecasts in the US.” Solar Energy 84.12 (2010): 2161- 2172.
Kalogirou, Soteris A. ”Applications of artificial neural-networks for energy systems.” Applied energy 67.1 (2000): 17-35.
Yadav, Amit Kumar, and S. S. Chandel. ”Artificial neural network based prediction of solar radiation for Indian stations.” International Journal of Computer Applications 50.9 (2012).
Geetha, A., and G. M. Nasira. ”Artificial Neural Networks’ Applica- tion in Weather ForecastingUsing RapidMiner.” International Journal of Computational Intelligence and Informatics 4.2 (2014): 177-182.
Narvekar, Meera, and Priyanca Fargose. ”Daily weather forecasting using artificial neural network.” International Journal of Computer Applications 121.22 (2015).
Taohidul Islam, Sajal Saha, Ali Ahmed Evan, Nabonita Halder, Shakti Chandra Dey ”A power theft detection using wireless system”, In Monthly Weather Forecasting through ANN Model: A Case Study in Barisal, Bangladesh,pg 58-64.International Journal of Advanced Re- search in Computer and Communication Engineering Vol. 5, Issue 6,
June 2016
Malik, Pooja, Saranjeet Singh, and Binni Arora. ”An effective weather forecasting using neural network.” Int J Emerg Eng Res Technol 2.2 (2014): 209-212.
Baboo, S. Santhosh, and I. Kadar Shereef. ”An efficient weather forecasting system using artificial neural network.” International journal of environmental science and development 1.4 (2010): 321.
Sawale, Gaurav J., and Sunil R. Gupta. ”Use of artificial neural network in data mining for weather forecasting.” International Journal of Computer Science and Applications 6.2 (2013): 383-7.
SS, P. R. J., Kiran, P. B. S., Chowdary, P. N., Reddy, B. R. K., and Murthy, V. (2015). Weather forecasting using artificial neural networks and data mining techniques. IJITR, 3(6), 2534-2539.
Naik, Arti R., and S. K. Pathan. ”Weather classification and forecast- ing using back propagation feed-forward neural network.” International Journal of Scientific and Research Publications 2.12 (2012).
PriyankaSebastian, Janani B., and P. G. Scholar. ”ANALYSIS ON THE WEATHER FORECASTING AND TECHNIQUES.”
Sawaitul, Sanjay D., K. P. Wagh, and P. N. Chatur. ”Classification and prediction of future weather by using back propagation algorithm-an approach.” International Journal of Emerging Technology and Advanced Engineering 2.1 (2012): 110-113.
Chauhan, Divya, and Jawahar Thakur. ”Data mining techniques for weather prediction: A review.” International Journal on Recent and Innovation Trends in Computing and Communication 2.8 (2014): 2184-
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