A review of bio-inspired computational intelligence algorithms in electricity load forecasting
SS Subbiah, J Chinnappan - Smart Buildings Digitalization, 2022 - taylorfrancis.com
The electricity load forecasting is an emerging research field in computer science. It plays a
major role in the power system and power utility companies for balancing the power demand …
major role in the power system and power utility companies for balancing the power demand …
Forecasting next-hour electricity demand in small-scale territories: Evidence from Jordan
S Nofal - Heliyon, 2023 - cell.com
In exceptional times of wars, natural crises (eg, snow storms), or hosting massive events (eg,
international sports events), prior knowledge of hour-by-hour electricity demand might …
international sports events), prior knowledge of hour-by-hour electricity demand might …
A real-time electrical load forecasting in Jordan using an enhanced evolutionary feedforward neural network
Power system planning and expansion start with forecasting the anticipated future load
requirement. Load forecasting is essential for the engineering perspective and a financial …
requirement. Load forecasting is essential for the engineering perspective and a financial …
Short-term load forecasting for Jordan power system based on NARX-ELMAN neural network and ARMA model
L Alhmoud, Q Nawafleh - IEEE Canadian Journal of Electrical …, 2021 - ieeexplore.ieee.org
Over the past few years, there is a vast expansion of the Jordan National Energy Sector.
Hence, National Electrical Power Company (NEPCO) sheds more light on load forecasting …
Hence, National Electrical Power Company (NEPCO) sheds more light on load forecasting …
Day-ahead residential electricity demand response model based on deep neural networks for peak demand reduction in the Jordanian power sector
Featured Application The presented model can be used as a baseline model for the
implementation of peak demand response systems in Jordan. The day-ahead prediction …
implementation of peak demand response systems in Jordan. The day-ahead prediction …
Solar PV power forecasting at Yarmouk University using machine learning techniques
Renewable energy sources are considered ubiquitous and drive the energy revolution.
Energy producers suffer from inconsistent electricity generation. They often struggled with …
Energy producers suffer from inconsistent electricity generation. They often struggled with …
Optimization of three-phase feeder load balancing using smart meters
L Alhmoud, W Marji - IEEE Canadian Journal of Electrical and …, 2021 - ieeexplore.ieee.org
Power losses in distribution systems are among the most important performance indicators
of electricity distribution companies' economic operations. Therefore, the distribution system …
of electricity distribution companies' economic operations. Therefore, the distribution system …
[PDF][PDF] Integration of predictive and computational intelligent techniques: A hybrid optimization mechanism for PMSM dynamics reinforcement.
S Chirantan, BB Pati - AIMS Electronics & Electrical Engineering, 2024 - aimspress.com
Integration of predictive and computational intelligent techniques: A hybrid optimization
mechanism for PMSM dynamics reinforcem Page 1 AIMS Electronics and Electrical …
mechanism for PMSM dynamics reinforcem Page 1 AIMS Electronics and Electrical …
Daily load curve prediction for Jordan based on statistical techniques
The article proposes a mathematical prediction model for daily load curves (DLCs) in Jordan
from 2023–2050. The historical hourly peak loads based on the growth rate statistical …
from 2023–2050. The historical hourly peak loads based on the growth rate statistical …
Short-term Load Forecasting using Genetic Algorithm based Artificial Neural Network
M Shakir - Jordan Journal of Energy, 2024 - dsr.mutah.edu.jo
The electrical load Forecasting is considered one of the main and important points for the
planning for the future in the electric power networks in both of transmission and distribution …
planning for the future in the electric power networks in both of transmission and distribution …