Open AccessReliability evaluation of bulk power systems using the uniform design technique
Author(s) -
Xie Kaigui,
Huang Yingcheng,
Hu Bo,
Tai HengMing,
Wang Leibao,
Liao Qinglong
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6040
Subject(s) - reliability (semiconductor) , monte carlo method , reliability engineering , electric power system , computer science , computational complexity theory , power (physics) , state space , control reconfiguration , interval (graph theory) , state (computer science) , algorithm , engineering , mathematics , statistics , embedded system , physics , quantum mechanics , combinatorics
Reliability evaluation of bulk power systems (BPSs) has inherent computational complexity due to the numerous system states and the time‐consuming system state analysis, including power flow calculation, load curtailment, recognition of split power systems and network reconfiguration. In this study, a novel uniform‐design based method is proposed to improve the computational efficiency of power system reliability evaluation. The main idea is that the uniform‐design technique is used to generate the system states in reliability evaluation, which makes the sampled states more uniform and representative in the overall state space compared to the enumerated system states in an analytical method or the random‐generated system states in Monte Carlo simulation. As a result, the sample size and the computational time can be significantly reduced. In addition, the confidence intervals of the reliability indices, such as LOLP, FLOL and EENS, are given. And the estimation errors of reliability indices are discussed. The proposed method is tested on several BPSs, including the IEEE‐RTS79, IEEE‐RTS96 and a real BPS in China. All the case studies indicate that the proposed technique can significantly improve the computational efficiency of BPS reliability evaluation.