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

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.National Natural Science Foundation of China under Grant U1734202National Key Research and Development Plan of China under Grant 2017YFB1200802-12National Natural Science Foundation of China under Grant 51877181National Natural Science Foundation of China under Grant 61703345Chinese Academy of Sciences, under Grant 2018-2019-0

Electrical Network Operational Vulnerability Evaluation Based on Small-World and Scale-Free Properties

Assessment of electrical network vulnerability based on complex network theory (CNT) has attracted increasing attention. However, CNT focuses on analyzing the structural vulnerability and has significant limitations regarding operational vulnerability. To address the lack of a comprehensive CNT-based framework to assess operational vulnerability, a temporal-spatial correlation graph (TSCG) that considers the topological, physical, and operational characteristics of electrical networks is proposed. To better assess vulnerability, two metrics, i.e., impact ability and susceptibility of branches, based on symmetric entropy from the load redistribution mechanism of electrical networks and their corresponding TSCGs are proposed. Applications to IEEE 39-bus system, IEEE 118-bus system, and French grid demonstrate that the proposed TSCGs have distinctive features that can intuitively and simply reveal the features of impact ability and susceptibility in CNT

A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism

Power transmission networks play an important role in smart girds. Fast and accurate faulty-equipment identification is critical for fault diagnosis of power systems; however, it is rather difficult due to uncertain and incomplete fault alarm messages in fault events. This paper proposes a new fault diagnosis method of transmission networks in the framework of membrane computing. We first propose a class of spiking neural P systems with self-updating rules (srSNPS) considering biological apoptosis mechanism and its self-updating matrix reasoning algorithm. The srSNPS, for the first time, effectively unitizes the attribute reduction ability of rough sets and the apoptosis mechanism of biological neurons in a P system, where the apoptosis algorithm for condition neurons is devised to delete redundant information in fault messages. This simplifies the complexity of the srSNPS model and allows us to deal with the uncertainty and incompleteness of fault information in an objective way without using historical statistics and expertise. Then, the srSNPS-based fault diagnosis method is proposed. It is composed of the transmission network partition, the SNPS model establishment, the pulse value correction and computing, and the protection device behavior evaluation, where the first two components can be finished before failures to save diagnosis time. Finally, case studies based on the IEEE 14- and IEEE 118-bus systems verify the effectiveness and superiority of the proposed method

Fault Diagnosis for Multi-energy Flows of Energy Internet: Framework and Prospects

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed.National Natural Science Foundation of China 61703345National Natural Science Foundation of China 61472328National Natural Science Foundation of China 5160714

The Tripartite Game Model for Electricity Pricing in Consideration of the Power Quality

Under the Energy Internet concept the distribution and management of resources in the electricity market have been gradually transiting from a centralized pattern to a decentralized pattern. Correspondingly, the methodological model for the analysis of economic behaviors needs to be upgraded too. Based on the idea of non-cooperative game theory, this paper puts forward a tripartite game model for electricity pricing in consideration of the power quality, which is applicable to the electricity market under the Energy Internet with distributed generation, including the State Grid Corporation of China (SGCC), generating companies (GENCOs) and the marketers which correspond to the regional power-retailing companies. Then, the sequential quadratic programming based on the quasi-Newton method is given to solve the game model. Finally, four sets of tests with different game factors are carried out to verify the validity and feasibility of the proposed model and algorithm. The SGCC price, the cost and the number of GENCOs and the cross-regional environment are considered in each test, respectively. The results show that this model can adapt well to the various conditions

Harmonic Source Localization Approach Based on Fast Kernel Entropy Optimization ICA and Minimum Conditional Entropy

Based on the fast kernel entropy optimization independent component analysis and the minimum conditional entropy, this paper proposes a harmonic source localization method which aims at accurately estimating harmonic currents and identifying harmonic sources. The injected harmonic currents are estimated by the fast kernel entropy optimization independent component analysis (FKEO-ICA) in the absence of prior knowledge of harmonic impedances. Then, the minimum conditional entropy is applied to locate the harmonic sources based on the estimated harmonic currents. The proposed harmonic source localization method is validated on the IEEE 34-bus system. By applying the correlation coefficient and three error evaluation indicators, comparison has been made among the performances of the FKEO-ICA and three other ICA algorithms. The results show that the FKEO-ICA algorithm could achieve a significantly better accuracy of harmonic current estimation, while the minimum conditional entropy could determine the locations of harmonic sources precisely

