AI for Status Monitoring of Utility Scale Batteries

Shunli Wang (Professor, Southwest University of Science and Technology, Sichuan, China),Kailong Liu (Assistant Professor, University of Warwick, Coventry, UK),Yujie Wang (Associate Professor, University of Science and Technology, Department of Automation, China),Daniel-Ioan Stroe (Associate Professor, Aalborg University, AAU Energy, Denmark),Carlos Fernandez (Senior Lecturer, Robert Gordon University, Scotland)

AI for Status Monitoring of Utility Scale Batteries
Format
Hardback
Publisher
Institution of Engineering and Technology
Country
United Kingdom
Published
1 December 2022
Pages
455
ISBN
9781839537387

AI for Status Monitoring of Utility Scale Batteries

Shunli Wang (Professor, Southwest University of Science and Technology, Sichuan, China),Kailong Liu (Assistant Professor, University of Warwick, Coventry, UK),Yujie Wang (Associate Professor, University of Science and Technology, Department of Automation, China),Daniel-Ioan Stroe (Associate Professor, Aalborg University, AAU Energy, Denmark),Carlos Fernandez (Senior Lecturer, Robert Gordon University, Scotland)

Batteries are a necessary part of a low-emission energy system, as they can store renewable electricity and assist the grid. Utility-scale batteries, with capacities of several to hundreds of MWh, are particularly important for condominiums, local grid nodes, and EV charging arrays. However, such batteries are expensive and need to be monitored and managed well to maintain capacity and reliability. Artificial intelligence offers a solution for effective monitoring and management of utility-scale batteries.

This book systematically describes AI-based technologies for battery state estimation and modeling for utility-scale Li-ion batteries. Chapters cover utility-scale lithium-ion battery system characteristics, AI-based equivalent modeling, parameter identification, state of charge estimation, battery parameter estimation, offer samples and case studies for utility-scale battery operation, and conclude with a summary and prospect for AI-based battery status monitoring. The book provides practical references for the design and application of large-scale lithium-ion battery systems.

AI for Status Monitoring of Utility-Scale Batteries is an invaluable resource for researchers in battery R&D, including battery management systems and related power electronics, battery manufacturers, and advanced students.

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