Research Areas
Biography and Research Information
OverviewAI-generated summary
Saikot Hossain Dadon's research focuses on power systems, particularly concerning the integration of renewable energy sources and the optimization of microgrid operations. His work investigates strategies for managing power system flexibility in scenarios with high renewable energy penetration. Dadon has explored the application of machine learning, specifically deep-Q-learning, for optimizing energy purchases within microgrid systems. Additionally, his research has addressed the scheduling of electric vehicle charging in solar-wind powered microgrids, also utilizing machine learning techniques. He has collaborated with researchers from Arkansas State University on shared publications, including Md Mahmudul Hasan, Motinur Rahman, and Yagub Suleymanov. Dadon's publication record includes work on power system flexibility and microgrid energy management, with his most recent publication dating to 2025. He has a cited h-index of 2 and a total of 4 publications.
Metrics
- h-index: 2
- Publications: 4
- Citations: 66
Selected Publications
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Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning (2025)
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Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393 (2025)
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Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning (2024)
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An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios (2024)
Collaboration Network
Top Collaborators
- An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios
- Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning
- Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393
- An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios
- Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393
- An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios
- Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393
- An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios
- Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393
- Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning
- Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning
- Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning
- Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning
- Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning
- Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning
- Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning
- Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning
- Energy Purchase Optimization for Microgrid Systems Using Deep-Q-Learning
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