Applications of Artificial Intelligence (AI) in Energy Storage Systems Design, Operation and Control
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1131
Special Issue Editors
Interests: energy systems engineering; facility management and maintenance; infrastructure management; sustainable cities; communities and buildings
Special Issues, Collections and Topics in MDPI journals
Interests: urban and building energy system; urban environment; renewable energy
Interests: indoor environment; ventilation; filtration; materials; high-performance green buildings; urban ventilation and outdoor environment; GHG
Interests: simulation-based optimization methodologies for energy management of buildings; ventilation design strategies; integration of novel building technologies and renewable energy supply systems during design phases; performance assessment of buildings
Interests: renewable energy technologies; energy conversion; energy engineering; energy saving; numerical modeling; thermal engineering; engineering thermodynamics; energy efficiency in building; energy; computational fluid dynamics
Interests: manufacturing systems; modeling; optimization; logistics; petri nets; fuzzy systems; discrete event systems; automation; systems theory; automatic control
Interests: construction; indoor climate; ventilation; particles; demand controlled ventilation
Special Issues, Collections and Topics in MDPI journals
Interests: sustainable building; low carbon architecture; energy efficiency in buildings
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Energy storage systems (ESSs) are receiving growing attention as main stream solutions for the widespread use of renewable energies and subsequently as a means of decarbonizing the electrification of society. At the building scale, they are increasingly utilized to enhance heat and cooling energy recovery, promote distributed energy supply and improve the efficiency of cities in reducing their peak demands by helping the utility companies to maintain reliable and resilient generation and distribution capacities. As energy storage systems are well-positioned to bridge the inputs from renewable and recovered energies with the energy demand across varied scales, geographies, and times, there is a pressing need to expand the research in systems’ modeling and analysis of energy storage technologies and their applications. This is of particular importance due to the various types of energy storage technologies in varied sizes and scales, and their diverse operational characteristics and challenges with respect to efficiency and reliability. In doing so, artificial intelligence provides an opportunity to better adapt energy storage systems with changing environmental conditions, dynamic characteristics of the grid, intermittent nature of renewables, thus improving the reliability and resilience of these systems. AI is widely applied in the sizing, scheduling, control, and optimization of energy systems. This Special Issue intends to collect and disseminate the state of the art on research and practice in applications of AI in modeling and analysis of energy storage systems with a focus on the following (and other closely related) topics:
- Energy supply predictions for integration of renewable energies and ESSs;
- Energy demand and critical load predictions for ESSs control and operation;
- Capacity planning and sizing of ESSs;
- Optimized scheduling of ESSs;
- Monitoring and control of ESSs;
- Fault detection, diagnosis, and reliability analysis for ESSs;
- Distributed management of ESSs;
- Data analytics for life cycle analysis of ESSs;
- Location-specific systems analysis for ESSs.
Dr. Fuzhan Nasiri
Prof. Dr. Ryozo Ooka
Prof. Dr. Fariborz Haghighat
prof. Dr. Ruchi Choudhary
Prof. Dr. Frédéric Kuznik
Prof. Dr. Mariagrazia Dotoli
Prof. Dr. Alireza Afshari
Dr. Enrico Fabrizio
Guest Editors
Manuscript Submission Information
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Keywords
- energy storage systems (ESSs)
- energy supply predictions for integration of renewable energies and ESSs
- energy demand and critical load predictions for ESSs control and operation
- capacity planning and sizing of ESSs
- optimized scheduling of ESSs
- monitoring and control of ESSs
- fault detection, diagnosis, and reliability analysis for ESSs
- distributed management of ESSs
- data analytics for life cycle analysis of ESSs
- location-specific systems analysis for ESSs
