Rocchetta, Roberto ORCID: 0000-0002-8117-8737 and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2016) POWER GRID ROBUSTENSS TO SEVERE FAILURES: TOPOLGICAL AND FLOW BASED METRICS COMPARISION. In: VII European Congress on Computational Methods in Applied Sciences and Engineering, 2016-6-5 - 2016-6-10.

[img] Text
eccomas2016.pdf - Author Accepted Manuscript

Download (487kB)


Power grids are generally regarded as very reliable systems, nevertheless outages and electricity shortfalls are common events and have the potential to produce significant social and economic consequences. It is important to reduce the likelihood of those severe accidents by assuring safe operations and robust topologies. The grid safety relies on accurate vulnerability measures, control schemes and good quality information. For instance, in power network operations, contingency analysis is used to constrain the network to secure operative states with respect to predefined failures (e.g. list of single component failures). An exhaustive failure list is often not treatable, therefore a selection or ranking is performed to help in the choice. In order to better understand the power network weakness and strengths a variety of robustness metrics have been introduced in literature, although many do not account or partially account for uncertainties which might affect the analysis. In this work power network vulnerability to failure events is analysed and single line outages (N-1 contingencies) have been ranked using different metrics (i.e. topology-based, flow-based and hybrid metrics). Sources of uncertainty such as power demand variability and lack of precise knowledge on the network parameters have been accounted for and its effect on the component ranking quantified. A modified version of the IEEE 118 bus power network has been selected as representative case study. The assumption underpinning the methodologies and the vulnerability results also accounting uncertainty are discussed.

Item Type: Conference or Workshop Item (Unspecified)
Depositing User: Symplectic Admin
Date Deposited: 11 Jan 2017 11:05
Last Modified: 19 Jan 2023 07:24
DOI: 10.7712/100016.2246.10737
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3004848