This page has only limited features, please log in for full access.

Unclaimed
T. Huang
Department of Energy, Politecnico di Torino, Italy

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 28 April 2021 in Renewable and Sustainable Energy Reviews
Reads 0
Downloads 0

With the increasing penetration of distributed renewable resources (RES) and flexible loads, distribution networks are gradually developing into an active distribution network (ADN), which includes many microgrids (MGs). By considering the network structure, operational targets, and transactional relationship of the ADN, this paper proposes a “physical-transactional” scheme to promote RES consumption through specifically designed price mechanisms. The proposed price forming mechanisms consider the traditional transactions and incorporate the supply-demand ratio into the dynamic price forming process to better suit the highly penetrated renewable energy and small-scale local markets. Through this framework, each player can maximize his/her interest, such as system security, social welfare, the satisfaction of electricity consumption, etc., while renewable energy consumption and sharing can be maximumly promoted. The exponential penalty function-based decomposition and Lyapunov theory-based solution for the multilayer optimization model are employed to solve the inter-layer coordination and individual optimization simultaneously. Finally, a modified IEEE-69 system is taken as an example to verify that the proposed method. Our simulation shows that the proposed framework can promote renewable energy consumption and sharing and improve the social welfare of the ADN.

ACS Style

Y.J. Wu; X.Y. Liang; T. Huang; Z.W. Lin; Z.X. Li; Mohammad Farhad Hossain. A hierarchical framework for renewable energy sources consumption promotion among microgrids through two-layer electricity prices. Renewable and Sustainable Energy Reviews 2021, 145, 111140 .

AMA Style

Y.J. Wu, X.Y. Liang, T. Huang, Z.W. Lin, Z.X. Li, Mohammad Farhad Hossain. A hierarchical framework for renewable energy sources consumption promotion among microgrids through two-layer electricity prices. Renewable and Sustainable Energy Reviews. 2021; 145 ():111140.

Chicago/Turabian Style

Y.J. Wu; X.Y. Liang; T. Huang; Z.W. Lin; Z.X. Li; Mohammad Farhad Hossain. 2021. "A hierarchical framework for renewable energy sources consumption promotion among microgrids through two-layer electricity prices." Renewable and Sustainable Energy Reviews 145, no. : 111140.

Journal article
Published: 24 February 2021 in Energies
Reads 0
Downloads 0

As one of the major pieces of equipment in fully mechanized coal mining, the drum shearer plays a critical role in improving the efficiency and energy utilization in the coal mining production process. In this paper, an energy consumption model of a shearer, derived from the analysis of the cutting and traction resistances on the shearer during different processes within a working cycle, is established. Based on the derived model, control and coordination strategies between the two speeds are proposed to minimize the shearer’s energy consumption in unidirectional mining. The case study of a real coal mine shows that the proposed models are valid, and the optimal control of shearer speeds can effectively reduce the energy consumption by 5.16% in a working cycle. To gain further insights into the impact of traction speed and drum rotational speed on the shearer’s energy consumption, several speed coordination cases are employed to further compare with the optimized one. Our study results show that the energy consumption of a shearer can be decreased with the increase of traction speed while decreasing drum rotational speed in coordination.

ACS Style

Zheng Zheng; Dilei Chen; Tao Huang; Guopeng Zhang. Coordinated Speed Control Strategy for Minimizing Energy Consumption of a Shearer in Fully Mechanized Mining. Energies 2021, 14, 1224 .

AMA Style

Zheng Zheng, Dilei Chen, Tao Huang, Guopeng Zhang. Coordinated Speed Control Strategy for Minimizing Energy Consumption of a Shearer in Fully Mechanized Mining. Energies. 2021; 14 (5):1224.

Chicago/Turabian Style

Zheng Zheng; Dilei Chen; Tao Huang; Guopeng Zhang. 2021. "Coordinated Speed Control Strategy for Minimizing Energy Consumption of a Shearer in Fully Mechanized Mining." Energies 14, no. 5: 1224.

Journal article
Published: 31 July 2020 in Applied Energy
Reads 0
Downloads 0

Greenhouse gases along with pollution generated by the present energy paradigm widely based on fossil fuels are providing large impacts in terms of climate change and the health of human and biological systems at large. A shift in the energy paradigm, from fossil fuels to renewable energy, is urgently needed for nature and society. This is what we refer to as the energy transition. An old commodity – electricity – can play a new key role in the energy transition. That can happen through what we call the electricity triangle involving electricity generation from Renewable Energy Sources, exploitation of electricity as the main energy vector, and electrification of the final energy uses in all sectors. The possible deployment of the electricity triangle must be carefully assessed in all its possible implications, from technological, economic, societal and environmental perspectives. In this paper, we conceptualize the electricity triangle as a viable approach to the energy transition, and we propose a set of holistic metrics to assess its possible impacts. We apply the electricity triangle framework to the case of Italy based on sectorial studies on RES generation and electrification in building, industry and transport sectors. Our results indicate that Italy in 2050 has the potential to achieve 85.6% penetration of RES in its electricity supply, while 41%, 53% and 42% of the energy consumptions in transport, residential, and industry sectors will be electrified. Ultimately, this would lead to a 68% reduction in CO2 emissions compared to current levels.

