Novel Model of an Adaptive Wave Energy Converter With Spectral Analysis-Based Sea State Classification

Overview

The objective of this project is to measure the effects of adaptive control on the performance of a wave energy converter (WEC). Ocean wave energy is one of the most promising sources of renewable energy with a measured annual 2.64 trillion kWh. This energy is harvested via WECs, which utilize a power-take-off (PTO) system to convert the kinetic energy of wave movement into usable electrical energy. The most common type of WEC is the point absorber, and one limitation of WECs is the unstable electrical power generation across changing climates. To solve this problem, an adaptive model of a point absorber with a hydraulic PTO was designed. The adaptive model consisted of a spectral analysis-based sea state classification algorithm and an alterable swashplate angle ratio. The adaptive model is compared to a non-adaptive model on a phased simulation to determine the megawattage. The results showed that the adaptive WEC generated 19.928% more electrical power than the control WEC, and the results were found to be significant via a t-test. It was found that an adaptive WEC could significantly increase the electrical power generation and maximize performance across sea state changes.

Awards (2)

• Acoustical Society of America: All ASA Award Recipients are invited to attend our next ASA Meeting for free! (Read the above, but not this next detail: The ASA meeting registration fees waived, valued at $25 per student & $200 for 1 guardian) $25
• Acoustical Society of America: Third Award of $600.00. In addition, their Mentor will be awarded $150. $600

Competition history

• ISEF 2022 Energy: Sustainable Materials and Design · Entry EGSD012 · Atlanta, Georgia, United States

Resources

• ISEF abstract page ↗

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