Academic Journal

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

التفاصيل البيبلوغرافية
العنوان: Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model
المؤلفون: Ray, P. K., Subudhi, B., Putrus, G., Marzband, M., Ali, Z.
بيانات النشر: CSEE
سنة النشر: 2022
المجموعة: LSBU Research Open (London South Bank University)
مصطلحات موضوعية: Predictive models, Numerical models, Indexes, Weather forecasting, Forecasting, Data models, Mathematical models
الوصف: 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.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: unknown
Relation: https://openresearch.lsbu.ac.uk/download/de57c2fdc9a2fb9bd3dabe685fc4d60d9f44bbd0b8ed8bbd02bbc555513bea75/1386302/Forecasting%20Global%20Solar%20Insolation%20Using%20the%20Ensemble%20Kalman%20Filter%20Based%20Clearness%20Index%20Model.pdf; https://doi.org/10.17775/CSEEJPES.2021.06230; 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
DOI: 10.17775/CSEEJPES.2021.06230
الاتاحة: https://openresearch.lsbu.ac.uk/item/94677
https://openresearch.lsbu.ac.uk/download/de57c2fdc9a2fb9bd3dabe685fc4d60d9f44bbd0b8ed8bbd02bbc555513bea75/1386302/Forecasting%20Global%20Solar%20Insolation%20Using%20the%20Ensemble%20Kalman%20Filter%20Based%20Clearness%20Index%20Model.pdf
https://doi.org/10.17775/CSEEJPES.2021.06230
Rights: CC BY 4.0
رقم الانضمام: edsbas.854E0913
قاعدة البيانات: BASE
الوصف
DOI:10.17775/CSEEJPES.2021.06230