Program of Graduate Studies | Smart Grid Energy Systems |
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Semester | Semester 1 – Fall |
Type | Required |
ECTS | 7,5 |
Weekly Teaching Hours | 3 |
Course Site | https://eclass.uth.gr/courses/E-CE_P_103/ |
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 1 – Fall |
Type | Required |
ECTS | 7,5 |
Weekly Teaching Hours | 3 |
Course Site | https://eclass.uth.gr/courses/E-CE_P_103/ |
Course Instructor |
|
Fundamental technologies for distributed energy generation using conventional and non conventional fuel. Units for power co-generation, internal combustion engines, microturbines and fuel cells. Renewable energy sources, energy storage systems. Autonomous and hybrid systems. Economic, Environmental and operational factors of distributed generation. Power Quality of distributed energy generation. Connectedness of distributed generation units to distribution networks. Influence of distributed generation on the design and operation on the generation, transmission and distribution power networks. Microgrids and smart grids.