Abdallah Abdellatif, Hamza Mubarak, Shameem Ahmad, Tofael Ahmed et al.
Nowadays, photovoltaics (PV) has gained popularity among other renewable energy sources because of its excellent features. However, the instability of the system’s output has become a critical problem due to the high PV penetration into the existing distribution system. Hence, it is essential to hav...
Hamza Mubarak, Ahmad Hammoudeh, Shameem Ahmad, Abdallah Abdellatif et al.
Nowadays, with the growing interest in green energy, further improvements in photovoltaic (PV) power systems are needed. In this regard, the main aim is to find an optimal method to predict the output power of PV systems to maintain a sustainable operation. Hence, this work proposes a hybrid Machine...
Hamza Mubarak, Abdallah Abdellatif, Shameem Ahmad, Md. Zohurul Islam et al.
• A hybrid DL model (CNN-BiLSTM-AR) is proposed to forecast the electricity price. • Integrating an AR model in parallel with a CNN-BiLSTM enhances the performance. • The influence of incorporating HPO methods like GA, PSO, and RS is investigated. • Performance difference between the models is verif...
Abdallah Abdellatif, Hamza Mubarak, Shameem Ahmad, Saad Mekhilef et al.
This study proposes hybrid Deep Learning (DL) models for electricity price forecasting (EPF) one day ahead of the Nord Pool spot electricity market. The proposed hybrid DL model employs the Bidirectional Long Short-Term Memory (BiLSTM) and Convolution Neural Network (CNN) to identify short-term loca...
Hamza Mubarak, Shameem Ahmad, Al Amin Hossain, Ben Horan et al.
In this paper, a combination of single and hybrid Machine learning (ML) models were proposed to forecast the electricity price one day ahead for the Nord Pool spot electricity market. The proposed models were evaluated based on performance metrics, such as Root Mean Square Error (RMSE), Mean Square ...
Hamza Mubarak, Abdallah Abdellatif, Shameem Ahmad, Ahmad Hammoudeh et al.
This paper presents solar photovoltaic (PV) energy prediction based on thin-film technology utilizing various machine learning (ML) models. Several ML models like Support Vector Machine (SVM), Extra Tree Regression (ETR), Decision Tree Regression (DTR), K-Nearest Neighbour (kNN) and Feed-Forward Neu...
Abdallah Abdellatif, Hamza Mubarak, Shameem Ahmad, Ahmad Hammoudeh et al.
This paper presents solar photovoltaic (PV) energy prediction based on Polycrystalline technology utilizing various ensemble machine learning (ML) models. Several ML models like Extra Tree Regressor (ETR), Decision Tree Regression (DTR), Random Forest Regressor (RFR), Adaptive Boosting (AdaBoost), a...