Biblio

This paper proposes a power network vulnerability analysis method based on topological approach considering of uncertainties from high-penetrated wind generations. In order to assess the influence of the impact of wind generation owing to its variable wind speed etc., the Quasi Monte Carlo based probabilistic load flow is adopted and performed. On the other hand, an extended stochastic topological vulnerability method involving Complex Network theory with probabilistic load flow is proposed. Corresponding metrics, namely stochastic electrical betweenness and stochastic net-ability are proposed respectively and applied to analyze the vulnerability of power network with wind generations. The case study of CIGRE medium voltage benchmark network is performed for illustration and evaluation. Furthermore, a cascading failures model considering the stochastic metrics is also developed to verify the effectiveness of proposed methodology.

Cyber security risk assessment is very important to quantify the security level of communication-based train control (CBTC) systems. In this paper, a methodology is proposed to assess the cyber security risk of CBTC systems that integrates complex network theory and attack graph method. On one hand, in order to determine the impact of malicious attacks on train control, we analyze the connectivity of movement authority (MA) paths based on the working state of nodes, the connectivity of edges. On the other hand, attack graph is introduced to quantify the probabilities of potential attacks that combine multiple vulnerabilities in the cyber world of CBTC. Experiments show that our methodology can assess the security risks of CBTC systems and improve the security level after implementing reinforcement schemes.

The vulnerability assessment of the cyber-physical power system based on complex network theory is applied in this paper. The influence of the power system statistics upon the system vulnerability is studied based on complex network theory. The electrical betweenness is defined to suitably describe the power system characteristics. The real power systems are utilized as examples to analyze the distribution of the degree and betweenness of the power system as a complex network. The topology model of the cyber-physical power system is formed, and the static analysis is implemented to the study of the cyber-physical power system structural vulnerability. The IEEE 300 bus test system is selected to verify the model.

Major blackouts are due to cascading failures in power systems. These failures usually occur at vulnerable links of the network. To identify these, indicators have already been defined using complex network theory. However, most of these indicators only depend on the topology of the grid; they fail to detect the weak links. We introduce a new metric to identify the vulnerable lines, based on the load-flow equations and the grid geometry. Contrary to the topological indicators, ours is built from the electrical equations and considers the location and magnitude of the loads and of the power generators. We apply this new metric to the IEEE 118-bus system and compare its prediction of weak links to the ones given by an industrial software. The agreement is very well and shows that using our indicator a simple examination of the network and its generator and load distribution suffices to find the weak lines.

Traditionally, power grid vulnerability assessment methods are separated to the study of nodes vulnerability and edges vulnerability, resulting in the evaluation results are not accurate. A framework for vulnerability assessment is still required for power grid. Thus, this paper proposes a universal method for vulnerability assessment of power grid by establishing a complex network model with uniform weight of nodes and edges. The concept of virtual edge is introduced into the distinct weighted complex network model of power system, and the selection function of edge weight and virtual edge weight are constructed based on electrical and physical parameters. In addition, in order to reflect the electrical characteristics of power grids more accurately, a weighted betweenness evaluation index with transmission efficiency is defined. Finally, the method has been demonstrated on the IEEE 39 buses system, and the results prove the effectiveness of the proposed method.

In order to make up for the shortcomings of traditional evaluation methods neglecting node difference, a vulnerability assessment method considering node heterogeneity for cyber physical power system (CPPS) is proposed. Based on the entropy of the power flow and complex network theory, we establish heterogeneity evaluation index system for CPPS, which considers the survivability of island survivability and short-term operation of the communication network. For mustration, hierarchical CPPS model and distributed CPPS model are established respectively based on partitioning characteristic and different relationships of power grid and communication network. Simulation results show that distributed system is more robust than hierarchical system of different weighting factor whether under random attack or deliberate attack and a hierarchical system is more sensitive to the weighting factor. The proposed method has a better recognition effect on the equilibrium of the network structure and can assess the vulnerability of CPPS more accurately.

Cascading failure is an intrinsic threat of power grid to cause enormous cost of society, and it is very challenging to be analyzed. The risk of cascading failure depends both on its probability and the severity of consequence. It is impossible to analyze all of the intrinsic attacks, only the critical and high probability initial events should be found to estimate the risk of cascading failure efficiently. To recognize the critical and high probability events, a cascading failure analysis model for power transmission grid is established based on complex network theory (CNT) in this paper. The risk coefficient of transmission line considering the betweenness, load rate and changeable outage probability is proposed to determine the initial events of power grid. The development tendency of cascading failure is determined by the network topology, the power flow and boundary conditions. The indicators of expected percentage of load loss and line cut are used to estimate the risk of cascading failure caused by the given initial malfunction of power grid. Simulation results from the IEEE RTS-79 test system show that the risk of cascading failure has close relations with the risk coefficient of transmission lines. The value of risk coefficient could be useful to make vulnerability assessment and to design specific action to reduce the topological weakness and the risk of cascading failure of power grid.

Software structure analysis is crucial in software testing. Using complex network theory, we present a series of methods and build a two-layer network model for software analysis, including network metrics calculation and features extraction. Through identifying the critical functions and reused modules, we can reduce nearly 80% workload in software testing on average. Besides, the structure network shows some interesting features that can assist to understand the software more clearly.