Abstract

Wave energy has the characteristics of high density and large power fluctuation. The power of oscillating water column wave energy (OWC) power generation device has strong randomness influenced by waves, which leads to the disadvantage of strong randomness in the output power of OWC power generation device. Based on the analysis of energy output characteristics of flywheel energy storage device, combining the power output advantages of offshore OWC and flywheel energy storage (FESS), OWC and FESS are effectively matched. Advanced and mature algorithms such as BP neural network learning control are introduced into the control strategy. The flywheel energy storage auxiliary smooth wave energy generation system (ASS) is constructed and the power control strategy of ASS system with FESS configured according to 60%Pe of OWC power generation device is simulated. The results show that the ASS can realize the fast compensation of the output power of the OWC power generation device. The maximum power deviation in the dynamic simulation process is 0.03 (per unit value), which solves the output power oscillation problem of the OWC power generation device. The effectiveness of the power control strategy is verified.

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