ACS Style

E. Bompard; A. Botterud; S. Corgnati; T. Huang; M. Jafari; P. Leone; S. Mauro; G. Montesano; C. Papa; F. Profumo. An electricity triangle for energy transition: Application to Italy. Applied Energy 2020, 277, 115525 .

AMA Style

E. Bompard, A. Botterud, S. Corgnati, T. Huang, M. Jafari, P. Leone, S. Mauro, G. Montesano, C. Papa, F. Profumo. An electricity triangle for energy transition: Application to Italy. Applied Energy. 2020; 277 ():115525.

Chicago/Turabian Style

E. Bompard; A. Botterud; S. Corgnati; T. Huang; M. Jafari; P. Leone; S. Mauro; G. Montesano; C. Papa; F. Profumo. 2020. "An electricity triangle for energy transition: Application to Italy." Applied Energy 277, no. : 115525.

Journal article
Published: 10 July 2020 in IEEE Transactions on Smart Grid
Reads 0
Downloads 0

The load redistribution (LR) attack, as a special type of false data injection attacks, aims to distort the results of the security-constrained economic dispatch (SCED) and drive the system to non-optimal or even unsecure operating conditions by injecting false data to the node power injection and branch power flow measurements. The LR attack represents a great danger to the safe and reliable operation of the current power grid where the physical infrastructure is increasingly intertwined with cyber components. In this paper, we propose a novel pre-overload vulnerability graph (POV-graph) approach to systematically assess, evaluate, and quantify the system vulnerability under an LR attack. The proposed approach is formulated based on the specific overloading mechanism of the LR attack as well as their cascading patterns. A set of case studies are performed on the IEEE 39-bus, 118-bus, and RTS-96 systems to validate the effectiveness of the proposed approach. Simulation results have shown, for the first time that, by revealing the vulnerability correlations among branches, the proposed approach allows the system operator to better utilize the defense resources and focus on strengthening a limited number of vulnerable branches to enhance the system’s overall security against LR attacks.

ACS Style

Yigu Liu; Shibin Gao; Jian Shi; Xiaoguang Wei; Zhu Han; Tao Huang. Pre-Overload-Graph-Based Vulnerable Correlation Identification Under Load Redistribution Attacks. IEEE Transactions on Smart Grid 2020, 11, 5216 -5226.

AMA Style

Yigu Liu, Shibin Gao, Jian Shi, Xiaoguang Wei, Zhu Han, Tao Huang. Pre-Overload-Graph-Based Vulnerable Correlation Identification Under Load Redistribution Attacks. IEEE Transactions on Smart Grid. 2020; 11 (6):5216-5226.

Chicago/Turabian Style

Yigu Liu; Shibin Gao; Jian Shi; Xiaoguang Wei; Zhu Han; Tao Huang. 2020. "Pre-Overload-Graph-Based Vulnerable Correlation Identification Under Load Redistribution Attacks." IEEE Transactions on Smart Grid 11, no. 6: 5216-5226.

Journal article
Published: 07 May 2020 in IEEE Access
Reads 0
Downloads 0

The weather has an important impact on the failure probability of components of power systems and on the time interval of pre-arranged maintenance. Therefore, it is essential to evaluate the reliability of distribution networks considering the impact of the weather. In this paper, weather condition models suitable for evaluating the probability of component failure and the pre-arranged maintenance are constructed based on the degree of influence of the main weather elements on them. Further, based on historical reliability data and meteorological data, a component failure model and a pre-arranged maintenance model considering weather conditions and their impact on the health of a component are proposed. The case study on an actual distribution network in Nanjing, China shows the effectiveness and merit of the proposed method.

ACS Style

Yingjun Wu; Tingting Fan; Tao Huang. Electric Power Distribution System Reliability Evaluation Considering the Impact of Weather on Component Failure and Pre-Arranged Maintenance. IEEE Access 2020, 8, 87800 -87809.

AMA Style

Yingjun Wu, Tingting Fan, Tao Huang. Electric Power Distribution System Reliability Evaluation Considering the Impact of Weather on Component Failure and Pre-Arranged Maintenance. IEEE Access. 2020; 8 (99):87800-87809.

Chicago/Turabian Style

Yingjun Wu; Tingting Fan; Tao Huang. 2020. "Electric Power Distribution System Reliability Evaluation Considering the Impact of Weather on Component Failure and Pre-Arranged Maintenance." IEEE Access 8, no. 99: 87800-87809.

