Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPWRS.2011.2113380
Title: Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources
Authors: Shu, Z. 
Jirutitijaroen, P. 
Keywords: Correlation analysis
Latin hypercube sampling
Monte Carlo simulation
power system reliability
renewable energy
Issue Date: Nov-2011
Source: Shu, Z., Jirutitijaroen, P. (2011-11). Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources. IEEE Transactions on Power Systems 26 (4) : 2066-2073. ScholarBank@NUS Repository. https://doi.org/10.1109/TPWRS.2011.2113380
Abstract: This paper proposes Latin hypercube sampling (LHS) methods for reliability analysis of power systems including renewable energy sources, with an emphasis on the fluctuation of bus loads and intermittent behavior of renewable generations such as wind and solar power. The LHS methods that are applicable for systems with correlated random variables - system load and renewable generation - are proposed. Reliability indices such as loss of load expectation and loss of load probability are estimated. Results from Monte Carlo (MC) sequential sampling, MC nonsequential sampling, and that from the proposed LHS methods are compared. It is shown that the proposed methods are as accurate as the other sampling methods while requiring much less CPU time. Two case studies modified from the Electric Reliability Council of Texas (ERCOT) and IEEE Reliability Test System (IEEE RTS) are presented to demonstrate the performances of the proposed sampling methods. © 2006 IEEE.
Source Title: IEEE Transactions on Power Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/56470
ISSN: 08858950
DOI: 10.1109/TPWRS.2011.2113380
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