Grid integration challenges of wind energy: A review

SD Ahmed, FSM Al-Ismail, M Shafiullah… - Ieee …, 2020 - ieeexplore.ieee.org
The strengthening of electric energy security and the reduction of greenhouse gas
emissions have gained enormous momentum in previous decades. The integration of large …

Weather forecasting for renewable energy system: a review

R Meenal, D Binu, KC Ramya, PA Michael… - … Methods in Engineering, 2022 - Springer
Energy crisis and climate change are the major concerns which has led to a significant
growth in the renewable energy resources which includes mainly the solar and wind power …

Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method

I Karijadi, SY Chou, A Dewabharata - Renewable Energy, 2023 - Elsevier
A precise wind power forecast is required for the renewable energy platform to function
effectively. By having a precise wind power forecast, the power system can better manage its …

[HTML][HTML] A review of short-term wind power generation forecasting methods in recent technological trends

EA Tuncar, Ş Sağlam, B Oral - Energy Reports, 2024 - Elsevier
Climate change and the escalating demand for energy are among the most pressing global
challenges of our era. Renewable energy sources, such as wind energy, are considered a …

Weather image-based short-term dense wind speed forecast with a ConvLSTM-LSTM deep learning model

L Zheng, W Lu, Q Zhou - Building and Environment, 2023 - Elsevier
Short-term wind speed predication is of great significance for scholars (eg, understanding
wind profiles), practitioners (eg, building energy management), regulators (eg, urban …

Deep learning in electrical utility industry: A comprehensive review of a decade of research

M Mishra, J Nayak, B Naik, A Abraham - Engineering Applications of …, 2020 - Elsevier
Smart-grid (SG) is a new revolution in the electrical utility industry (EUI) over the past
decade. With each moving day, some new advanced technologies are coming into the …

Large-scale wind power grid integration challenges and their solution: a detailed review

MS Mastoi, S Zhuang, M Haris, M Hassan… - … Science and Pollution …, 2023 - Springer
Despite global warming, renewable energy has gained much interest worldwide due to its
ability to generate large-scale energy without emitting greenhouse gases. The availability …

Wind speed behaviors feather analysis and its utilization on wind speed prediction using 3D-CNN

X Zhu, R Liu, Y Chen, X Gao, Y Wang, Z Xu - Energy, 2021 - Elsevier
Aiming at the local wind speed prediction of each turbine in the wind farm, a wind speed
prediction method based on feature analysis of wind speed behavior coupling the time …

[PDF][PDF] Integration of machine learning (ML) and finite element analysis (FEA) for predicting the failure modes of a small horizontal composite blade

AAF Ogaili, MN Hamzah, AA Jaber - International Journal of …, 2022 - researchgate.net
This article aims to integrate machine learning (ML) methodologies and Finite Element
Analysis (FEA) to analyze wind turbine blades made of composite material. The methods for …

A short-term forecasting of wind power outputs based on gradient boosting regression tree algorithms

S Park, S Jung, J Lee, J Hur - Energies, 2023 - mdpi.com
With growing interest in sustainability and net-zero emissions, there has been a global trend
to integrate wind power into energy grids. However, challenges such as the intermittency of …