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An ensemble framework for short-term load forecasting based on parallel CNN and GRU with improved ResNet
H Hua, M Liu, Y Li, S Deng, Q Wang - Electric Power Systems Research, 2023 - Elsevier
Accurate and efficient load forecasting is of great significance for stable operation and
scheduling of modern power systems. However, load data are usually nonlinear and non …
scheduling of modern power systems. However, load data are usually nonlinear and non …
Residual LSTM based short-term load forecasting
As the modern energy systems is becoming more complex and flexible, accurate load
forecasting has been the key to scheduling power to meet customers' needs, load switching …
forecasting has been the key to scheduling power to meet customers' needs, load switching …
An ensemble framework for short-term load forecasting based on timesnet and tcn
C Zuo, J Wang, M Liu, S Deng, Q Wang - Energies, 2023 - mdpi.com
Accurate and efficient short-term power load forecasting is crucial for ensuring the stable
operation of power systems and rational planning of electricity resources. However, power …
operation of power systems and rational planning of electricity resources. However, power …
Research review of the knowledge graph and its application in power system dispatching and operation
With the construction of a new power system and the proposal of a double carbon goal,
power system operation data are growing explosively, and the optimization of power system …
power system operation data are growing explosively, and the optimization of power system …
Combining fuzzy clustering and improved long short-term memory neural networks for short-term load forecasting
Short-term load forecasting (STLF) is a critical component of smart grid operations, yet it is a
challenging task due to the high uncertainty of electrical loads. This paper proposes a novel …
challenging task due to the high uncertainty of electrical loads. This paper proposes a novel …
Electricity demand error corrections with attention bi-directional neural networks
Reliable forecast of electricity demand is crucial to stability, supply, and management of
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
Short term electric power load forecasting using principal component analysis and recurrent neural networks
Electrical load forecasting study is required in electric power systems for different
applications with respect to the specific time horizon, such as optimal operations, grid …
applications with respect to the specific time horizon, such as optimal operations, grid …
A novel residual gated recurrent unit framework for runoff forecasting
Runoff forecasting is the key to the rational use and protection of water resources by
mankind. The large-scale application of machine learning and neural networks in …
mankind. The large-scale application of machine learning and neural networks in …
Lake water body extraction of optical remote sensing images based on semantic segmentation
Automatically extract lake water bodies of optical remote sensing images is a very
challenging task, because there are many small lakes in such images, these small lakes …
challenging task, because there are many small lakes in such images, these small lakes …
A parallel short-term power load forecasting method considering high-level elastic loads
J Dong, L Luo, Y Lu, Q Zhang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article proposes an electric load forecasting model for systems containing high-level
elastic loads. The model consists of three structures: a one-dimensional (1-D) convolutional …
elastic loads. The model consists of three structures: a one-dimensional (1-D) convolutional …