Short-term prediction of global solar radiation energy using weather data and machine learning ensembles: A comparative study
The ability to predict solar radiation one-day-ahead is critical for the best management of
renewable energy tied-grids. Several machine learning ensemble techniques have been …
renewable energy tied-grids. Several machine learning ensemble techniques have been …
An MPC-based dual-solver optimization method for DC microgrids with simultaneous consideration of operation cost and power loss
In this paper, a dual-solver framework based on model predictive control (MPC) is proposed,
E-solver and L-solver. The economic scheduling problem is formulated using mixedinteger …
E-solver and L-solver. The economic scheduling problem is formulated using mixedinteger …
A review on energy forecasting algorithms crucial for energy industry development and policy design
M Babu, P Ray - Energy Sources, Part A: Recovery, Utilization, and …, 2021 - Taylor & Francis
The power extracted from non-conventional energy sources has increased significantly in
recent days, and power extracted from renewable energy will play an essential part in the …
recent days, and power extracted from renewable energy will play an essential part in the …
A nonlinear autoregressive neural network for interference prediction and resource allocation in URLLC scenarios
C Padilla, R Hashemi, NH Mahmood… - … on Information and …, 2021 - ieeexplore.ieee.org
Ultra reliable low latency communications (URLLC) is a new service class introduced in 5G
which is characterized by strict reliability (1–10− 5) and low latency requirements (1 ms). To …
which is characterized by strict reliability (1–10− 5) and low latency requirements (1 ms). To …
Forecasting solar radiation strength using machine learning ensemble
To enhance the forecasting of solar radiation strength on horizontals, an ensemble learning
approach is proposed. Two types of machine learning models are arranged to predict solar …
approach is proposed. Two types of machine learning models are arranged to predict solar …
Blood glucose level prediction of diabetic type 1 patients using nonlinear autoregressive neural networks
Diabetes type 1 is a chronic disease which is increasing at an alarming rate throughout the
world. Studies reveal that the complications associated with diabetes can be reduced by …
world. Studies reveal that the complications associated with diabetes can be reduced by …
Stacking-based ensemble of support vector regressors for one-day ahead solar irradiance prediction
The integration of Solar Energy in smart grids and many utilities is continuously increasing
due to its environmental and economical benefits. However, the uncertainty of available …
due to its environmental and economical benefits. However, the uncertainty of available …
A new method for generating short-term power forecasting based on artificial neural networks and optimization methods for solar photovoltaic power plants
In recent times, solar PV power plants have been used worldwide due to their high solar
energy potential. Although the PV power plants are highly preferred, the main disadvantage …
energy potential. Although the PV power plants are highly preferred, the main disadvantage …
Long short-term memory model for time series prediction and forecast of solar radiation and other weather parameters
A Abayomi-Alli, MO Odusami… - … science and its …, 2019 - ieeexplore.ieee.org
Interest in the solar radiation and associated meteorological variables have been growing
over the years due to their effect on energy generation, agriculture and food security, Ozone …
over the years due to their effect on energy generation, agriculture and food security, Ozone …
A review on solar radiation assessment and forecasting in Algeria:(Part 2; Solar radiation forecasting)
Solar radiation forecasting is an important component in many areas related to either the
production or exploitation of renewable energies. This field has attracted the attention of …
production or exploitation of renewable energies. This field has attracted the attention of …