测风塔神经网络法对弃风电量的评估  

Wind Power Loss Estimation Based on Wind Tower Neural Network Model

作　　者：高阳 吴伟晴 许傲然 李东阳 于杰承 

机构地区：[1]沈阳工程学院电力学院,辽宁沈阳110136

出　　处：《沈阳工程学院学报（自然科学版）》2017年第3期240-243,共4页Journal of Shenyang Institute of Engineering:Natural Science

摘　　要：由于电网容量的快速可调的容量限制,造成风电并网的消纳能力较弱,导致越来越多的弃风电量。研究了神经网络方法,根据历史风塔的测量的不同高度、风速和风向的数据,结合风电场风机的历史观测数据,建立了神经网络模型,然后将样本数据输入到已建好的神经网络模型以得到风机的理论发电功率,进而得到弃风电量。通过对比测风塔法,神经网络法,样板机法和面积积分法统计风电弃风电量大小,基于测风塔神经网络法的弃风电量评估模型在低风速时的评估效果具有良好的参考价值,比较接近实测风速。There are increasing abandoned wind due to the relatively weak wind power accommodation ability led by the fast adjustable power supply capacity limitation of the power grid. This paper studied the tower neural network method and built the neural network model according to different height wind speed and wind direction data of historical wind tower measuring combining with the fan power of historical observation data of wind farm. Then,the sample data was input to the model which had built to get theoretical power fan and abandoned wind power. The abandoned wind power data counted by the wind tower method,neural network method,model machine method and area integral method respectively showed that the value based on abandoned wind power tower evaluation model of neural network method in lowwind speed had a good reference,which relatively closer to the measured wind speed.

关 键 词：电力系统 测风塔 神经网络模型 弃风电量 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]