A state-of-the-art review of long short-term memory models with applications in hydrology and water resources

Z Feng, J Zhang, W Niu - Applied Soft Computing, 2024‏ - Elsevier
Abstract Long Short-Term Memory (LSTM) has recently emerged as a crucial tool for
scientific research in hydrology and water resources. Despite its widespread use, a …

Artificial neural networks for photovoltaic power forecasting: a review of five promising models

R Asghar, FR Fulginei, M Quercio, A Mahrouch - IEEE Access, 2024‏ - ieeexplore.ieee.org
Solar energy is largely dependent on weather conditions, resulting in unpredictable,
fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power …

A novel WaveNet-GRU deep learning model for PEM fuel cells degradation prediction based on transfer learning

MJ Izadi, P Hassani, M Raeesi, P Ahmadi - Energy, 2024‏ - Elsevier
Abstract Precise prediction of Remaining Useful Life (RUL) within the transportation industry
is essential for cost reduction and enhanced energy efficiency, focusing on extending the …

A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation

Y Zhou, J Wang, C Wei, Y Li - Energy, 2024‏ - Elsevier
Small-scale distributed energy systems with combined cooling, heating, and power (DES-
CCHP) production have attracted international interest. However, fluctuating loads and …

InfoCAVB-MemoryFormer: Forecasting of wind and photovoltaic power through the interaction of data reconstruction and data augmentation

M Zhong, J Fan, J Luo, X **ao, G He, R Cai - Applied Energy, 2024‏ - Elsevier
Rare or missing data pose significant challenges in the prediction of wind power (WP) and
photovoltaic power (PV). Many methods address the data scarcity issue solely through …

Power system flexibility analysis using net-load forecasting based on deep learning considering distributed energy sources and electric vehicles

ET Rizi, M Rastegar, A Forootani - Computers and Electrical Engineering, 2024‏ - Elsevier
Today, wind and solar energy sources have opened their place in the power system due to
their environmental appeal. With the presence of these renewable energy sources (RESs) …

Short-term PV power data prediction based on improved FCM with WTEEMD and adaptive weather weights

F Sun, L Li, D Bian, H Ji, N Li, S Wang - Journal of Building Engineering, 2024‏ - Elsevier
Photovoltaic (PV) systems are commonly used in zero energy buildings (ZEBs) due to their
high efficiency and convenience. However, PV systems are affected by meteorological …

An interpretable hybrid spatiotemporal fusion method for ultra-short-term photovoltaic power prediction

B Gong, A An, Y Shi, H Guan, W Jia, F Yang - Energy, 2024‏ - Elsevier
For a long time, fossil fuels have been the primary source for meeting energy demands and
driving economic growth worldwide [[1],[2],[3]]. However, in recent years, the negative …

Water resource management and flood mitigation: hybrid decomposition EMD-ANN model study under climate change

N Ahmad, X Yi, M Tayyab, MH Zafar… - Sustainable Water …, 2024‏ - Springer
The growing population and the rise in urbanization have made managing water a critical
concern around the world in recent years. Globally, flooding is one of the most devastating …

Spectral-temporal convolutional approach for PV systems output power forecasting: Case studies in single-site and multi-site

T Nguyen-Duc, T Nguyen-Trong… - … Energy, Grids and …, 2024‏ - Elsevier
Accurate predictions of photovoltaic (PV) and wind power outputs are indispensable for
integrating additional renewable energy sources into the grid. Photovoltaic energy is …