Smart grid (SG) is considered a form of intelligent system that allows the electric grid to perform its functions efficiently. The SG is a network that allows for the flow of electrical energy and data, where the data is used to make intelligent decisions in the operation of the electric grid. Artificial intelligence (AI) techniques, such as expert system (ES), Machine Learning (ML), and deep Learning (DL) have brought an advancing frontier in power electronics and power engineering with their powerful data processing capabilities. The SG relies on the flow of data to make its intelligent control; therefore, AI technology is a perfect fit for the SG. The application of AI technology in the SG has the potential to improve the intelligence of the SG.
This research topic is focused on ways of improving the data analysis and control of SG by leveraging technologies. Manuscripts with the progress made in solving a range of miscellaneous and critical problems in SG by leveraging AI methods such as ES, ML, and DL methods are welcome. Reviews and original research that describe the latest developments in this field are considered for publication in this research topic.
The scope of this Research Topic will include the following themes, but are not limited to:
1. Data-driven and artificial intelligence approaches to enhancing flexibility and resilience of SG.
2. Expert system, Machine Learning and Deep Learning, reinforcement learning and transfer learning for applications in SG.
3. AI for development in ensuring high reliability and stability of electric power system with high penetration of renewable energy.
4. AI for studies in operation protection, integrated planning, and control of SG systems.
5. AI for development in diagnostics and diagnostics for SG.
6. Health monitoring of a modern wind generation system using an adaptive neuro-fuzzy system.
7. Space vector fault pattern identification of a smart grid subsystem by neural mapping.
8. Control techniques, mathematical programming methods, optimization techniques and metaheuristics applied in SG.
9. AI and optimization techniques for green energy and carbon footprint.
10. Novel applications of AI-based smart grids in smart cities, smart transportation, smart healthcare, and smart manufacturing.
Smart grid (SG) is considered a form of intelligent system that allows the electric grid to perform its functions efficiently. The SG is a network that allows for the flow of electrical energy and data, where the data is used to make intelligent decisions in the operation of the electric grid. Artificial intelligence (AI) techniques, such as expert system (ES), Machine Learning (ML), and deep Learning (DL) have brought an advancing frontier in power electronics and power engineering with their powerful data processing capabilities. The SG relies on the flow of data to make its intelligent control; therefore, AI technology is a perfect fit for the SG. The application of AI technology in the SG has the potential to improve the intelligence of the SG.
This research topic is focused on ways of improving the data analysis and control of SG by leveraging technologies. Manuscripts with the progress made in solving a range of miscellaneous and critical problems in SG by leveraging AI methods such as ES, ML, and DL methods are welcome. Reviews and original research that describe the latest developments in this field are considered for publication in this research topic.
The scope of this Research Topic will include the following themes, but are not limited to:
1. Data-driven and artificial intelligence approaches to enhancing flexibility and resilience of SG.
2. Expert system, Machine Learning and Deep Learning, reinforcement learning and transfer learning for applications in SG.
3. AI for development in ensuring high reliability and stability of electric power system with high penetration of renewable energy.
4. AI for studies in operation protection, integrated planning, and control of SG systems.
5. AI for development in diagnostics and diagnostics for SG.
6. Health monitoring of a modern wind generation system using an adaptive neuro-fuzzy system.
7. Space vector fault pattern identification of a smart grid subsystem by neural mapping.
8. Control techniques, mathematical programming methods, optimization techniques and metaheuristics applied in SG.
9. AI and optimization techniques for green energy and carbon footprint.
10. Novel applications of AI-based smart grids in smart cities, smart transportation, smart healthcare, and smart manufacturing.
