Applications of Deep Machine Learning in Future Energy Systems

1. Introduction<br>2. Artificial intelligence and Machine learning in Future Energy Systems (State-of-Art, future development)<br>Jalal Heidary<br>3. Digital Twins-Assisted Design of Next-Generation DC Microgrid<br>Meysam Gheisarnejad, Maryam Homayounzadeh, Burak Yildirim<br>4. Deep Learning-Based Procedure for Profit Maximization of EV Charging Stations<br>Mohammad Hassan Khooban, Peyman Razmi, MASOUMEH SEYEDYAZDI<br>5. Deep Frequency Control of Power Grids Under Cyber Attacks<br>Mohammad Aghamohammadi, jalal heidary, Soroush Oshnoei<br>6. Application of Q-Learning in Stabilization of Multi Carrier Energy Systems<br>Meysam Gheisarnejad, Maryam Homayounzadeh, Burak Yildirim<br>7. Design of Next-Generation of 5G Data Center Power Supply based on AI<br>Mohammad Hassan Khooban, Meysam Gheisarnejad<br>8. Smart EV Battery Charger Based on Deep Machine Learning<br>Mohammad Hassan Khooban, Jalil Boudjadar, Mehdi Rafiei<br>9. Machine learning in Talkative Power<br>Mohammad Hassan Khooban, Zahra Ghahraman Izadi, Ali Mousavi<br>10. Advanced Control of Power Electronics-based Machine Learning<br>Maryam Homayounzadeh, Meysam Gheisarnejad, Mohamadreza Homayounzade, Mohammad Hassan Khooban<br>11. Multi-Level Energy Management and Optimal Control System in Smart Cities Based on Deep Machine Learning<br>Javid Ghafourian, Atefe Hedayatnia, Ahmed Al-Durra, Reza Sepehrzad