Advanced controls optimization offers a promising pathway to improve performance, reduce structural loads and thereby reduce the Levelized Cost of Electricity (LCOE) for wave energy conversion (WEC) systems. Model predictive control (MPC), which remains the preferred algorithm framework for WEC devices requires a wave excitation force forecast on the order of 30 seconds into the future to be effective. To establish the feasibility of forecasting the wave resource within this time-horizon, we benchmarked a wave prediction system that leverages an X-band ship navigation radar using a set of field campaigns carried out offshore Santa Cruz in California. For quantitative assessment of the prediction accuracy, we evaluated error metrics based on correlation and normalized mean absolute error between measurement and prediction. The relationship between prediction accuracy and key environmental factors prevalent during data collection (wave height and wind-speed) was analyzed through a set of sensitivity studies. Overall, the results show that wave prediction accuracy is good enough to enable MPC based control, which establishes a credible technology pathway to utilize these control techniques on commercial devices at sea.

先进的控制优化提供了一条有前途的途径来提高性能、减少结构载荷，从而降低波浪能转换 (WEC) 系统的平准化电力成本 (LCOE)。模型预测控制 (MPC) 仍然是 WEC 设备的首选算法框架，需要预测未来 30 秒左右的波浪激励力才能有效。为了确定在这个时间范围内预测波浪资源的可行性，我们使用一组在加利福尼亚州圣克鲁斯近海进行的实地活动，对利用 X 波段船舶导航雷达的波浪预测系统进行了基准测试。为了定量评估预测精度，我们根据测量和预测之间的相关性和归一化平均绝对误差评估了误差指标。通过一组敏感性研究分析了预测精度与数据收集过程中普遍存在的关键环境因素（波高和风速）之间的关系。总体而言，结果表明波浪预测精度足以实现基于 MPC 的控制，这为在海上商业设备上利用这些控制技术建立了可靠的技术途径。