Bart Doekemeijer
Power Forecasting Analyst at Shell
The Hague, South Holland, Netherlands
Summary
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Senior🎓
Top SchoolBart Doekemeijer is an award-winning offshore wind yield engineer with nine years of hands-on experience translating advanced research into commercial offshore wind assessments and preconstruction decisions. Based in The Hague and currently at Shell, he combines deep expertise in wake modeling, wind farm control and SCADA analysis with owner-level responsibility for four in-house Python tools that directly support yield workflows. His background spans top-tier research roles at NREL and TU Delft, where he led field experiments, published journal papers, and co-invented a patented control method (“Helix”) used in industry studies. Known for securing competitive research funding and driving tech collaborations with universities and industry partners, he also serves as a team software-engineering and DE&I focal point. Colleagues rely on him for uncertainty quantification, layout optimization and technical due diligence that bridge theory and operational data. Less obvious: he repeatedly converts R&D into tangible business value, having delivered yield assessments for over ten assets and directly attracted external funding to accelerate Shell’s wind innovations.
10 years of coding experience
4 years of employment as a software developer
TU DelftBachelor of Science (BSc) Aerospace, Aeronautical and Astronautical/Space Engineering, Bachelor of Science (BSc) Aerospace, Aeronautical and Astronautical/Space Engineering at Delft University of Technology
Dutch, English, French
Stackoverflow
64reputation
3kreached
7answers
0questions
Github Skills (40)
simulation10
controller10
modeling-tool10
matlab10
power-systems10
steady-state10
power-management10
renewable-energy10
medium10
wake10
modeling10
modelica10
floris10
toolbox9
scada9
Programming languages (8)
Github contributions (5)
paulf81/SOWFA
May 2018 - Jul 2019
Contributions:16 PRs, 48 pushes, 2 branches in 1 year 2 months
TUDelft-DataDrivenControl/WFObs
Dec 2016 - Dec 2018
A collection of time-efficient state estimation algorithms for the medium-fidelity WindFarmSimulator (WFSim) control model
Contributions:4 PRs, 196 pushes, 6 branches in 2 years
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