Prediction of Wind Turbine-Grid Interaction Based on a Principal Component Analysis-Long Short Term Memory Model
The interaction between the gird and wind farms has significant impact on the power grid, therefore prediction of the interaction between gird and wind farms is of great significance. In this paper, a wind turbine-gird interaction prediction model based on long short term memory (LSTM) network under...
Main Authors: | Yining Wang, Da Xie, Xitian Wang, Yu Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-11-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/11/11/3221 |
Similar Items
-
Study on grid adaptability testing methodology for wind turbines
by: Shaolin Li, et al.
Published: (2013-01-01) -
Different options for multi-rotor wind turbine grid connection
by: Kamyab Givaki
Published: (2019-04-01) -
A Novel Condition Monitoring Method of Wind Turbines Based on Long Short-Term Memory Neural Network
by: Peng Qian, et al.
Published: (2019-09-01) -
Wind Resources Assessment and Development of Grid Connected Wind Farm—A Case Study
by: Ming-Hong Chen, et al.
Published: (2020-10-01) -
Deep Learning-Based Prediction of Wind Power for Multi-turbines in a Wind Farm
by: Xiaojiao Chen, et al.
Published: (2021-07-01)