Results 11 to 20 of about 649,385 (296)

Short term power load forecasting based on BES-VMD and CNN-Bi-LSTM method with error correction

Frontiers in Energy Research, 2023
Aiming at the strong non-linear and non-stationary characteristics of power load, a short-term power load forecasting method based on bald eagle search (BES) optimization variational mode decomposition (VMD), convolutional bi-directional long short-term ...
Nier Wang, Zhanming Li
semanticscholar   +1 more source

Power-Load Forecasting Model Based on Informer and Its Application

Energies, 2023
Worldwide, the demand for power load forecasting is increasing. A multi-step power-load forecasting model is established based on Informer, which takes the historical load data as the input to realize the prediction of the power load in the future.
Hongbin Xu, Qiang Peng, Yuhao Wang, Zengwen Zhan   +3 more
semanticscholar   +1 more source

Ultra Short-Term Power Load Forecasting Based on Similar Day Clustering and Ensemble Empirical Mode Decomposition

Energies, 2023
With the increasing demand of the power industry for load forecasting, improving the accuracy of power load forecasting has become increasingly important.
Wenhui Zeng, Jiarui Li, Changchun Sun, Lin Cao, Xiaoping Tang, Shaolong Shu, Junsheng Zheng   +6 more
semanticscholar   +1 more source

Short-Term Power Load Forecasting Based on VMD-Pyraformer-Adan

IEEE Access, 2023
For the characteristics of fluctuation, periodicity and nonlinearity of power load data, this paper proposes a short-term power load forecasting model based on VMD-Pyraformer-Adan.
Yihao Tang, Huafeng Cai
semanticscholar   +1 more source

Short-Term Power Load Forecasting: An Integrated Approach Utilizing Variational Mode Decomposition and TCN–BiGRU

Energies, 2023
Accurate short-term power load forecasting is crucial to maintaining a balance between energy supply and demand, thus minimizing operational costs. However, the intrinsic uncertainty and non-linearity of load data substantially impact the accuracy of ...
Zhuoqun Zou, Jing Wang, Ning E, Can Zhang, Zhaocai Wang, Enyu Jiang   +5 more
semanticscholar   +1 more source

Short Term Electric Power Load Forecasting Using Principal Component Analysis and Recurrent Neural Networks

Forecasting, 2022
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 stability, Demand Side Management (DSM) and long-term strategic planning.
V. Veeramsetty, D. R. Chandra, F. Grimaccia, M. Mussetta   +3 more
semanticscholar   +1 more source

Advanced Methods of Power Load Forecasting

, 2022
openaire   +2 more sources

A hybrid temporal convolutional network and Prophet model for power load forecasting

Complex & Intelligent Systems, 2022
Accurate and effective power system load forecasting is an important prerequisite for the safe and stable operation of the power grid and the normal production and operation of society.
Jinyuan Mo, Rui Wang, M. Cao, Kang Yang, Xu Yang, Tao Zhang   +5 more
semanticscholar   +1 more source

Short-term load forecasting of power system [PDF]

AIP Conference Proceedings, 2017
In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development
  +6 more sources

Analysis load forecasting of power system using fuzzy logic and artificial neural network [PDF]

, 2017
Load forecasting is a vital element in the energy management of function and execution purpose throughout the energy power system. Power systems problems are complicated to solve because power systems are huge complex graphically widely distributed and ...
A Mostafa, Salama, F. Al-dolaimy, F. Al-dolaimy, Hashim Abbas, Fatima, Jubair, Mohammed Ahmed, Muhi Hariz, Hussein, Noor Nabeel, Noor Nabeel, Rabei Raad Al, Rabei Raad Al, Wisam Subhi Al-Dayyeni4, Wisam Subhi Al-Dayyeni4   +7 more
core   +1 more source