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Renewable Energy

Principal investigator: Guang LI

Current work is mainly on sea wave energy:
Ocean waves provide a vast, persistent and spatially concentrated energy compared with other renewable energy resources (e.g. solar and wind energies). Although enormous efforts have been made for decades in modern marine energy generation, it is still a relatively immature technology for commercial purposes because of the inefficient energy extraction rate and the risk of device damages. This all results in uneconomically high installed capacity costs. It has been demonstrated that suitable control strategies play key roles in resolving these problems. Briefly, the control objective of a wave energy converter (WEC) is to maximize the energy extraction at given sea conditions, while the devices are guaranteed to run safely by imposing constraints during operations. This is a typical constrained optimal control problem and can be potentially solved by model predictive control (MPC) strategy. Our recent works have demonstrated that MPC combined with appropriated wave prediction algorithms can double the energy output. This result shows promising direction of WEC control. This work has attracted broad media coverage such as BBC TV, BBC radio and many websites. Following this work, we are developing more efficient control algorithms for the control of a single WEC and an array of WECs.