Hybrid structures in time series modeling and forecasting: A review
Z Hajirahimi, M Khashei - Engineering Applications of Artificial Intelligence, 2019 - Elsevier
The key factor in selecting appropriate forecasting model is accuracy. Given the deficiencies
of single models in processing various patterns and relationships latent in data, hybrid …
of single models in processing various patterns and relationships latent in data, hybrid …
A survey on hyperparameters optimization algorithms of forecasting models in smart grid
Forecasting in the smart grid (SG) plays a vital role in maintaining the balance between
demand and supply of electricity, efficient energy management, better planning of energy …
demand and supply of electricity, efficient energy management, better planning of energy …
Hybrid VMD-CNN-GRU-based model for short-term forecasting of wind power considering spatio-temporal features
Z Zhao, S Yun, L Jia, J Guo, Y Meng, N He, X Li… - … Applications of Artificial …, 2023 - Elsevier
Accurate and reliable short-term forecasting of wind power is vital for balancing energy and
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …
Residential load forecasting based on LSTM fusing self-attention mechanism with pooling
Day-ahead residential load forecasting is crucial for electricity dispatch and demand
response in power systems. Electrical loads are characterized by volatility and uncertainty …
response in power systems. Electrical loads are characterized by volatility and uncertainty …
Short term electricity load forecasting using a hybrid model
J Zhang, YM Wei, D Li, Z Tan, J Zhou - Energy, 2018 - Elsevier
Short term electricity load forecasting is one of the most important issue for all market
participants. Short term electricity load is affected by natural and social factors, which makes …
participants. Short term electricity load is affected by natural and social factors, which makes …
A deep model for short-term load forecasting applying a stacked autoencoder based on LSTM supported by a multi-stage attention mechanism
Z Fazlipour, E Mashhour, M Joorabian - Applied Energy, 2022 - Elsevier
This paper presents an innovative univariate Deep LSTM-based Stacked Autoencoder
(DLSTM-SAE) model for short-term load forecasting, equipped with a Multi-Stage Attention …
(DLSTM-SAE) model for short-term load forecasting, equipped with a Multi-Stage Attention …
A novel two-stage forecasting model based on error factor and ensemble method for multi-step wind power forecasting
Y Hao, C Tian - Applied energy, 2019 - Elsevier
With the fast growth of wind power penetration into the electric grid, wind power forecasting
plays an increasingly significant role in the secure and economic operation of power …
plays an increasingly significant role in the secure and economic operation of power …
A seasonal GM (1, 1) model for forecasting the electricity consumption of the primary economic sectors
ZX Wang, Q Li, LL Pei - Energy, 2018 - Elsevier
To accurately predict the seasonal fluctuations of the electricity consumption of the primary
economic sectors, we propose a seasonal grey model (SGM (1, 1) model) based on the …
economic sectors, we propose a seasonal grey model (SGM (1, 1) model) based on the …
Short-term electric load forecasting based on singular spectrum analysis and support vector machine optimized by Cuckoo search algorithm
X Zhang, J Wang, K Zhang - Electric Power Systems Research, 2017 - Elsevier
Short-term electric load forecasting (STLF) has been one of the most active areas of
research because of its vital role in planning and operation of power systems. Additionally …
research because of its vital role in planning and operation of power systems. Additionally …
A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting
J Song, J Wang, H Lu - Applied energy, 2018 - Elsevier
Short-term wind speed forecasting has a significant influence on enhancing the operation
efficiency and increasing the economic benefits of wind power generation systems. A …
efficiency and increasing the economic benefits of wind power generation systems. A …