CL-Net: ConvLSTM-Based Hybrid Architecture for Batteries’ State of Health and Power Consumption Forecasting

CL-Net: ConvLSTM-Based Hybrid Architecture for Batteries’ State of Health and Power Consumption Forecasting

Traditional power generating technologies rely on fossil fuels, which contribute to worldwide environmental issues such as global warming and climate change. As a result, renewable energy sources (RESs) are used for power generation where battery energy storage systems (BESSs) are widely used to sto...

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Bibliographic Details
Main Authors: Noman Khan, Ijaz Ul Haq, Fath U Min Ullah, Samee Ullah Khan, Mi Young Lee
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Mathematics
Subjects:
batteries
deep learning
energy storage system
lithium-ion
machine learning
power consumption
Online Access:https://www.mdpi.com/2227-7390/9/24/3326

Internet

https://www.mdpi.com/2227-7390/9/24/3326

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