Energy Systems - Anomaly detection and state estimation
Work description
- Review of the state of the art regarding the application of state estimation algorithms in distribution networks, particularly low-voltage networks. - Study of alternative techniques for analysing and managing distribution networks, particularly those based on automatic learning. - Improvements and error correction of the state estimation tool based on data collected by smart meters. - Improvements to the predictive state estimation functionality. - Implementation of an anomaly identification module. - Identifying and specifying use cases. - Writing technical support documentation.
Minimum profile required
Bachelor's or Master's degree in electrical engineering and computers; informatics; computer science; applied maths; related areas
Preference factors
- Knowledge of electrical distribution networks - Knowledge of machine learning and/or optimisation algorithms. - Experience in software development and APIs. - Fluency in English (written and spoken).
Application Period
Since 03 Oct 2024 to 03 Nov 2024
Centre
Power and Energy Systems