Load Frequency Control (LFC) of a Microgrid using PSCAD/EMTDC Simulation Program

Üney, Mehmet; Karaman, Ömer Ali

doi:10.54365/adyumbd.939716

Cited by 1 publication

(1 citation statement)

References 27 publications

(33 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Time series analysis has been successfully applied in many fields, such as construction [24], transportation systems [25], and energy forecasting [26]. Output power forecasting is valuable information for the continuous support of power grids [27]. A highly accurate forecasting model with a suitable performance curve provided by the manufacturer can help renewable-based power grids operate efficiently and safely [28].…”

Section: Article Info Abstractmentioning

confidence: 99%

Multilayer LSTM Model for Wind Power Estimation in the Scada System

ÇELEBİ,

KARAMAN

2023

EJT

View full text Add to dashboard Cite

Wind energy is clean energy that does not pollute the environment. However, the complex and variable operating environment of a wind turbine often makes it difficult to predict the instantaneous active power generated. In this study, a wind turbine active power estimation system based on a short-term memory network (LSTM) using time series analysis is proposed. The data obtained from the wind turbine SCADA system is used as input variables. In the proposed method, a multilayer LSTM architecture is designed to train the model. The first LSTM network consists of 64 units, and the second one consists of 32 units. This is followed by a dense layer consisting of 16 neurons. In the last layer, the architecture is finalized by using a linear activation function for the prediction process. The proposed deep learning (DL)-based LSTM prediction model takes into account environmental factors such as wind speed and wind direction for active power forecasting. The results show that the LSTM-based time series analysis method is capable of effectively capturing time series features among the data. Thus, the proposed architecture can realize high-accuracy active power forecasting.

show abstract