Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches

Abstract

Security issues related to vulnerability assessment in electrical networks are necessary for operators to identify the critical branches. At present, using complex network theory to assess the structural vulnerability of the electrical network is a popular method. However, the complex network theory cannot be comprehensively applicable to the operational vulnerability assessment of the electrical network because the network operation is closely dependent on the physical rules not only on the topological structure. To overcome the problem, an adjacent graph (AG) considering the topological, physical, and operational features of the electrical network is constructed to replace the original network. Through the AG, a branch importance index that considers both the importance of a branch and the fault adjacent relationships among branches is constructed to evaluate the electrical network vulnerability. The IEEE 118-bus system and the French grid are employed to validate the effectiveness of the proposed method. INDEX TERMS Vulnerability, complex network theory, adjacent graph, branch importance index. NOMENCLATURE ACRONYMS ENV Electrical network vulnerability AG Adjacent graph LRM Load redistribution model BIM Branch importance metric BLAI Branch loading assessment index OPF Optimal power flow NNR Nearest neighbor redistribution rule USR Uniform sharing redistribution rule CNT Complex network theory BLAI Branch loading assessment index The associate editor coordinating the review of this manuscript and approving it for publication was Weisi Guo.

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

“…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]. This novel taxonomy is used to classify thirty detailed research studies, including conference and journal publications, in the data-driven category into various subcategories.…”

“…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,…”

“…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]…”

“…These weights can be interpreted as the probability of occurrence of each pair of successive line outages. Examples of studies using this method to develop the power grid's graph of interactions include [13][14][15][16][17][18][19][20], where transmission lines in the system are the vertices V i of the interaction graph G i .…”

“…For creating the dataset of fault chains, in the first step, a single transmission line is tripped as the initiator of cascading failure in the simulation, and in the subsequent steps, the most overloaded component due to power flow re-distributions is considered as the next failure in the overall sequence of consecutive failures. In the studies in [14][15][16][18][19][20], for a power grid with n transmission lines, n fault chains are created, and the edges among consecutive failures in each chain are weighted based on power flow changes in a line after the failure. In the work in [17], fault chains are created by considering multiple initial failures such that a system with n transmission lines may have more than n fault chains.…”