Title :
Load Model Based on Integrative K-means Clustering For Reliability Evaluation in Operational Planning
Author :
Li, Xiaoyan ; Ding, Ming
Author_Institution :
Sch. of Electr. Eng., Hefei Univ. of Technol., Hefei, China
Abstract :
Aiming the deficiency of traditional load model used for reliability assessment, this paper proposes a new integrative K-means clustering algorithm incorporating load characteristics information. Based on the clustering algorithm, this model adopts multi-dimension correlation sampling technique considering bus load correlation load forecasting uncertainty to determine the bus load in evaluation period. At last, the effects of number of clustering, bus load correlation, and load forecast uncertainty are discussed and compared by case studies. The feasibility and reasonableness of the proposed algorithm are proved.
Keywords :
load forecasting; power system planning; power system reliability; statistical analysis; bus load correlation; integrative k-means clustering; load characteristics information; load forecasting uncertainty; operational planning; reliability evaluation; Clustering algorithms; Load forecasting; Load modeling; Partitioning algorithms; Power grids; Power system modeling; Predictive models; Sampling methods; Technology planning; Uncertainty;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
DOI :
10.1109/APPEEC.2010.5448182