Rory Morrison

rmrorymorrison@gmail.com

linkedin.com/in/rory-morrison/

Profile

PhD graduate in Wind Turbine (WT) O&M, with further Lifetime Extension (LTE) and Through-Life Management (TLM) industry experience. PhD: advancing optimisation techniques for improved modelling of offshore WTs. Context of advancing Digital Twins to aid O&M. Recent industry: leading development of company’s LTE & TLM service offerings. Published author in data science, including Machine Learning. Digital Twin theory domain expert. Experienced Renewables Industry professional and Mechanical Engineer.

Career Summary

Xi Engineering Consultants

Edinburgh, UK

Project Engineer, September 2025 – March 2026

  • Lifetime Extension Strategy: Developed the company’s internal approach to LTE and TLM. This included writing a compliance guide for IEC 61400-28 and establishing standard procedures for calculating Remaining Useful Life using both relative and absolute methods. Also experienced with DNV-ST-0262.
  • Asset Assessment: Developed and proposed work packages for a life extension assessment project for 36 turbines over 20 years old. Navigated challenge of maintaining IEC compliance given little documentation.
  • Reliability & Monitoring: Researched wind turbine failure modes and how effectively Condition Monitoring and Structural Health Monitoring systems could detect them, with a focus on supporting reliability-centred maintenance.
  • Data Analysis & Modelling: Led Python-based sub-project to predict noise from high-voltage conductors. This involved data processing and analysis, establishing theory for/performing variable reduction, and building models to predict performance in untested cases.
  • Technical Support: Performed analyses for various smaller projects, including noise and curtailment studies for multi-rotor turbine prototype and virtual prototyping of pressure signal generators. Various other responsibilities including reporting, client support, presentations, conference attendance, and supporting measurement campaigns.

University of Glasgow

Glasgow, UK

PhD Graduate in Science and Engineering, 2020 – 2025

  • Title: Digital Twins for Offshore Wind Turbines: Physics-Based Model Updating for Improved O&M
  • Supervisors: Dr Guanchen Li, Professor Angela Busse.
  • Topic: Thesis explores how Digital Twins (DT) can improve offshore Wind Energy O&M. Research in recalibrating DT models to assets by leveraging operational (SCADA) data. Created optimisation framework to achieve this for Physics-Based Models. This permits remote “virtual inspections”, aiding O&M decision making. Mooring case study employed, showing material characterisation, subsequently improved corrosion and biofouling estimations. Later, developed Anomaly Detection techniques to improve data quality and framework robustness.

Black and Veatch UK

Glasgow, UK

Renewable Energy Engineer, 2018 – 2020

  • Developed project for reducing uncertainties for ship owners/financiers considering fuel-saving technologies. I developed a MATLAB model utilising Monte Carlo Analysis.
  • Performed due diligence on energy yield analyses of 3 wind farms on behalf of the lender. Assisted the principal wind energy consultant in reviewing the reports, including scrutinizing the methods, values, and assumptions used.
  • Ofgem audits: Performed over 30 wind, solar farms, and biomass plants audits on behalf of Ofgem. Additionally, developed tools which aid in the production of these reports.

Ross-Shire Engineering

Cumbernauld, UK

Mechanical Engineer, 2017 – 2018

  • Worked in the design team of a design-and-build firm in the water industry. Diverse workload including pump sizing, determining friction losses throughout water treatment works, FEA, surge analysis, risk assessments and method statements, bespoke part design, feasibility studies.
Education

PhD in Engineering

See "Career Summary" section above.

Masters of Science: Strathclyde University

Renewable Energy Systems and the Environment (Distinction), 2016 - 2017

  • Dissertation: Retrofitting of decommissioned oil and gas platforms with wind turbines. Environmental loading of structures via numerical analysis and FEA.
  • Key modules: Energy Systems Analysis | Electrical Power Systems | Energy Modelling and Monitoring | Energy Resources and Policy | Project Management

Bachelor of Engineering: Robert Gordon University

Mechanical Engineering (1st Class Honours), 2012 - 2016

  • Dissertation: Investigation of carbon fibre/flax bio-composites for improved damping properties.
  • Key modules: Engineering Analysis | Safety, Risk and Reliability Management | Mathematics | Electrical Power Control and Instrumentation | Failure Analysis | Thermo-Fluids
Publications
  • Morrison, R., Liu, X., Lin, Z., 2022, Anomaly Detection in Wind Turbine SCADA Data for Power Curve Cleaning, Renewable Energy, 184, 473-486.
  • Li, T., Liu, X., Lin, X., Morrison, R., 2022, Ensemble offshore Wind Turbine Power Curve modelling – An integration of Isolation Forest, fast Radial Basis Function Neural Network, and metaheuristic algorithm, Energy, 239.
  • Morrison, R., Li, G., Busse, A., 2026, Parameter Estimation of Mooring Lines for a Floating Offshore Wind Turbine Digital Twin, submitted for publication.
  • Morrison, R., Li, G., Busse, A., 2026, Mooring Line Parameter Estimation under Biofouling and Corrosion, submitted for publication.
Research Skills
  • Machine Learning: Deployed ML for wind turbine power curve cleaning (2 publications) and optimisation frameworks (thesis/2 further papers submitted).
  • Python: Self-taught Python programmer. Extensive use for both work and PhD, including Machine Learning, Data Analysis, and Data Visualisation, and automation. Developed optimisation frameworks for PhD. Python use in previous work and hobbyist projects.
  • Data Analysis: Proficient in Python packages of Pandas, Numpy, and Matplotlib. Also proficient with SQL.
  • Modelling: Long history of numerical modelling with SolidWorks, Ansys (for MSc), Autodesk Inventor (work), and OpenFOAM and OpenFAST (PhD). Additional data-driven modelling with Neural Networks (PhD) and general mathematical modelling.
  • Research: Critical research skills developed for strategy development, papers and thesis chapters.
  • Digital Twins: Domain expert from extensive critical analysis of DT applications in Wind Energy. Original DT papers currently under review.
  • Anomaly Detection: Extensive knowledge of AD, expert level regarding wind turbine power curves, developed new approaches to detect AD methods “cheating” evaluation metrics.
  • WindPro use for noise assessments using the DECIBEL module.
  • Also proficient with C++, Linux, MATLAB, Ansys, SolidWorks, WAsP, VBA.
Training and Certification
  • Global Wind Organisation wind turbine access course, MRS Training and Rescue. Manual handing, working at heights, first aid, fire awareness, 2026.
  • Emergency first-aid at work training, by Siren, 2025
  • OpenFOAM – “Essential CFD”, “Applied CFD” and “Programming CFD” 2-week course by CFD Direct, 2022
  • IAM Asset Management Introduction (IAM certified) Black and Veatch, internal 1-day, 2020
  • WAsP software training, DTU, self-paced, 1-week, 2019
  • Health and Safety in Design, Black and Veatch, internal, 3-days, 2019