WACE - Wave energy AI-based Control Enhancement

Purpose and goal

Driven by sustainable development, wave energy converters have gained extensive attention over the last decades. In particular, the optimal operation of wave energy converters is one of the key factors to lower the levelized cost of energy (LCOE). The main goal of this project is to achieve a performance improvement of a wave energy converter by utilising artificial intelligence to enhance an existing control strategy.

Expected effects and result

Commonly, numerical models are utilized to develop an optimization-based control strategy for wave energy converters (WECs). The idea of this project is to utilize an existing control algorithm for WECs and combine it with AI-based methods to improve the performance of the overall closed-loop control scheme. This approach is not limited to WECs and can be extended to improve existing control algorithms in a wide range of industrial applications.

Planned approach and implementation

A model-based design framework is utilized in this project. After establishing requirements for the closed-loop control system, an AI-based optimal control strategy is designed along with a hardware-in-the-loop (HIL) test setup. The performance of the developed algorithm is proven using HIL testing providing a realistic real-time environment while using the existing operating strategy as a baseline.