Postdoc in Electrical Power System Intertia Estimation using System Id

As more and more electrical power is produced by renewable and carbon free sources, the electrical power system is undergoing a rapid transformation where the electrical power production is becoming more geographically diverse and intermittent. This progress poses various challanges to the system operators when it comes to network stability and balancing. The level of inertia is one key feature which is important to estimate on-line. In this project you will develop system identification based estimation algorithms which, on-line, provide reliable estimates of the system inertia. Altogether, this position offers an excellent opportunity for fruitful postdoctoral research work in an exciting and expanding field which is of high societal relevance meanwhile being part of a dynamic research environment.

Information about the project
The magnitude of a frequency deviation in the power grid due to a power imbalance is proportional to the inverse of the system inertia. For a transmission system operator (TSO) it is hence important to know the system inertia in order to take the correct measures to guarantee a stable delivery of electric power to the consumers also during significant load imbalances. In a future network with many distributed energy sources it will be necessary to monitor the level of system inertia from measurements as it will vary depending on which generating sources are active and how they are controlled. If the TSO accurately can monitor the level of system inertia based on measurements they can optimize the size of the energy storage needed to keep the system frequency within bounds for present given load. This will result in a robust, more compact and less expensive system.

In this project we aim to approach the system inertia estimation problem by employing recent methods developed in the system identification research community. Hence the research will bridge the gap between advanced system identification theory and electrical power research. We will use measurements of frequency and load differences and employ a multivariate (MIMO) small-signal approach and employ methods from MIMO frequency domain system identification that we have developed previously in the research group. The project will be conducted together with researchers at both the Signal Processing group and the division of Electrical Power Engineering.

Information about the research group
The Signal Processing Group conducts research on a broad range of topics related to the physics-based processing of sensor signals, the fusion of data from multiple sources, system identification as well as the automatic learning from big data. The research focuses on both the fundamentals of physics modeling of signals and the fundamentals of signal processing, as well as the applications of the methods to relevant problems. Several research topics are undertaken in collaboration with the industry and the university hospital.

Information about the department
At the department of Electrical Engineering, research and education are performed in the areas of Communication and Antenna systems, Systems and Control, Computer vision, Signal processing and Biomedical engineering, and Electric Power Engineering. Our knowledge is of use everywhere where there is advanced technology with, e.g., integrated electronics and microwave systems. We work with challenges for a sustainable future in the society of today, for example in the growing demands concerning efficient systems for communications and electrification. We offer a dynamic and international work environment with about 200 employees from more than 20 countries, and with extensive national and international research collaborations with academia, industry and society. The department provides about 100 courses, of which most are included in the Master’s Programs “Biomedical Engineering”, “Electric Power Engineering”, ”Systems, Control and Mechatronics” and ”Communication Engineering”.

Major responsibilities
Your major responsibilities are to pursue your own postdoc work within the project. You are expected to develop your own scientific concepts and communicate the results of your research verbally and in writing.

Position summary
Full-time temporary employment. The position is limited to a maximum of two years. 

Qualifications
To qualify as a postdoc, you must have a PhD-degree in the field of System Identification, Signal Processing or Estimation.

Candidates should be interested in pursuing theoretical research in an international environment. The position requires sound verbal and written communication skills in English.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

Our offer to you
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees.

Application procedure
For more information and to apply, please go to this webpage

Application deadline: 31 December, 2020

For questions, please contact:
Tomas McKelvey, tomas.mckelvey@chalmers.se, +46 31 772 8061


*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***