Energy Management Systems Based on Industrial Artificial Intelligence

Dear Colleague,

Artificial intelligence (AI) has dramatically altered the dynamic landscape of science and industry in the past several years. Industrial AI (IAI), defined as “ a systematic discipline, which focuses on developing, validating, and deploying various machine learning algorithms for industrial applications with sustainable performance,” can power the sustainable performance of energy management systems (EMSs) and the critical aspect of optimizing energy distribution. IAI can actualize smart and resilient industrial EMSs that are fault-tolerant, self-organizing, and can predict potential breakdowns in critical energy infrastructure. IAI focuses on developing EMSs for the management of renewable energy in smart grids and the challenge of managing the additional load on grids due to electric vehicles (EVs).

This Special Issue aims to present recent and high-quality research on the development of AI techniques, such as optimized solutions, industrial data modeling, and control, for improving industrial EMSs and building EMSs (BEMSs).

Topics of interest for publication include, but are not limited to, the following:

• IAI in demand-side management (DSM)
• IAI in building energy management system (BEMS)
• IAI and IoT energy management systems
• Forecast energy demand by AI
• Identify inefficiencies in EMS by AI
• Energy optimization by AI
• IAI in renewable energy systems
• IAI in energy hubs and microgrids
• IAI in smart grids
• IAI in smart cities
• IAI for sustainable EMS
• Energy trading with AI
• Prediction of renewable energy by AI
• Estimation of occupancy in buildings by AI
• IAI in electric vehicles
• Fuzzy logic energy management system
• Decision methods in EMS with AI 

Prof. Dr. Anastasios Dounis
Prof. Dr. George Papadakis
Guest Editors

Manuscript Submission Information

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