Improving Power System Reliability Calculation Efficiency With EPSO Variants

abstract

• This paper presents an application of evolutionary particle swarm optimization (EPSO)-based methods to evaluate power system reliability. Population-based (PB) methods appear as competitors to the traditional Monte Carlo simulation (MCS), because they are computationally efficient in estimating a variety of reliability indices. The work reported in this paper demonstrates that EPSO variants can focus the search in the region of the state space where contributions to the formation of a reliability index may be found, instead of conducting a blind sampling of the space. The results obtained with EPSO are compared to MCS and with other PB methods. 2009 IEEE.

authors

• Singh, Chanan

published proceedings

• IEEE TRANSACTIONS ON POWER SYSTEMS

author list (cited authors)

• Miranda, V., Carvalho, L., da Rosa, M. A., Leite da Silva, A. M., & Singh, C.

citation count

• 66

complete list of authors

• Miranda, Vladimiro||Carvalho, Leonel de Magalhaes||da Rosa, Mauro Augusto||Leite da Silva, Armando M||Singh, Chanan

publication date

• November 2009

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE TRANSACTIONS ON POWER SYSTEMS  Journal

keywords

• Evolutionary Algorithms
• Monte Carlo Sampling
• Particle Swarm
• Population-based Methods
• Reliability Analysis

Digital Object Identifier (DOI)

• 10.1109/TPWRS.2009.2030397

start page

• 1772

end page

• 1779

volume

• 24

issue

• 4

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ftpwrs.2009.2030397