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Energies
Volume 17
Issue 14
10.3390/en17143371
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Review

Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives

by
Maria Ferrara
1,
Matteo Bilardo
1,
Dragos-Ioan Bogatu
2,
Doyun Lee
3,
Mahmood Khatibi
4,
Samira Rahnama
4,
Jun Shinoda
2,
Ying Sun
5,6,
Yongjun Sun
7,
Alireza Afshari
4,
Fariborz Haghighat
6,
Ongun B. Kazanci
2,
Ryozo Ooka
3 and
Enrico Fabrizio
1,*
1
Department of Energy, TEBE Research Group, Politecnico di Torino, 10129 Turin, Italy
2
International Centre for Indoor Environment and Energy—ICIEE, Department of Environmental and Resource Engineering, Technical University of Denmark, Kgs. Lyngby, 2800 Lyngby, Denmark
3
Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan
4
Department of the Built Environment, Aalborg University Copenhagen, 2450 København, Denmark
5
School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266033, China
6
Energy and Environment Group, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada
7
Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong
*
Author to whom correspondence should be addressed.
Energies 2024, 17(14), 3371; https://doi.org/10.3390/en17143371
Submission received: 30 May 2024 / Revised: 21 June 2024 / Accepted: 5 July 2024 / Published: 9 July 2024
(This article belongs to the Section F5: Artificial Intelligence and Smart Energy)
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Abstract

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.
Keywords: thermal storage; energy storage; electric storage; model predictive control; artificial intelligence thermal storage; energy storage; electric storage; model predictive control; artificial intelligence

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MDPI and ACS Style

Ferrara, M.; Bilardo, M.; Bogatu, D.-I.; Lee, D.; Khatibi, M.; Rahnama, S.; Shinoda, J.; Sun, Y.; Sun, Y.; Afshari, A.; et al. Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives. Energies 2024, 17, 3371. https://doi.org/10.3390/en17143371

AMA Style

Ferrara M, Bilardo M, Bogatu D-I, Lee D, Khatibi M, Rahnama S, Shinoda J, Sun Y, Sun Y, Afshari A, et al. Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives. Energies. 2024; 17(14):3371. https://doi.org/10.3390/en17143371

Chicago/Turabian Style

Ferrara, Maria, Matteo Bilardo, Dragos-Ioan Bogatu, Doyun Lee, Mahmood Khatibi, Samira Rahnama, Jun Shinoda, Ying Sun, Yongjun Sun, Alireza Afshari, and et al. 2024. "Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives" Energies 17, no. 14: 3371. https://doi.org/10.3390/en17143371

APA Style

Ferrara, M., Bilardo, M., Bogatu, D.-I., Lee, D., Khatibi, M., Rahnama, S., Shinoda, J., Sun, Y., Sun, Y., Afshari, A., Haghighat, F., Kazanci, O. B., Ooka, R., & Fabrizio, E. (2024). Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives. Energies, 17(14), 3371. https://doi.org/10.3390/en17143371

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