19M021ESE - Power system state estimation and SCADA
Course specification | ||||
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Course title | Power system state estimation and SCADA | |||
Acronym | 19M021ESE | |||
Study programme | Electrical Engineering and Computing | |||
Module | Applied Mathematics, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering | |||
Type of study | master academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | Exams: Power system analysis | |||
The goal | Introduction to the concepts of state and parameter estimation in power systems, as well as system observability. Familiarization with the fundamentals and functionalities of SCADA systems. | |||
The outcome | Students will be able to: Explain the principles of state estimation and parameter estimation in electric power systems (EPS). Analyze the observability of power systems and understand its significance for reliable system operation. Apply basic methods for implementing state estimators in EPS. Understand the architecture, components, and functions of SCADA systems. | |||
Contents | ||||
Contents of lectures | Introduction to state estimation in power systems (PS) PS modeling for state estimation purposes Basic methods of state estimation Observability of PS Detection and elimination of bad data Introduction to SCADA systems Architecture and components of SCADA systems Integration of SCADA systems with state estimators | |||
Contents of exercises | Modeling of the power system Measurement analysis in power systems Implementation of the least squares method for state estimation Observability analysis of the system based on available measurements Detection and correction of bad data in measurements Visualization and analysis of estimation results Final project | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
2 | 2 | |||
Methods of teaching | Classic lectures and lectures in electronic form (presentation). Practices include classical tasks and problems solving using computer calculations. | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | Test paper | |||
Practical lessons | 20 | Oral examination | 50 | |
Projects | 30 | |||
Colloquia | ||||
Seminars |