Abstract:In this paper, the problem of identification of critical k‐line contingencies that fail one after another in quick succession that render large load shed in the power system is addressed. The problem is formulated as a mixed‐integer non‐linear programming problem (MINLP) that determines total demand that cannot be satisfied under various k‐line removal scenarios. Due to the large search space of the problem, the solution through enumeration is intractable. Two algorithms are proposed using a proposed power flo… Show more
“…However, the optimization method is inadequate to generate a large collection of contingencies in a limited time. [15] formulates a mixed-integer non-linear programming problem to identify multiple contingencies that cause a large load shed. Two algorithms using power flow sensitivity and a topological metric reduce the search space to speed up computation.…”
Multiple line outages that occur together show a variety of spatial patterns in the power transmission network. Some of these spatial patterns form network contingency motifs, which we define as the patterns of multiple outages that occur much more frequently than multiple outages chosen randomly from the network. We show that choosing N-k contingencies from these commonly occurring contingency motifs accounts for most of the probability of multiple initiating line outages. This result is demonstrated using historical outage data for two transmission systems. It enables N-k contingency lists that are much more efficient in accounting for the likely multiple initiating outages than exhaustive listing or random selection. The N-k contingency lists constructed from motifs can improve risk estimation in cascading outage simulations and help to confirm utility contingency selection.
“…However, the optimization method is inadequate to generate a large collection of contingencies in a limited time. [15] formulates a mixed-integer non-linear programming problem to identify multiple contingencies that cause a large load shed. Two algorithms using power flow sensitivity and a topological metric reduce the search space to speed up computation.…”
Multiple line outages that occur together show a variety of spatial patterns in the power transmission network. Some of these spatial patterns form network contingency motifs, which we define as the patterns of multiple outages that occur much more frequently than multiple outages chosen randomly from the network. We show that choosing N-k contingencies from these commonly occurring contingency motifs accounts for most of the probability of multiple initiating line outages. This result is demonstrated using historical outage data for two transmission systems. It enables N-k contingency lists that are much more efficient in accounting for the likely multiple initiating outages than exhaustive listing or random selection. The N-k contingency lists constructed from motifs can improve risk estimation in cascading outage simulations and help to confirm utility contingency selection.
This study proposes a new four-level model to enhance power system resilience against human attacks. The model considers human attacks, such as intelligent attackers and power system planners, as defenders. The attackers want to maximize the impacts of actions, while the defender tries to avoid imposed costs and damages due to budget limitations. To this end, a new four-level model defense-defense-attackdefense (DDAD) is proposed, in which a new defense layer is added to the common three-level model defenseattack-defense (DAD). Looking at the model more closely, new power plants and substations are added to the power system to improve its resilience, while the most important power plants and substations are determined. Subsequently, the conventional three-level model was applied. In this research, the defender and attacker have some strategies with their own costs for every power system component, such as power plants and substations, and their own interactions. The power system model includes the load, power plant and substation, and substation priority, which are defined as a combination of the value of the load and network topology. The proposed model was applied to the IEEE-30 bus test system, and the results indicated the effectiveness of the proposed method.
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