Power Systems Research Engineer

Transmission Excellence (TX) is an innovative company that provides simulation software, optimisation software and advisory services to the renewables and power transmission sectors.

Our clients include household-name energy companies such as BP and National Grid. We work alone and in partnership with others to provide integrated services to our clients.

It is expected that over the next 1-2 years the primary role of the selected candidate will be on an industry-funded research project that will combine grid simulation and machine learning technologies to construct “surrogate” software models that can replicate the behaviour of the power electronic converters in wind turbines, solar inverters and HVDC links. This in turn will involve:

· using an electromagnetic transient simulation programme (PSCAD) to create data sets for training, validation and testing,

· using machine learning to train a surrogate model,

· testing the resulting surrogate model,

· converting the surrogate model into a form that can be run within the PSCAD simulation programme (this will require coding in a language such as C),

· testing the surrogate model within a PSCAD simulation of the grid.

TX will be undertaking this project in collaboration with academic staff at the University of Bristol, who will assist the candidate with the machine learning aspects of the project. This means that it is not essential for the selected candidate to have previous experience of machine learning.

The selected candidate will be expected to lead on the electrical aspects of the project. Training in PSCAD will be provided if necessary, but a knowledge of the underlying principles is expected.

A typical day could include:

· researching & understanding the design of the grid and/or the technical operation of power transmission equipment,

· discussing with University of Bristol academic staff how best to design and configure machine learning software,

· writing and documenting machine learning code and/or code to implement the surrogate model within the PSCAD simulation environment,

· testing the surrogate models developed with machine learning,

· evaluating test results and consulting with University of Bristol academic staff on how to modify the model or machine learning process to improve results,

· preparing reports.

At TX we don’t work within the restrictive silos that can be found in larger companies, which makes our work more varied and interesting. The selected candidate must therefore be flexible, and must be willing to help TX respond to immediate client requirements across our businesses and software products.

Requirements:

· A degree in electrical engineering.

· A knowledge of power system modelling techniques.

· Demonstrated ability in computer programming.

· 2-3 years of experience following completion of first degree. This experience must be in a relevant area such as software development or power system analysis. The experience may be acquired in industry or in an academic research role (e.g. a dissertation-only master’s degree or a PhD).

Salary & benefits:

· A £40-50k pa starting salary range (dependent on the extent and relevance of the candidate’s experience).

· Annual salary reviews

· A discretionary bonus of up to 20%

· A 4.5 day week (the office closes at 1pm on Friday)

Closing Date:

1 April 2024

Job Types: Full-time, Permanent

Schedule:

• Monday to Friday

Work Location: In person