Parameter Estimation for Distribution Grid Reliability Assessment

被引：4

作者：

Wu, Raphael ^{[1
]}

Sansavini, Giovanni ^{[1
]}

机构：

[1] Swiss Fed Inst Technol, Dept Mech & Proc Engn, Inst Energy & Proc Engn, Reliabil & Risk Engn Lab, Zurich, Switzerland

来源：

2020 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS) | 2020年

关键词：

parameter estimation; distribution grid reliability; multi-objective optimization; Monte Carlo Simulation; sensitivity analysis;

D O I：

10.1109/pmaps47429.2020.9183408

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Strengthening distribution grids reliability and resilience against technical and natural hazards is a costly endeavor including equipment upgrades and distributed energy resources. Therefore, using accurate data when assessing grid reliability is key to identify effective solutions. As literature parameters can be inaccurate for specific locations, tuning and validating reliability models against real-world data is key for accurate assessments. In this paper, distribution grid reliability is modelled by considering three failure mechanisms in a Monte Carlo simulation: bus and line failures within the distribution grid, blackouts of the surrounding grid, and dependent failures due to extreme events. Ten parameters governing the frequency and duration distributions of the three failure mechanisms are tuned using metaheuristic optimization. A subsequent global sensitivity analysis quantifies the importance of the estimated parameters.

引用

页数：6

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