DocumentCode :
2604676
Title :
Data envelopment analysis based efficiency assessment of power plants
Author :
Yang, Aimin ; Wang, Qin ; Wen, Fushuan ; MacGill, Iain
Author_Institution :
Sch. of Electr. Eng., South China Univ. of Technol., Guangzhou, China
fYear :
2009
fDate :
6-7 April 2009
Firstpage :
1
Lastpage :
5
Abstract :
Generation plant efficiency is an important measure for evaluating the operating behavior of a power plant, and hence an issue of extensive concern with generation companies. On the other hand, in the deregulated electricity market environment, the change of generation efficiency before and after the restructuring is a very important index for evaluating, at least to some extent, if the restructuring is successful or not. This paper estimates the efficiency of an electric power generation company for the period of 1991 through 2008 using Data Envelopment Analysis (DEA). Heat rate and utilization of net capacity are used as DEA outputs; installed capacity per capital, labor efficiency, share of operating expenses to revenue and share of energy loss to net generation are used as DEA inputs. Obtained results reveal a relative increase in efficiency after the restructuring, and hence providing some modest support for restructuring.
Keywords :
data envelopment analysis; electric power generation; power generation economics; power markets; data envelopment analysis; deregulated electricity market; electric power generation company; generation plant efficiency; power plant efficiency assessment; Australia; Data envelopment analysis; Electricity supply industry; Electricity supply industry deregulation; Energy loss; Power generation; Power grids; Power industry; Power measurement; Production; Data Envelopment Analysis (DEA); Electricity generation; assessment; efficiency; power sector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
Type :
conf
DOI :
10.1109/SUPERGEN.2009.5348284
Filename :
5348284
Link To Document :
بازگشت