A tutorial review of neural network modeling approaches for model predictive control

YM Ren, MS Alhajeri, J Luo, S Chen, F Abdullah… - Computers & Chemical …, 2022 - Elsevier
An overview of the recent developments of time-series neural network modeling is
presented along with its use in model predictive control (MPC). A tutorial on the construction …

Fault prediction based on leakage current in contaminated insulators using enhanced time series forecasting models

NF Sopelsa Neto, SF Stefenon, LH Meyer, RG Ovejero… - Sensors, 2022 - mdpi.com
To improve the monitoring of the electrical power grid, it is necessary to evaluate the
influence of contamination in relation to leakage current and its progression to a disruptive …

Carbon price forecasting based on CEEMDAN and LSTM

F Zhou, Z Huang, C Zhang - Applied energy, 2022 - Elsevier
Abstract After signing the Paris Agreement and piloting carbon trading for many years, China
has taken a significant step toward carbon neutrality. Carbon price forecasting is helpful to …

Efficient bootstrap stacking ensemble learning model applied to wind power generation forecasting

MHDM Ribeiro, RG da Silva, SR Moreno… - International Journal of …, 2022 - Elsevier
The use of wind energy plays a vital role in society owing to its economic and environmental
importance. Knowing the wind power generation within a specific time window is useful for …

A novel decomposition-ensemble learning framework for multi-step ahead wind energy forecasting

RG da Silva, MHDM Ribeiro, SR Moreno, VC Mariani… - Energy, 2021 - Elsevier
Wind energy is one of the sources which is still in development in Brazil. However, it already
represents 17% of the National Interconnected System. Due to the high level of uncertainty …

Aggregating prophet and seasonal trend decomposition for time series forecasting of Italian electricity spot prices

SF Stefenon, LO Seman, VC Mariani, LS Coelho - Energies, 2023 - mdpi.com
The cost of electricity and gas has a direct influence on the everyday routines of people who
rely on these resources to keep their businesses running. However, the value of electricity is …

Time series forecasting using ensemble learning methods for emergency prevention in hydroelectric power plants with dam

SF Stefenon, MHDM Ribeiro, A Nied, KC Yow… - Electric Power Systems …, 2022 - Elsevier
In hydroelectric plants, the responsibility for the operation of the reservoirs typically lies with
the national system operator, who controls the level of the reservoirs based on a stochastic …

Classification of insulators using neural network based on computer vision

SF Stefenon, MP Corso, A Nied… - IET Generation …, 2022 - Wiley Online Library
Insulators of the electrical power grid are usually installed outdoors, so they suffer from
environmental stresses, such as the presence of contamination. Contamination can increase …

Echo state network applied for classification of medium voltage insulators

SF Stefenon, LO Seman, NFS Neto, LH Meyer… - International Journal of …, 2022 - Elsevier
Insulators are components of electrical power grid that have the function of mechanically
supporting cables and isolating electrical potential. The proper functioning of the insulators …

Artificial intelligence of things applied to assistive technology: a systematic literature review

MP de Freitas, VA Piai, RH Farias, AMR Fernandes… - Sensors, 2022 - mdpi.com
According to the World Health Organization, about 15% of the world's population has some
form of disability. Assistive Technology, in this context, contributes directly to the overcoming …