机械与电子2024，Vol.42Issue(8)：15-19,25,6.
基于自适应k均值和SVR的光伏出力预测
Photovoltaic Output Prediction Based on Adaptive k-means and SVR
孙艳玲 1朱晨光 1邵山 2田媛 2陈中杰 2谢东阳2
作者信息
- 1. 平高集团有限公司,河南 平顶山 467000
- 2. 平高综合能源服务有限公司,河南 平顶山 467000
- 折叠
摘要
Abstract
To solve the problem of inaccurate photovoltaic power prediction,a photovoltaic output pre-diction method based on adaptive k-means and support vector regression is proposed.Firstly,k-means clustering and its improvement methods are analyzed,and the basic principle and application process of support vector regression(SVR)are presented.The radial basis function convex optimization model is in-troduced.Then,combining adaptive k-means and support vector regression,based on the basic character-istics of photovoltaic output,the photovoltaic output prediction process and statistical evaluation indicators of prediction results are analyzed.Finally,taking the lighting data of"Kunming,Yunnan"as an actual cal-culation example,the prediction model structure is determined,and three algorithms,k-means and SVR,ARMA,and ANN,are used for prediction.The prediction statistical indicators under different clustering results and algorithms are compared to verify the effectiveness of the proposed method,providing a method for photovoltaic output prediction.关键词
自适应k均值/光伏功率/出力预测/支持向量回归Key words
adaptive k-means/PV power/output prediction/support vector regression分类
信息技术与安全科学引用本文复制引用
孙艳玲,朱晨光,邵山,田媛,陈中杰,谢东阳..基于自适应k均值和SVR的光伏出力预测[J].机械与电子,2024,42(8):15-19,25,6.
