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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
T. Logeswaran
Kongu Engineering College
Control & Systems Engineering Electrical & Electronics Engineering

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Multi-output deep learning framework for joint forecasting of solar irradiance and wind speed with cross-regional transferability analysis S. Selvi; Annamalai Muthu; Murali Narayanamurthy; B. Ardly Melba Reena; Gobimohan Sivasubramanian; T. Logeswaran
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2101-2111

Abstract

Accurate forecasting of solar irradiance and wind speed is essential for improving hybrid renewable energy systems and ensuring grid stability. This study develops and evaluates a multi-output deep learning framework for the simultaneous prediction of global horizontal irradiance (GHI) and wind speed across multiple Indian regions. Hourly data from the National Solar Radiation Database (NSRDB) for the period 2015–2020 were used to train light gradient boosting machine (LightGBM), long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM), and convolutional long short-term memory (ConvLSTM) models, with cross-regional transfer learning applied across Tamil Nadu, Kerala, Karnataka, and Andhra Pradesh. Among the models, ConvLSTM achieved the best performance with a mean absolute error (MAE) of 0.061 and an R² value of approximately 0.91, while BiLSTM demonstrated comparable accuracy with lower computational cost. The proposed framework emphasizes cross-regional transferability, demonstrating robust generalization across heterogeneous climatic conditions. Error distribution analysis further indicates improved prediction stability, with ConvLSTM exhibiting lower variability compared to other models. These results support scalable and reliable renewable energy forecasting, with practical implications for grid operation, power electronic control, and hybrid energy system management.
Co-Authors Annamalai Muthu B. Ardly Melba Reena Gobimohan Sivasubramanian Murali Narayanamurthy S. Selvi