摘要
风力发电的不可控性,给电网带来了很多问题,所以当前迫切需要一种高精度的风力发电预测系统。对此,提出了一种结合量子遗传算法和BP神经网络的预测方法,通过量子遗传算法优化BP神经网络的权值和阈值。最后通过MATLAB试验仿真,验证了该方法可有效提高风功率的准确性。
The uncontrollability of wind power has brought many problems to the grid,so there is an urgent need for a high-precision wind power generation prediction system.In this regard,a prediction method combining quantum genetic algorithm and BP neural network is proposed,and the weights and thresholds of BP neural network are optimized by quantum genetic algorithm.Finally,through MATLAB test simulation,it is verified that the method can effectively improve the accuracy of wind power.
作者
李铭
昝润鹏
刘景霞
LI Ming;ZAN Runpeng;LIU Jingxia(School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou 014010,China;Guodian North China Inner Mongolia New Energy Co.,Ltd.,Baotou 014000,China)
出处
《电工技术》
2021年第20期65-66,70,共3页
Electric Engineering
关键词
风功率预测
BP神经网络
量子遗传算法优化BP神经网络
风力发电
wind power prediction
BP neural network
optimization of BP neural network by quantum genetic algorithm
wind power generation
