基于BP神经网络的摇臂式波浪发电平台取能效率预测

Energy Efficiency of Rocker Wave Power Generation Platform Based on BP Neural Network Prediction

取能效率是衡量波浪发电装置设计合理与否的重要参考标准。文章首先介绍了摇臂式波浪发电平台,接着对BP神经网络的原理和算法进行了描述,最后以水池试验过程中收集的数据为样本数据,在Matlab平台上运用BP神经网络对实海况下摇臂式波浪发电平台的取能效率作了仿真预测。仿真结果表明:实海况下摇臂式波浪发电平台的取能效率达到了预期目标,进一步说明BP神经网络成功训练出可靠的网络,在此基础上预测的数据具有一定的参考价值。

Energy efficiency is an important reference standard for measuring the rationality of wave power plant design.This paper introduced the rocker-type wave power generation platform,and described the principle and algorithm of BP neural network.The data collected during the pool test process was taken as the sample data,and the BP neural network was used to shake the real sea state on the Matlab platform.The energy-receiving efficiency of the arm wave power platform was simulated and predicted.The simulation results showed that the energy efficiency of the rocker-type wave power generation platform reached the expected range under real sea conditions,which further demonstrated that the BP neural network had successfully trained a reliable network,so as the predicted data would have certain reference value.