Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

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• 作者：Aneela Zameer^a ; ^{aneelas@gmail.com} ; ^{aneelaz@pieas.edu.pk} ; Junaid Arshad^a ; ^b ; ^{Junaid.pieas@gmail.com} ; Asifullah Khan^a ; ^{asif@pieas.edu.pk} ; Muhammad Asif Zahoor Raja^c ; ^{rasifzahoor@yahoo.com}
• 关键词：Wind power forecasting ; Meterological variables ; Regression ; Genetic programming ; Artificial neural network ; Ensemble
• 刊名：Energy Conversion and Management
• 出版年：2017
• 出版时间：15 February 2017
• 年：2017
• 卷：134
• 期：Complete
• 页码：361-372
• 全文大小：3564 K
• 卷排序：134

文摘

Genetic programming based ensemble of neural networks is employed for short term wind power prediction. Proposed predictor shows resilience against abrupt changes in weather. Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. Proposed approach gives mathematical expressions of wind power to its independent variables. Proposed model shows relatively accurate and steady wind-power prediction performance.