Analyzing Power Grids’ Cascading Failures and Critical Components using Interaction Graphs

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].…”

“…In addition to the review of various methods for constructing interaction graphs, various reliability analysis and studies performed using these graphs are also briefly reviewed. Some studies of interaction graphs are focused on identifying critical components in the cascade process of power grids [14][15][16][17][18][19][20][21][22][23][24][27][28][29][30][31][38][39][40]48,[56][57][58][59]. These studies can have different purposes such as (1) identifying the vulnerable or most influential components of the system in the cascade process by utilizing standard centrality metrics [14][15][16][17][18][19][20]50,54] or defining new centrality metrics [21][22][23][24] and (2) identifying the set of components whose upgrade (for instance, by increasing the power flow capacity of transmission lines) or protection can help in mitigating the risk of cascading failures and large blackouts [27,28,31,58] or quantifying the performance of the grids after addition of new transmission lines [58,…”

“…To characterize the latter, some works [16,[38][39][40]59] focus on the response of power grids to attacks and failure scenarios using metrics that quantify the efficiency of the grid before and after the attacks. Furthermore, to characterize the role of components in the cascade process, some efforts are focused on characterizing the patterns and structures in interaction graphs using community detection approaches [29,30] or tree structures [43,44]. Moreover, the work in [44] uses interaction graphs to identify transmission lines that when switched off create partitions that limit the propagation of failures in the power grid.…”

“…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]…”

“…Based on the influence graph, cascading failures can start with a line outage at a node of the graph and propagate probabilistically along the directed links in the graph. Examples of other works, that have used the influence-based approach to derive the graph of interactions for power grids include [28][29][30].…”