Abstract
In this paper we numerically study the topology robustness of power grids under random and selective node breakdowns, and analytically estimate the critical node-removal thresholds to disintegrate a system, based on the available US power grid data. We also present an analysis on the node degree distribution in power grids because it closely relates with the topology robustness. It is found that the node degree in a power grid can be well fitted by a mixture distribution coming from the sum of a truncated Geometric random variable and an irregular Discrete random variable. With the findings we obtain better estimates of the threshold under selective node breakdowns which predict the numerical thresholds more correctly.
| Original language | English (US) |
|---|---|
| Title of host publication | 2010 IEEE International Conference on Communications Workshops, ICC 2010 |
| DOIs | |
| State | Published - 2010 |
| Externally published | Yes |
| Event | 2010 IEEE International Conference on Communications Workshops, ICC 2010 - Capetown, South Africa Duration: May 23 2010 → May 27 2010 |
Other
| Other | 2010 IEEE International Conference on Communications Workshops, ICC 2010 |
|---|---|
| Country | South Africa |
| City | Capetown |
| Period | 5/23/10 → 5/27/10 |
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Keywords
- Node degree distribution
- Power grid
- Topology robustness
ASJC Scopus subject areas
- Computer Networks and Communications
- Electrical and Electronic Engineering
Cite this
The node degree distribution in power grid and its topology robustness under random and selective node removals. / Wang, Zhifang; Scaglione, Anna; Thomas, Robert J.
2010 IEEE International Conference on Communications Workshops, ICC 2010. 2010. 5503926.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - The node degree distribution in power grid and its topology robustness under random and selective node removals
AU - Wang, Zhifang
AU - Scaglione, Anna
AU - Thomas, Robert J.
PY - 2010
Y1 - 2010
N2 - In this paper we numerically study the topology robustness of power grids under random and selective node breakdowns, and analytically estimate the critical node-removal thresholds to disintegrate a system, based on the available US power grid data. We also present an analysis on the node degree distribution in power grids because it closely relates with the topology robustness. It is found that the node degree in a power grid can be well fitted by a mixture distribution coming from the sum of a truncated Geometric random variable and an irregular Discrete random variable. With the findings we obtain better estimates of the threshold under selective node breakdowns which predict the numerical thresholds more correctly.
AB - In this paper we numerically study the topology robustness of power grids under random and selective node breakdowns, and analytically estimate the critical node-removal thresholds to disintegrate a system, based on the available US power grid data. We also present an analysis on the node degree distribution in power grids because it closely relates with the topology robustness. It is found that the node degree in a power grid can be well fitted by a mixture distribution coming from the sum of a truncated Geometric random variable and an irregular Discrete random variable. With the findings we obtain better estimates of the threshold under selective node breakdowns which predict the numerical thresholds more correctly.
KW - Node degree distribution
KW - Power grid
KW - Topology robustness
UR - http://www.scopus.com/inward/record.url?scp=77954891059&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954891059&partnerID=8YFLogxK
U2 - 10.1109/ICCW.2010.5503926
DO - 10.1109/ICCW.2010.5503926
M3 - Conference contribution
AN - SCOPUS:77954891059
SN - 9781424468263
BT - 2010 IEEE International Conference on Communications Workshops, ICC 2010
ER -