 Location: Glasgow, UK
 Duration of the internship: 10-12 weeks
 Starting date: Flexible, likely around beginning of June
 Working pattern: Generally 9-5, 5 days a week, but flexibility is offered

Game Changers is going international! This project offers an exciting opportunity to be a part of the first international collaborative Game Changers research project. Three research interns will be hired to work together, tackling real world data-driven wind energy challenges, with each student based at a different partner university. Interns will be expertly supported by their host institution to drive their particular contribution to this work. Partners in this work are Cubico Sustainable Investments, the Wind Energy Innovation Division of the Eastern Switzerland University of Applied Sciences (OST), and Texas A&M University (TAMU). Strathclyde’s intern on this project will take on the role of wind energy knowledge-lead.

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Background and motivation: The digital transformation is one of the key drivers for reducing costs and risks of wind energy. A lack of data and knowledge sharing is one of the largest barriers to a successful digital transformation of wind energy. WeDoWind is seeking to take away the fear associated with data and knowledge sharing – and foster collaborative mind-sets in wind energy! This will ultimately help the world reach its ambitious net zero goals. The WeDoWind is a method for solving the most pressing problems collaboratively based on setting “challenges” and using data provided by the industry, providing both challenge providers and solution developers with added value and access to what they need. Cubico has recently published two sets of open wind farm SCADA data for the wind farms Kelmarsh and Penmanshiel. Several WeDoWind Challenges are already running in the WeDoWind Cubico Open Data Exploration (CODE) space. However, Cubico is continuously looking for new and exciting ways to use their data. This collaborative Game Changers project has therefore been developed to mutually benefit both the programme participants (the interns) and the challenge provider (Cubico Sustainable Investments). The interns will have the opportunity to work closely with experts at their host institutions, have access to real world turbine data, and will actively contribute to important ongoing research. In return, Cubico will be provided with a wide range of interesting and useful inputs and solutions to their problem(s).

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What will you do? In order to allow for free and open innovation, the parameters of this work have been left up to the interns. The first task of the assembled research team will therefore be to explore the available data, seek to understand Cubico’s needs and requirements and then, supported by their expert supervisory teams, identify the specific problem that will be tackled, and the outcomes which will be sought. The research interns contributing to this work will tackle the problem collectively, but, each will have a different role which reflects the expertise available at their host institution. Strathclyde’s intern will take on the role of wind energy knowledge-lead, requiring them to drive efforts to understand the practical nature of wind turbine operation and monitoring data, the form that data takes, and the impacts of additional effects such as turbine curtailment events. They will develop this domain knowledge through interactions with wind energy experts at Strathclyde, as well as being supported by a PhD student mentor from the Wind and Marine Energy Systems and Structures CDT. Your role on the overall team will then be to use this contextual knowledge to support how the identified data-driven problem should be best approached given the operational turbine knowledge you develop. For example, this may lead you to suggest that the data be partitioned according to operating region, wind speed etc. OST and TAMU interns will assume knowledge-lead roles related to data driven methods and machine learning. Beyond each team members’ specific role, all interns will contribute to the overall analysis, coding and testing.

Required skills and experience: Candidates should have an interest in renewable energy technology and data-driven analysis. An engineering or relevant STEM background is desirable, ideally with some exposure to wind energy. Proven communication and team working skills are key. Candidates should be comfortable leading information gathering efforts, including eliciting support from third parties where necessary.