Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
Review on deep learning research and applications in wind and wave energy
Wind energy and wave energy are considered to have enormous potential as renewable
energy sources in the energy system to make great contributions in transitioning from fossil …
energy sources in the energy system to make great contributions in transitioning from fossil …
Data-driven interpretable ensemble learning methods for the prediction of wind turbine power incorporating SHAP analysis
Wind energy increasingly attracts investment from many countries as a clean and renewable
energy source. Since wind energy investment cost is high, the efficiency of a potential wind …
energy source. Since wind energy investment cost is high, the efficiency of a potential wind …
An evolutionary deep learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM for wind speed prediction
Accurate prediction of wind speed is of great significance to the stable operation of wind
power equipment. In this study, a hybrid deep learning model based on convolutional neural …
power equipment. In this study, a hybrid deep learning model based on convolutional neural …
Integrated framework of extreme learning machine (ELM) based on improved atom search optimization for short-term wind speed prediction
L Hua, C Zhang, T Peng, C Ji, MS Nazir - Energy Conversion and …, 2022 - Elsevier
Wind energy plays an important role in terms of renewable energy. Accurate and reliable
wind speed prediction is essential for effective use of wind energy. However, the uncertainty …
wind speed prediction is essential for effective use of wind energy. However, the uncertainty …
Wind speed prediction by a swarm intelligence based deep learning model via signal decomposition and parameter optimization using improved chimp optimization …
L Suo, T Peng, S Song, C Zhang, Y Wang, Y Fu… - Energy, 2023 - Elsevier
Accurate prediction of wind speed plays a very important role in the stable operation of wind
power plants. In this study, the goal is to establish a hybrid wind speed prediction model …
power plants. In this study, the goal is to establish a hybrid wind speed prediction model …
Evolutionary quantile regression gated recurrent unit network based on variational mode decomposition, improved whale optimization algorithm for probabilistic short …
C Zhang, C Ji, L Hua, H Ma, MS Nazir, T Peng - Renewable Energy, 2022 - Elsevier
Wind energy, as clean energy, has attracted more and more attention. Wind power
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
Load forecasting for regional integrated energy system based on complementary ensemble empirical mode decomposition and multi-model fusion
J Shi, J Teh - Applied Energy, 2024 - Elsevier
The multiple loads of the Regional Integrated Energy System (RIES) possess characteristics
of randomness and relatively higher complexity. The current forecasting methods struggle to …
of randomness and relatively higher complexity. The current forecasting methods struggle to …
Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization
This study proposes an effective combined model system for wind speed forecasting tasks.
In this model,(a) improved hybrid time series decomposition strategy (HTD) is developed to …
In this model,(a) improved hybrid time series decomposition strategy (HTD) is developed to …
A novel integrated photovoltaic power forecasting model based on variational mode decomposition and CNN-BiGRU considering meteorological variables
C Zhang, T Peng, MS Nazir - Electric Power Systems Research, 2022 - Elsevier
The present study aims to develop an integrated multivariate model based on variational
mode decomposition (VMD), convolutional neural network (CNN) and Bi-directional gated …
mode decomposition (VMD), convolutional neural network (CNN) and Bi-directional gated …