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A New Approach for Prediction of Solar Radiation with Using Ensemble Learning Algorithm

  • Research Article - Electrical Engineering
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Abstract

This article investigates the competence of ensemble learning techniques in solar irradiance prediction. It was seen from the literature survey, an ensemble tree model, random forests is studied more frequently as ensemble models. However, ensemble of support vector regression (SVR) and artificial neural networks (ANN) is also possible. So, this study is the first detailed evaluation of ensemble models in solar irradiance estimation domain. Boosting and bagging ensembles of SVR, ANN and decision tree (DT), are developed to estimate solar irradiance in hourly basis in five cities in Turkey. First frequently used base models (SVR, ANN, and DT) are created and tested with the use of 5 years meteorological data. Then boosting and bagging ensembles of the base models are developed and tested with the same data. The base models are compared with their ensemble counterparts in terms of average coefficient of determination (R2) and root mean squared error (RMSE). The comparative results show that boosting and bagging ensemble models improve SVR, ANN, and DT in terms of RMSE between 4.6 and 14.6% in average. The results show empirically that ensemble models improve prediction accuracies of various base regression models and it can be applied to other machine learning models used in solar irradiance prediction.

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Abbreviations

DMI:

Turkish state meteorological service

SDF:

Sunshine duration fraction

MSDF:

Modified sunshine duration fraction

ANFIS:

Adaptive neuro-fuzzy inference system

ARMA:

Autoregressive moving average

ANN:

Artificial neural network

MLP:

Multi-layer perceptron

SVM:

Support vector machine

SVR:

Support vector regression

DT:

Decision-tree

ID3:

Iternative Dichotomizer

KNN:

K-nearest neighbors

GBT:

Gradient boosting tree

RF:

Random forests

RMSE:

Root mean square error

R 2 :

Coefficient of determination

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Authors and Affiliations

  1. Department of Energy Systems Engineering, Manisa Celal Bayar University, Manisa, Turkey

    Kivanc Basaran

  2. Department of Software Engineering, Manisa Celal Bayar University, Manisa, Turkey

    Akın Özçift & Deniz Kılınç

Authors
  1. Kivanc Basaran
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  2. Akın Özçift
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  3. Deniz Kılınç
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Correspondence to Kivanc Basaran.

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Basaran, K., Özçift, A. & Kılınç, D. A New Approach for Prediction of Solar Radiation with Using Ensemble Learning Algorithm. Arab J Sci Eng 44, 7159–7171 (2019). https://doi.org/10.1007/s13369-019-03841-7

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  • DOI: https://doi.org/10.1007/s13369-019-03841-7

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