Online prediction of transmission dynamic line rating based on radial basis function neural network

Dianwang Jishu/Power System Technology

Volumn 37, Issue 6, 2013, Pages 1719-1725

  Wang, Kongsen ^a   Sheng, Gehao ^b   Sun, Xuri ^c   Wang, Wei ^d   Wang, Shiqiang ^c   Jiang, Xiuchen ^b  

^a State Grid Materials Co Ltd   (China)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

^c Liaocheng Power Supply Company   (China)

^d NARI TECHNOLOGY CO LTD   (China)

Author keywords

Dynamic line rating; Online prediction; RBFNN; Transmission line

Indexed keywords

DYNAMIC LINE RATING(DLR); DYNAMIC LINE RATINGS; GRID-CONNECTED CAPACITIES; MAXIMUM RELATIVE ERRORS; ONLINE PREDICTION; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBFNN; SHORT TERM LOAD FORECASTING;

ELECTRIC LINES; ELECTRIC LOAD FORECASTING; ELECTRIC POWER TRANSMISSION NETWORKS; RATING; SCHEDULING; TRANSMISSION LINE THEORY; WIND POWER;

FORECASTING;

EID: 84879536626     PISSN: 10003673     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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