Recurrent Neural-Network-Based Maximum Frequency Deviation Prediction Using Probability Power Flow Dynamic Tool

Recurrent Neural-Network-Based Maximum Frequency Deviation Prediction Using Probability Power Flow Dynamic Tool

This paper proposes a recurrent neural network (RNN)-based maximum frequency deviation forecasting model for power systems with high photovoltaic power (PV) penetration. The proposed RNN model extracts the nonlinear features and invariant structures exhibited in regional PV power output data and tim...

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Bibliographic Details
Main Authors: Sungyoon Song, Yoongun Jung, Changhee Han, Seungmin Jung, Minhan Yoon, Gilsoo Jang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
RNN
frequency stability
probability power flow
randomness
Online Access:https://ieeexplore.ieee.org/document/9212358/

Internet

https://ieeexplore.ieee.org/document/9212358/

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