基于大数据的配电网架空线路工程造价预测  

Project Cost Prediction of Overhead Lines in Distribution Network Based on Big Data

作　　者：李谟兴 何永秀[1] 柳洋 潘肇伦 LI Moxing;HE Yongxiu;LIU Yang;PAN Zhaolun(School of Economic and Management,North China Electric Power University,102206 Beijing,China)

机构地区：[1]华北电力大学经济与管理学院,北京102206

出　　处：《河北电力技术》2023年第1期37-44,共8页Hebei Electric Power

基　　金：国家自然科学基金项目(71671065);国家电网上海市电力公司科技项目(52090R200016)。

摘　　要：大数据与人工智能技术推动了工程造价全方位创新,为了提升配电网工程造价决策的水平,针对配电网架空线路工程中存在造价影响因素多、预测精度低等问题,提出一种配电网架空线路工程造价组合预测模型。首先,对配电网架空线路工程中重要数据缺失情况进行分析处理,其次,基于随机森林算法对配电网架空线路重要造价影响因素进行选取。最后,在参数寻优基础上采用最小二乘支持向量机模型进行造价预测。仿真对比结果显示,所构建的造价预测模型能有效提升预测速度和精度,该预测模型可为实现配电网架空线路工程造价预测提供一种有效实用的方法。Big data and artificial intelligence technology have promoted the all-round innovation of engineering cost.In order to improve the level of decisionr making of distribution network engineering cost,aiming at the problems of many influencing cost factors and low prediction accuracy in distribution network,this paper proposed a distribution network overhead line engineering cost combination prediction model.Firstly,the missing of important data in the overhead line project of the distribution network was analyzed and processed.Seconelly,the important cost factors of overhead lines of the distribution network were selected based on the random forest algorithm.Finally,the least squares support vector machine model was used for cost prediction based on parameter optimization.By the comparison of the results of different prediction methods,it is confirmed that the cost predic-tion model constructed is closest to the measured value and can effectively improve the prediction speed and accuracy.The pre-diction model can provide an effective and practical method for realizing the cost prediction of overhead line project in distribu-tion network.

关 键 词：配电网 大数据 随机森林算法 交叉验证方法 最小二乘支持向量机 造价预测 

分 类 号：TM726[电气工程—电力系统及自动化]