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Forecasting Waves and Optimal Control of a Novel Wave Energy Device




2: Mechanical Engineering

Faculty Supervisor:

Paul Sclavounos

Faculty email:


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Project Description

Wave energy is poised to play an important role in the renewable energy space, however few designs have been able to achieve the robust and cost-effective performance needed garner widespread support for large-scale implementation. A new oscillating water column and bi-radial turbine design developed by our collaborators may be able change that attitude, and we need to design an optimal control strategy to maximize its energy capture. In a complex, real-world environment, this requires predicting waves a few seconds/minutes into the future. Our lab has been developing a pair of novel forecasting methods using advanced signal processing and machine learning strategies. We are seeking a motivated student to help us further develop novel forecasting and control strategies. Additionally, we are seeking a student to extend an existing simulation framework to evaluate the device performance. This work will inform the next iteration of the hydro-turbo-mechanical design that will take place in the subsequent terms. Students will work closely with a team of graduate students and researchers from MIT and Instituto Superior Technico Lisbon.


Understand the fundamentals of fluid mechanics, basic signal processing and have MATLAB, Julia or other programming experience. Basic knowledge of thermodynamics and/or advanced signal processing is a plus. Applicants should be interested in renewable energy and/or ocean systems, but no prior experience is necessary.