A Piecewise Bound Constrained Optimization for Harmonic Responsibilities Assessment under Utility Harmonic Impedance Changes

Considering the effect of the utility harmonic impedance variations on harmonic responsibility, a method based on piecewise bound constrained optimization is proposed in this paper to evaluate the load harmonic responsibilities. The wavelet packet transform is employed to determine the change times of the utility harmonic impedances. The harmonic monitoring data is divided into several segments where the utility harmonic impedances are considered as constants. Then, the problem of harmonic responsibility assessment under utility harmonic impedance changes are settled by the piecewise bound constrained optimization model. Furthermore, the interior point, the sequential quadratic programming and the active set algorithm are respectively adopted to calculate all the instantaneous harmonic responsibilities of harmonic loads. Finally, the weighted summation is used to calculate the total harmonic responsibility. To demonstrate the validity, simulation tests are carried out on an experimental circuit and the IEEE 13-bus distribution system

A Piecewise Bound Constrained Optimization for Harmonic Responsibilities Assessment under Utility Harmonic Impedance Changes

Considering the effect of the utility harmonic impedance variations on harmonic responsibility, a method based on piecewise bound constrained optimization is proposed in this paper to evaluate the load harmonic responsibilities. The wavelet packet transform is employed to determine the change times of the utility harmonic impedances. The harmonic monitoring data is divided into several segments where the utility harmonic impedances are considered as constants. Then, the problem of harmonic responsibility assessment under utility harmonic impedance changes are settled by the piecewise bound constrained optimization model. Furthermore, the interior point, the sequential quadratic programming and the active set algorithm are respectively adopted to calculate all the instantaneous harmonic responsibilities of harmonic loads. Finally, the weighted summation is used to calculate the total harmonic responsibility. To demonstrate the validity, simulation tests are carried out on an experimental circuit and the IEEE 13-bus distribution system

Security Risk Assessment Approach for Distribution Network Cyber Physical Systems Considering Cyber Attack Vulnerabilities

With the increasing digitalization and informatization of distribution network systems, distribution networks have gradually developed into distribution network cyber physical systems (CPS) which are deeply integrated with traditional power systems and cyber systems. However, at the same time, the network risk problems that the cyber systems face have also increased. Considering the possible cyber attack vulnerabilities in the distribution network CPS, a dynamic Bayesian network approach is proposed in this paper to quantitatively assess the security risk of the distribution network CPS. First, the Bayesian network model is constructed based on the structure of the distribution network and common vulnerability scoring system (CVSS). Second, a combination of the fuzzy analytic hierarchy process (FAHP) and entropy weight method is used to correct the selectivity of the attacker to strike the target when cyber attack vulnerabilities occur, and then after considering the defense resources of the system, the risk probability of the target nodes is obtained. Finally, the node loads and node risk rates are used to quantitatively assess the risk values that are applied to determine the risk level of the distribution network CPS, so that defense strategies can be given in advance to counter the adverse effects of cyber attack vulnerabilities

Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory

The increasing factors of uncertainty faced by the system are due to the deep coupling of the electric power cyber network and the physical network. Consequently, ensuring the efficient, secure, and stable operation of the cyber–physical power system (CPPS) has become a key concern. To achieve this, vulnerability assessment plays a crucial role, as it identifies and protects the vulnerable points of the system. The application of complex network theory to assess the vulnerability of CPPSs has garnered significant attention from scholars. This paper delves into the research connotation of vulnerability assessment for CPPSs, starting with the origin, definition, and classification of vulnerability. Subsequently, the assessment framework of vulnerability based on complex network theory is presented, and the status of current domestic and international research in this field is summarized. Furthermore, the interrelationship between system vulnerability and cascading failures is analyzed from the perspective of complex network theory. In conclusion, the ideas of CPPS coupling modeling in vulnerability assessment are summarized, the concept of situation awareness is introduced, and a prospective approach for dynamic vulnerability assessment is proposed. This approach is based on situation awareness combined with complex network theory. Security protection and optimal operation of CPPSs based on vulnerability assessment are also discussed, along with the assessment of vulnerability within integrated energy cyber–physical systems (IECPSs)