Abstract
In this article, a novel multilevel Monte Carlo (MLMC) simulation approach is applied for large distribution systems reliability evaluation. Basic Monte Carlo simulation (MCS) can be effectively used in this purpose. However, main limitation of MCS is the huge computational cost when a large sample size is needed for a high accuracy. The MLMC method reduces the variance of MCS and speeds up its computational efficiency through combining simulations on multiple levels of resolution. The methodology is implemented through modelling the reliability indices using stochastic differential equations. The performance of the proposed method is analysed based on computation accuracy and time, and compared with analytical and MCS approaches. A benchmark distribution system of Roy Billinton Test System (RBTS) is used as test system. Discussions of the results obtained are presented in this paper.
Original language | English |
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Title of host publication | 2017 IEEE Manchester PowerTech, Powertech 2017 |
ISBN (Electronic) | 9781509042371 |
DOIs | |
Publication status | Published - 13 Jul 2017 |
Event | PowerTech, 2017 IEEE Manchester - Manchester, UK, United Kingdom Duration: 18 Jun 2017 → 22 Jun 2017 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7964294 |
Publication series
Name | 2017 IEEE Manchester PowerTech, Powertech 2017 |
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Conference
Conference | PowerTech, 2017 IEEE Manchester |
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Country/Territory | United Kingdom |
City | Manchester, UK |
Period | 18.06.2017 → 22.06.2017 |
Internet address |
Keywords
- computational efficiency
- distribution systems
- Milstein discretisation
- multilevel Monte Carlo
- reliability