基于Vague软集的海上风电功率区间预测  

Offshore Wind Power Interval Prediction Based on Vague Soft Set

作　　者：田书欣[1] 朱峰 杨喜军[3] 符杨 苏向敬 TIAN Shuxin;ZHU Feng;YANG Xijun;FU Yang;SU Xiangjing(Engineering Research Center of Offshore Wind Technology Ministry of Education(Shanghai University of Electric Power),Yangpu District,Shanghai 200090,China;College of Electrical Engineering,Shanghai University of Electric Power,Yangpu District,Shanghai 200090,China;Department of Electrical Engineering,Shanghai Jiao Tong University,Minhang District,Shanghai 200240,China)

机构地区：[1]教育部海上风电技术工程研究中心(上海电力大学),上海市杨浦区200090 [2]上海电力大学电气工程学院,上海市杨浦区200090 [3]上海交通大学电气工程系,上海市闵行区200240

出　　处：《中国电机工程学报》2025年第4期1465-1476,I0019,共13页PROCEEDINGS OF THE CHINESE SOCIETY FOR ELECTRICAL ENGINEERING

基　　金：国家自然科学基金项目(52007112)。

摘　　要：海上风电输出功率的精准预测是保障海上风电并网系统调度运行的基础。针对海上风电海洋环境高度复杂、随机时空强烈耦合的特征,提出一种基于Vague软集的海上风电输出功率的新型区间预测方法。首先,引入Vague软集概念,提出融合Vague集真隶属度和伪隶属度函数的交错式海上风电功率区间划分方法,实现风电功率数据Vague软区间化。其次,建立基于Vague-卷积神经网络(convolutional neural network,CNN)-长短期记忆神经网络(long short-term memory neural network,LSTM)的海上风电功率组合预测模型。通过类Vague软区间转换方法将双隶属度区间概率向量转化为海上风电功率复杂不确定信息下的区间预测结果。然后,从预测准确性、清晰性和兼顾性角度建立预测区间覆盖精度、预测区间宽度和预测综合水平等Vague软区间预测评估指标。最后,以我国东部某海上风电机组实际数据为算例进行验证。结果表明,所提预测模型预测结果可以兼顾预测区间的覆盖精度和清晰度,能够为海上风电不同工况下运行需求提供支撑。Accurate prediction of offshore wind power output is the basis for guaranteeing the dispatch operation of offshore wind power grid-connected system.Aiming at the highly complex marine environment of offshore wind power and the strong coupling of stochastic space-time,this paper proposes a new type of interval prediction method for offshore wind power output based on Vague soft set.First,the concept of Vague soft set is introduced,and the interleaved offshore wind power interval division method integrating the true affiliation and pseudo-affiliation functions of Vague set is proposed to realize the Vague soft intervalization of wind power data.Then,an offshore wind power combination prediction model based on Vague-convolutional neural network(CNN)-long short-term memory neural network(LSTM)is established.The double affiliation interval probability vector is transformed into the interval prediction result under the complex uncertain information of offshore wind power by the Vague-like soft interval transformation method.Next,Vague soft interval prediction evaluation indexes such as prediction interval coverage accuracy,prediction interval width and prediction synthesis level are established from the perspective of prediction accuracy,clarity and compatibility.Finally,the actual data of an offshore wind turbine in the eastern part of China are used as an example for validation,and the results show that the proposed prediction model can take into account the coverage accuracy and clarity of the prediction intervals,which can provide support for the operational requirements of offshore wind power under different working conditions.

关 键 词：海上风电 Vague-卷积神经网络(CNN)-长短期记忆神经网络(LSTM)模型 Vague软集 软区间转换 区间预测 

分 类 号：TM614[电气工程—电力系统及自动化]