Program of Graduate Studies | Smart Grid Energy Systems |
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Semester | Semester 2 – Spring |
Type | Elective |
ECTS | 7,5 |
Weekly Teaching Hours | 3 |
Course Site | https://eclass.uth.gr/courses/E-CE_P_106/ |
Course Instructor |
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Scientific Responsible |
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Title | MLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum |
Duration | 2023 – 2025 |
Site | https://csl.e-ce.uth.gr/projects/mlsysops |
Department of Electrical and Computer Engineering | |
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Tel. | +30 24210 74967, +30 24210 74934 |
gece ΑΤ e-ce.uth.gr | |
PGS Tel. | +30 24210 74933 |
PGS e-mail | pgsec ΑΤ e-ce.uth.gr |
URL | https://www.e-ce.uth.gr/contact-info/?lang=en |
Program of Graduate Studies | Smart Grid Energy Systems |
---|---|
Semester | Semester 2 – Spring |
Type | Elective |
ECTS | 7,5 |
Weekly Teaching Hours | 3 |
Course Site | https://eclass.uth.gr/courses/E-CE_P_106/ |
Course Instructor |
|
Prospects for the development, design and implementation of smart grids. Smart grid architecture, technology, demand response. Price based energy exchange. Advanced measurement systems and smart devices. Renewable energy sources and their integration in the grid. Microgrids and their importance on the control and stability of power systems. Technologies, Progress and Impact of Integration of Electric Vehicles on the Network, Simulation, monitoring and control of the smart distribution grid. Advanced sensor technology, communication and information technology for the monitoring and control of the grid. Stability assessment of smart grids.