Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model

Journal article


Ray, P. K., Subudhi, B., Putrus, G., Marzband, M. and Ali, Z. (2022). Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model. IEEE CSEE Journal of Power and Energy Systems. 8 (4), pp. 1087-1096. https://doi.org/10.17775/CSEEJPES.2021.06230
AuthorsRay, P. K., Subudhi, B., Putrus, G., Marzband, M. and Ali, Z.
Abstract

This paper describes a novel approach in developing a model for forecasting of global insolation on a horizontal plane. In the proposed forecasting model, constraints, such as latitude and whole precipitable water content in vertical column of that location, are used. These parameters can be easily measurable with a global positioning system (GPS). The earlier model was developed by using the above datasets generated from different locations in India. The model has been verified by calculating theoretical global insolation for different sites covering east, west, north, south and the central region with the measured values from the same locations. The model has also been validated on a region, from which data was not used during the development of the model. In the model, clearness index coefficients (KT) are updated using the ensemble Kalman filter (EnKF) algorithm. The forecasting efficacies using the KT model and EnKF algorithm have also been verified by comparing two popular algorithms, namely the recursive least square (RLS) and Kalman filter (KF) algorithms. The minimum mean absolute percentage error (MAPE), mean square error (MSE) and correlation coefficient (R) value obtained in global solar insolation estimations using EnKF in one of the locations are 2.4%, 0.0285 and 0.9866 respectively.

KeywordsPredictive models , Numerical models , Indexes , Weather forecasting , Forecasting , Data models , Mathematical models
Year2022
JournalIEEE CSEE Journal of Power and Energy Systems
Journal citation8 (4), pp. 1087-1096
PublisherCSEE
ISSN2096-0042
Digital Object Identifier (DOI)https://doi.org/10.17775/CSEEJPES.2021.06230
Web address (URL)https://ieeexplore.ieee.org/abstract/document/9770547
Publication dates
Print06 May 2022
Publication process dates
Deposited07 Jul 2023
Accepted author manuscript
License
File Access Level
Open
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