About the position
The Department of Electric Power Engineering at NTNU has a vacancy for a full-time 100% position (3 years) as a PhD candidate within stability of power electronics system in renewable energy integration – “AI-based techniques to understand the underlying mechanism leading to instability in power electronics systems”.
The PhD candidate will work alongside 2-3 other PhD candidates and Postdoc covering different aspects of the same topic. The project is based on a special research grant provided by the Faculty of Information Technology and Electrical Engineering at NTNU.
The prospective candidate will work in the research group Power Electronic Systems and Components (PESC),
The main supervisor of the PhD candidate will be Associate Professor Mohammad Amin.
You will report to the head of Department.
Duties of the position
The objective of the PhD education is to qualify for scientific research of high international standard. The PhD education has a nominal duration of three years of full-time study and includes required coursework or similar academic training comprising a minimum of 30 credits. The most important component of the PhD education is an independent scientific research project carried out under academic supervision, which results in the PhD thesis. The PhD degree is conferred based on these two elements and the doctoral examination, which consists of a trial lecture and a public defense of the scientific thesis.
The candidate is expected to fully complete the course work and the PhD thesis within the period of employment, which could be 3 or 4 years. The doctoral examination may take place after the period of employment. The option of 4-year employment would imply 1 year of duties as Teaching Assistant for the Department and may be offered to a candidate with clear motivation and ability for such work, if the Department sees the need. This will be clarified during and after any interview.
The future distribution grids will be much more dynamic than they are today. The key drivers for this are the distributed generation (DG) largely driven by power electronics-based advanced technology adoption of intermittent renewable energy sources (RES) such as solar and wind energy as well as the energy storage system (ESS), and highly dynamic power electronics loads. These power electronics based DGs are non-linear in nature and require to operate in a non-sinusoidal and unbalanced regime. Therefore, the effective application of this technology depends on the appropriate modelling and analysis, control design, and successful implementation of the control algorithm of the power electronics converter (PEC). Due to the complexity of these PEC-based interconnections, different instability and interaction phenomena such as sub-synchronous oscillation, harmonic pollution, unplanned shut-down have been experienced in the electric power system. If these electrical oscillations are sustained or underdamped, they can introduce a serious problem to the grid and subsequently lead to grid failure.
AI-techniques, such as artificial neural network, expert system, and genetic algorithm draw significant attention in the power community for advancing its applications in the modern power system. The goal of this PhD project is to apply the AI-technique to predict the stability of grid-connected power electronics based RES system. The project will develop AI-based solutions to understand the underlying mechanism leading to instability resulting from the interaction between the RES inverter control algorithm and the highly dynamic nonlinear grid. The project will develop the necessary competence to design the control and understand the nonlinear behavior of PEC to remove the critical barrier in the integration of large-scale renewable energy sources. The expected results of the research provide precise conditions and control design guidelines for guaranteeing stability and controllability of these complex and non-linearly coupled network dynamics.
The research work is divided into several tasks to achieve the research goal. First, the stability analysis will be carried out analytically, then the theoretical analysis will be verified in the computer-aided simulation tool and hardware-in-the-loop (HIL) test. After successful implementation in the HIL, the system will be tested in the real hardware in NTNU national smart grid lab.
Required selection criteria
- The candidate should hold a Master’s degree in Electric Power Engineering with a grade of B or better in terms of NTNU’s grading scale.
- Experience and a strong interest in design and control of power electronics are relevant to the chosen task.
- Experience with power electronics lab work and implementation of control method with FPGA or microcontroller development boards, dSPACE or Opal-RT are an advantage.
- Competences in one of the following: Artificial Neural Networks (ANNs), the Genetic Algorithms (GAs) and the Particle Swarm Optimization will be given preference.
- A record of scientific publications in international journals and conferences are merited.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistant
Preferred selection criteria
Applicants must have very good English language skills, written and spoken. Applicants from non-English speaking countries outside EU/EEA/Switzerland must provide preliminary documentation of English language proficiency, in terms of an approved test. The following tests can be used: TOEFL, IELTS and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE).
Further assessment of both written and oral English language skills and the ability to communicate fluently will be conducted in the continued selection process and during any interviews for all applicants.
In the evaluation of the candidates, emphasis will be placed on education, experience and personal suitability, as well as personal motivation for the position, in terms of the qualification requirements specified above. We look for candidates who show clear signs of independence, original thinking and scientific mindset.
Salary and conditions
PhD candidates are remunerated in code 1017, and the salary is NOK 491 200 before tax. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The employment contract is for three years; however, there is a possibility for extension up to four years if selected for assistantship.
Appointment to a PhD position requires admission to the PhD programme in Electrical Power Engineering. Applicants must be qualified for admission as PhD students at NTNU. See https://www.ntnu.edu/ie/research/phd for information about PhD studies at NTNU.
As a PhD candidate, you will have to successfully complete the PhD academic training programme; the training includes mandatory course work and other obligatory activities. Within the first three months of your employment, you must formally qualify for admission to the PhD programme at the Faculty of Information Technology and Electrical Engineering.
The Department of Electric Power Engineering works closely with key players in the Norwegian electricity supply sector, who manage critical infrastructure. A comprehensive risk assessment of the candidates’ research interests and potential activities related to national threat assessments will therefore also form basis for the final selection of candidates.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application must include:
- A cover letter where the applicant describes his/her personal motivation and how he/she intends to fill the position and contributes to the research topic with his/her skills
- A draft research proposal specific to the PhD topic
- Curriculum vitae (CV) which includes information about the candidate’s prior education, work experience, academic merits and any scientific publications.
- Academic work/publication (not master thesis). Joint work will be evaluated. If it is difficult to identify the contributions from individuals in a joint piece of work, applicants should enclose a short descriptive summary of what she/he contributed to the work
- Certified copies of academic diplomas and certificates (both Bachelor and Master).
- Applicants from universities outside Norway are kindly requested to send a diploma supplement or a similar document, which describes in detail the study programme and grading system.
- The required documentation of English language proficiency.
- Names and contact information of at least two references.
Emphasis will be placed on the quality of the cover letter and the ideas and/or originality of the draft research proposal in shortlisting of candidates. Incomplete applications will not be taken into consideration.
In the final assessment of the candidates, strategic considerations at the Department of Electric Power Engineering will also be taken into account. We aim for better gender balance, and when qualifications are approximately equal among qualified candidates, female applicants will be preferred.
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor’s and master’s education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from NOKUT, please attach this as well.
Joint works will be considered. If it is difficult to identify your contribution to joint works, you must attach a brief description of your participation.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment – DORA.
Working at NTNU
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
In accordance with The Public Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.
Questions about the position can be directed to Associate Professor Mohammad Amin, firstname.lastname@example.org
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI).
If you are invited for interview you must include certified copies of transcripts and reference letters. Please refer to the application number 2021/46104 when applying.
Application deadline: 06.10.2021