Comparison of simulation methods for power system reliability indexes and their distributions

abstract

• In this paper, Latin hypercube sampling (LHS) is investigated in connection with reliability evaluation of a power system. A new sampling technique called discrete Latin hypercube (DLHS) is also proposed. Distributions of reliability indexes resulting from two sampling techniques are presented and analyzed along with those from Monte Carlo (MC) sampling. A comparison among LHS, DLHS and traditional MC for reliability analysis is made. The LHS and DLHS are shown to be more effective than MC for obtaining distributions of indices that are close to the real distributions. The distributions of indices are useful in risk analysis and certain stochastic optimization problems. The test system is a 12-area power system which is based on the data from an actual multi-area system. 2008 IEEE.

authors

• Singh, Chanan

published proceedings

• IEEE TRANSACTIONS ON POWER SYSTEMS

author list (cited authors)

• Jirutitijaroen, P., & Singh, C.

citation count

• 81

complete list of authors

• Jirutitijaroen, Panida||Singh, Chanan

publication date

• May 2008

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE TRANSACTIONS ON POWER SYSTEMS  Journal

keywords

• Discrete Latin Hypercube Sampling
• Latin Hypercube Sampling
• Monte Carlo Sampling
• Power System Reliability
• Single Area Reliability Analysis

Digital Object Identifier (DOI)

• 10.1109/TPWRS.2008.919425

start page

• 486

end page

• 493

volume

• 23

issue

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ftpwrs.2008.919425