Abstract—In this paper, autoregressive moving average (ARMA) has modeling for solar irradiation forecast by combining two types of parameter estimation methods, Forgetting Factor (FF) and Kalman Filter (KF). For this purpose, the geographical location of length, width and average height than 76.75 e, 31.75 N and 1130.3 meters were used. Parameter with regard to the mean absolute error (MAE), root mean square error (RMSE), mean square error (MSE) and R2 estimator is compared. The result shows that the KF consists of high convergence rate to solve complex problems.
Index Terms—Solar irradiation, autoregressive moving average, forgetting factor, Kalman filter.
Yashwant Kashyap and Satyanarayan Patel are with the School of Engineering, Indian Institute of Technology Mandi, 175005 India (tel.: 91-9805-911710; e-mail: yashwant.kashyap@gmail.com, satyou1990@gmail.com).
Ankit Bansal is with the Department of Mechanical and Industrial Engineering, 233 MIED, IIT Roorkee, 247667 India (e-mail: abansfme@iitr.ac.in).
Anil K. Sao is with the School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India (e-mail: anil@iitmandi.ac.in).
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Cite:Yashwant Kashyap, Ankit Bansal, Anil K. Sao, and Satyanarayan Patel, "Comparative Study of Parameter Estimation Methods for Solar Irradiation Forecasting," Journal of Clean Energy Technologies vol. 4, no. 3, pp. 192-196, 2016.
