Using Clustering to Evaluate Reliability of Composite Power Systems Conference Paper

abstract

• 2015 IEEE. A methodology is proposed to incorporate wind farms into a conventional power system which includes transmission constraints at composite system level. Monte Carlo method is used to represent operating states of turbines over time. The methodology uses clustering to consider correlation between load and wind power and sensitivity analysis to calculate reliability indices of the system efficiently. We validate our approach by using the IEEE Reliability Test Systems as well as the wind speed data from the National Renewable Energy Laboratory. It is shown that clustering can give more accurate results than the exact transition rate method previously proposed.

name of conference

• 2015 18th International Conference on Intelligent System Application to Power Systems (ISAP)

authors

• Singh, Chanan

published proceedings

• 2015 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP)

author list (cited authors)

• Kim, H., Singh, C., & Sprintson, A.

citation count

• 1

complete list of authors

• Kim, Hagkwen||Singh, Chanan||Sprintson, Alex

publication date

• January 2015

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Clustering
• Composite Level
• Monte Carlo
• Optimal Storage Bus
• Sensitivity Analysis
• Two Phase Method
• Wind Farm

Digital Object Identifier (DOI)

• 10.1109/isap.2015.7325577

International Standard Book Number (ISBN) 13

• 9781509001903

start page

• 1

end page

• 7

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Fisap.2015.7325577

user-defined tag

• 13 Climate Action
• 7 Affordable and Clean Energy