Data Analytics and Information Technologies for Smart Energy Storage Systems: A State-of-the-Art Review

被引：11

作者：

Nasiri, Fuzhan ^{[1
]}

Ooka, Ryozo ^{[2
]}

Haghighat, Fariborz ^{[1
]}

Shirzadi, Navid ^{[1
]}

Dotoli, Mariagrazia ^{[3
]}

Carli, Raffaele ^{[3
]}

Scarabaggio, Paolo ^{[3
]}

Behzadi, Amirmohammad ^{[4
]}

Rahnama, Samira ^{[5
]}

Afshari, Alireza ^{[5
]}

Kuznik, Frederic ^{[6
]}

Fabrizio, Enrico ^{[7
]}

Choudhary, Ruchi ^{[8
]}

Sadrizadeh, Sasan ^{[4
]}

机构：

[1] Concordia Univ, Dept Bldg Civil & Environm Engn, Montreal, PQ, Canada

[2] Univ Tokyo, Inst Ind Sci, Tokyo, Japan

[3] Politecn Bari, Dept Elect & Informat Engn, Bari, Italy

[4] KTH Royal Inst Technol, Dept Civil & Architectural Engn, Stockholm, Sweden

[5] Aalborg Univ, Dept Built Environm, Copenhagen, Denmark

[6] Inst Natl Sci Appl Lyon INSA Lyon, Lyon, France

[7] Politecn Torino, DOE, Turin, Italy

[8] Univ Cambridge, Engn Dept, Cambridge, England

来源：

SUSTAINABLE CITIES AND SOCIETY | 2022年 / 84卷

基金：

英国工程与自然科学研究理事会;

关键词：

Energy Storage; Smart Systems; Artificial Intelligence; Renewable Energy Intermittency; Data Analytics; Information Technology; LITHIUM-ION BATTERIES; EXTENDED KALMAN FILTER; LIFE-CYCLE ASSESSMENT; CIRCUIT VOLTAGE HYSTERESIS; CHARGE ESTIMATION; NEURAL-NETWORK; POLYMER BATTERIES; MANAGEMENT-SYSTEM; BUILDING ENERGY; VECTOR MACHINE;

D O I：

10.1016/j.scs.2022.104004

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This article provides a state-of-the-art review on emerging applications of smart tools such as data analytics and smart technologies such as internet-of-things in case of design, management and control of energy storage systems. In particular, we have established a classification of the types and targets of various predictive analytics for estimation of load, energy prices, renewable energy inputs, state of the charge, fault diagnosis, etc. In addition, the applications of information technologies, and in particular, use of cloud, internet-of-things, building management systems and building information modeling and their contributions to management of energy storage systems will be reviewed in details. The paper concludes by highlighting the emerging issues in smart energy storage systems and providing directions for future research.

引用

页数：14

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