会议专题

Application of Support Vector Machine Based on Particle Swarm Optimization in Low Voltage Line Loss Prediction

  As low voltage line loss calculation is the difficulty of line loss, accurate prediction of low voltage line loss rate can guide energy-saving and consumption-reducing work effectively. In this paper, the support vector machine (SVM) Parameters Optimization Algorithm based on particle swarm optimization (PSO) is used to predict the low voltage line loss rate. After the analysis of the related factors that affecting line loss, the power supply;average length of lines; average capacity of transformers and maximum load are selected as parameters for the training of SVM prediction model, then use the line loss prediction model to predict the low voltage line loss rate. Predict results of model testing which uses part of the known data in typical year show the average prediction error is only1.92%, which can give a strong support for this line loss prediction model.

support vector machine particle swarm optimization line loss prediction

Tan Min Wang Xinghua Li Qing Guo Lexin Yu Tao Feng Yongkun

South China University of Technology, Guangzhou, China Hunan Electric Power Transmission Construction Company, Changsha, China

国际会议

2015 Joint International Mechanical,Electronic and Information Technology Conference(JIMET 2015)(2015 联合国际机械,电子与信息技术国际会议)

重庆

英文

193-196

2015-12-18(万方平台首次上网日期,不代表论文的发表时间)