Statistical Properties and Classification of N-2 Contingencies in Large Scale Power Grids

Abstract

We present the systematic analysis of all dangerous N − 2 contingencies observed in medium size model of Polish power grid with about 2600 power lines. Each of the dangerous contingencies is composed of two initially tripped lines and one or more lines that overloaded as the result. There are 443 distinct contingencies that do not lead to immediate islanding of the grid. In the scope of the work we analyze the statistics of individual line participation in those contingencies and show that some lines have anomalously high rate of participation in the contingencies. Next, we show that about third of all the contingencies can be associated with the subgrids that are connected to the rest of the grid via small set of power line chains. The contingencies arise when cutting some of those chains results in overload of the others. Simple reduction of power grid corresponding to aggregation of chain components significantly reduces the total number of distinct contingencies. The rest of the contingencies are closely related to a set of almost dangerous N − 1 contingencies that result in heavy loading of particular lines. Tripping many different additional lines on top of these N − 1 contingencies results in an overload of one or more lines. We conclude our work by characterization of the joint distributions of power flows through the initiating and overloaded lines and statistical analysis of topological distance between the initially tripped and overloaded lines.

Cascading Power Outages Propagate Locally in an Influence Graph that is not the Actual Grid Topology

“…Or, more practically, finding components that could be improved in some way to substantially reduce blackout risk. Prior work [12], [31] has suggested that some components, when they fail as a part of a multiple initiating contingency, contribute orders of magnitude more to blackout risk, relative to the average component. Here we suggest a method for using the information contained in H 0 and H 1+ to find those components that could propagate large cascading failures if they fail during a cascade, as opposed to during the initiating contingency.…”

Interaction Graphs for Cascading Failure Analysis in Power Grids: A Survey

“…As the name implies, the data-driven approaches for building interaction graphs rely on data collected from the system (historical and real data or simulation data) for inferring and characterizing interactions among the components of the system. Further, three categories are defined for data-driven interaction graphs based on the method used for analyzing the data.These include: (1) methods based on outage sequence analysis , (2) risk-graph methods [38][39][40][41], and (3) correlation-based methods [29,30,42,79]. The category of outage sequence analysis is further divided into four sub-categories including (i) consecutive failure-based methods [13][14][15][16][17][18][19][20], (ii) generation-based methods [21][22][23][24][25][26], (iii) influence-based methods [27][28][29][30], and (iv) multiple and simultaneous failure-based methods [31][32][33][34][35][36][37].…”

“…Consecutive Failures [13][14][15][16][17][18][19][20] Generation-based Failures [21][22][23][24][25][26] Influence-based [27][28][29][30] Multiple and Simultaneous Failures [31][32][33][34][35][36][37] Risk-graph [38][39][40][41] Correlation-based [29,30,42]…”

“…Another similar concept to risk graph is the double contingency graph introduced in [41]. While m contingency combinations of attack scenarios for the power grid was studied in the risk graphs, many methods focus on N − 2 contingency analysis as the power grid is considered to be N − 1 protected [90].…”

Security Analysis and the Contribution of UPFC for Improving Voltage Stability

“…In security analysis, power system may operate in different states, namely normal, emergency, alert, extreme state and restorative [26,27]. A system is said to be in normal operating state when it satisfies equality and inequality sets of constraints.…”