A Model Predictive Control Strategy for Smoothing Power Fluctuations of Wave Energy Converter Arrays Using Supercapacitors

Combining multiple direct-drive wave energy converters (WECs) into WEC arrays can effectively improve power generation and energy utilization, which is a promising wave energy utilization scheme. However, unlike wind and photovoltaic systems, the output power of WEC arrays fluctuates frequently and varies greatly, which can easily threaten the reliability and security of power grids. Therefore, it is necessary to use energy storage systems (ESSs) with long cycle life and high power density to realize stable power output. To this end, this paper employs supercapacitors (SCs) to smooth output power fluctuations of WEC arrays and proposes a model predictive control (MPC) strategy aiming at minimum power output and optimal state of charge (SOC) of supercapacitors. To characterize the power output requirements of supercapacitors under different SOCs, this paper introduces a weight factor for the SOC increment in the MPC objective function. By dynamically adjusting the weight factor during rolling horizon optimization, the self-recovery of the supercapacitor SOC can be ensured while the output power of supercapacitors is as small as possible. Finally, a simulation model is built in MATLAB/Simulink. Compared with the low-pass filtering (LPF) strategy, the MPC strategy proposed in this paper can obtain significantly smoother grid-connected power with smaller supercapacitor throughput, and the supercapacitor SOC can be stabilized within the target range.