DocumentCode
645751
Title
Impacts of wind speed simulation methods and reliability metrics on capacity value of wind power
Author
Chong Qu ; Xiuli Wang ; Shaoyu Xie ; Xiong Wu
Author_Institution
Sch. of Electr. Eng., Xi´an Jiaotong Univ., Xi´an, China
fYear
2013
fDate
22-24 Sept. 2013
Firstpage
1
Lastpage
6
Abstract
Capacity value (CV) designates the extent to which a power plant contributes to the generating system adequacy. Evaluating the CV of wind power has been the focus. Simulating wind speed is a prerequisite for the wind power CV evaluation, since the available actual wind speed data is usually limited. Also, the reliability has to be assessed by certain indices to measure the contribution of wind power to the generation adequacy. In fact, to date, such evaluation of CV is confronted with the confusion of how to select wind speed simulation methods and reliability metrics. This study first incorporates the probability, frequency, and duration indices of the at-risk, marginal, and healthy states from the well-being analysis, together with several common wind speed simulation methods, in a consistent framework to evaluate the CV of wind power for a thorough comparison. A convenient approach to approximate the CV based on a sequential Monte Carlo simulation technique is proposed. Then with the wind integrated IEEE-RTS case study, the impacts of different wind speed simulation methods and reliability metrics on both the reliability assessment of generating systems, and the CV evaluation of wind power, are investigated. Finally, recommendations of their usage are presented.
Keywords
Monte Carlo methods; power generation reliability; wind power plants; Monte Carlo simulation; capacity value; generating system adequacy; power plant; probability; reliability metrics; wind integrated IEEE-RTS; wind power; wind speed simulation; Analytical models; Measurement; Power system reliability; Reliability; Wind farms; Wind power generation; Wind speed;
fLanguage
English
Publisher
ieee
Conference_Titel
North American Power Symposium (NAPS), 2013
Conference_Location
Manhattan, KS
Type
conf
DOI
10.1109/NAPS.2013.6666902
Filename
6666902
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