|Table of Contents|

Medium and Long Term Photovoltaic Power GenerationForecasting Based on OS-ELM(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2020年01期
Page:
8-14
Research Field:
电气工程
Publishing date:

Info

Title:
Medium and Long Term Photovoltaic Power GenerationForecasting Based on OS-ELM
Author(s):
Qian Ziwei1; 2; Sun Yichao1; 2; Wang Qi1; 2; Ji Shunxiang1; 2; Zhou Min1; 2; Zeng Baichen1; 2
(1.School of NARI Electrical and Automation,Nanjing Normal University,Nanjing 210023,China)(2.Jiangsu Key Laboratory of Gas and Electricity Interconnection Integrated Energy,Nanjing Normal University,Nanjing 210023,China)
Keywords:
photovoltaic forecasting; correlation analysis; online sequential extreme learning machine(OS-ELM); data update
PACS:
TM615
DOI:
10.3969/j.issn.1672-1292.2020.01.002
Abstract:
In order to further improve the accuracy of PV output prediction,a medium and long term power prediction method based on online sequential extreme learning machine(OS-ELM)is proposed. Combined with the characteristics of fast learning and generalization ability of OS-ELM,the output power of photovoltaic power generation system is predicted by comprehensively processing a large number of meteorological data and historical power generation data. At the same time,due to the continuous input of real-time data,the method can update the prediction model online. The simulation study shows that compared with the back propagation(BP)neural network and support vector machine(SVM)method,the predictional method can effectively improve the prediction accuracy and meet the needs of online applications,and it has a good application prospect.

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Last Update: 2020-03-15