Power system substation asset monitoring and condition analysis in future power systems

Traditionally, the power system asset management is based on interval-based approach and not on actual asset condition. In this PhD project the objective is to thoroughly assess the applicability of existing and alternative measurement options, sensors, IoT and cyber security aspects to enable reliable and usable asset management approaches considering the actual asset condition. This PhD is part of a research and development project between TalTech and Estonian Transmission System Operator.

Description
Power system asset management in current power systems is mostly related to interval-based approach and the actual condition of the asset is not observed nor relevant. This approach in future power system is seen as obsolete as the finances available should be used as much as possible in an appropriate manner.
In view of this, there are two main objectives of this research: 

• First one is to understand current and alternative approaches for substation asset condition monitoring and what are the main influencing factors to increase the observability of asset condition. These include collecting, assessing and making decisions on available assets conditions using the available measurement data but also considering applicability of new sensors technology, IoT and cyber security. Here, the various sensitivities and alternatives shall be determined and as much as possible highlighted considering the limitations in actual power systems. 
• Secondly, to implement probabilistic and risk management theory or some other approach to enable condition based asset management approach in power system. There are various type of information available from the substations and the decisions made shall be based on these. Usually, these include measurements from SCADA, WAMS, environment measurements, etc. In addition, the objective is to develop methodology (including substation based asset condition and component/asset ranking) which combines the available information, assesses the level and content of this data and determine the level and extent of data what is necessary to enable the approach of condition based asset management.

All these aspects shall enable secure, reliable and cost-effective asset life monitoring and management in future power systems including recommendations for appropriate system design enabling the most optimal techno-economical solution for substations. One of the objectives is also to develop comprehensive decision making principles and condition indexes that can be applicable in actual substation maintenance planning. 

Responsibilities and tasks
This is a full time PhD position and student is expected to do research 90% of the time. Other 10% is related to teaching, i.e. supporting lectures and course works in courses related to power system substations and power system optimization. Research results shall be presented through publications and presentations. In minimum, two journal papers and one conference paper shall be published during PhD studies. 

Qualifications
The applicants should fulfill the following requirements:

• Holds a master's degree in Electrical Engineering or Data Analysis/Management (with emphasis on technical assets) or a similar degree with an academic level equivalent to a master's degree
• Have obtained excellent study results and has good knowledge on different mathematical analysis methods (probabilistic and risk assessment theory and methods)
• Have knowledge on power system assets and their operational characteristics
• Have knowledge on power system assets conditon monitoring 
• Have experience with programming languages, e.g. MATLAB
• Is able to understand, speak and write texts in English language with high profiency

Requirements for motivation letter
The motivation letter included to the application shall include information about applicant background, reasoning why she/he is interested in this topic and discussion about the development of this topic.