Journal article
Published: 28 April 2020 in Engineering Applications of Artificial Intelligence
Reads 0
Downloads 0

This paper focuses on power system fault diagnosis based on Weighted Corrective Fuzzy Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a graphic fault diagnosis method, called FD-WCFRSNPS. In the FD-WCFRSNPS, an rWCFRSNPS is proposed to model the logical relationships between faults and potential warning messages triggered by the corresponding protective devices. In addition, a matrix-based reasoning algorithm for the rWCFRSNPS is devised to reason about the fault alarm messages using parallel representations. Besides, a layered modeling method based on rWCFRSNPSs is developed to adapt to topological changes in power systems and a Temporal Order Information Processing Method based on Cause–Effect Networks is designed to correct fault alarm messages before the fault reasoning. Finally, in a case study considering a local subsystem of a 220kV power system, the diagnosis results of five test cases prove that the proposed FD-WCFRSNPS is viable and effective.

ACS Style

Tao Wang; Xiaoguang Wei; Jun Wang; Tao Huang; Hong Peng; Xiaoxiao Song; Luis Valencia Cabrera; Mario J. Pérez-Jiménez. A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies. Engineering Applications of Artificial Intelligence 2020, 92, 103680 .

AMA Style

Tao Wang, Xiaoguang Wei, Jun Wang, Tao Huang, Hong Peng, Xiaoxiao Song, Luis Valencia Cabrera, Mario J. Pérez-Jiménez. A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies. Engineering Applications of Artificial Intelligence. 2020; 92 ():103680.

Chicago/Turabian Style

Tao Wang; Xiaoguang Wei; Jun Wang; Tao Huang; Hong Peng; Xiaoxiao Song; Luis Valencia Cabrera; Mario J. Pérez-Jiménez. 2020. "A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies." Engineering Applications of Artificial Intelligence 92, no. : 103680.

Journal article
Published: 11 February 2020 in IEEE Access
Reads 0
Downloads 0
ACS Style

Yanbing Jia; Tao Huang; Yubo Li; Rongrong Ma. Parameter Setting Strategy for the Controller of the DFIG Wind Turbine Considering the Small-Signal Stability of Power Grids. IEEE Access 2020, 8, 31287 -31294.

AMA Style

Yanbing Jia, Tao Huang, Yubo Li, Rongrong Ma. Parameter Setting Strategy for the Controller of the DFIG Wind Turbine Considering the Small-Signal Stability of Power Grids. IEEE Access. 2020; 8 ():31287-31294.

Chicago/Turabian Style

Yanbing Jia; Tao Huang; Yubo Li; Rongrong Ma. 2020. "Parameter Setting Strategy for the Controller of the DFIG Wind Turbine Considering the Small-Signal Stability of Power Grids." IEEE Access 8, no. : 31287-31294.

Research article
Published: 21 January 2020 in Complexity
Reads 0
Downloads 0

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.

ACS Style

Wei Liu; Tao Wang; TianLei Zang; Zhu Huang; Jun Wang; Tao Huang; Xiaoguang Wei; Chuan Li. A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism. Complexity 2020, 2020, 1 -18.

AMA Style

Wei Liu, Tao Wang, TianLei Zang, Zhu Huang, Jun Wang, Tao Huang, Xiaoguang Wei, Chuan Li. A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism. Complexity. 2020; 2020 ():1-18.

Chicago/Turabian Style

Wei Liu; Tao Wang; TianLei Zang; Zhu Huang; Jun Wang; Tao Huang; Xiaoguang Wei; Chuan Li. 2020. "A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism." Complexity 2020, no. : 1-18.

Article
Published: 11 January 2020 in Computing
Reads 0
Downloads 0

Data-driven models are becoming of fundamental importance in electric distribution networks to enable predictive maintenance, to perform effective diagnosis and to reduce related expenditures, with the final goal of improving the electric service efficiency and reliability to the benefit of both the citizens and the grid operators themselves. This paper considers a dataset collected over 6 years in a real-world medium-voltage distribution network by the Supervisory Control And Data Acquisition (SCADA) system. A transparent, exploratory, and exhaustive data-mining workflow, based on data characterisation, time-windowing, association rule mining, and associative classification is proposed and experimentally evaluated to automatically identify correlations and build a prognostic–diagnostic model from the SCADA events occurring before and after specific service interruptions, i.e., network faults. Our results, evaluated by both data-driven quality metrics and domain expert interpretations, highlight the capability to assess the limited predictive capability of the SCADA events for medium-voltage distribution networks, while their effective exploitation for diagnostic purposes is promising.

ACS Style

Daniela Renga; Daniele Apiletti; Danilo Giordano; Matteo Nisi; Tao Huang; Yang Zhang; Marco Mellia; Elena Baralis. Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis. Computing 2020, 102, 1199 -1211.

AMA Style

Daniela Renga, Daniele Apiletti, Danilo Giordano, Matteo Nisi, Tao Huang, Yang Zhang, Marco Mellia, Elena Baralis. Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis. Computing. 2020; 102 (5):1199-1211.

Chicago/Turabian Style

Daniela Renga; Daniele Apiletti; Danilo Giordano; Matteo Nisi; Tao Huang; Yang Zhang; Marco Mellia; Elena Baralis. 2020. "Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis." Computing 102, no. 5: 1199-1211.

Journal article
Published: 02 December 2019 in Computers & Electrical Engineering
Reads 0
Downloads 0

To reveal the mechanism of fault propagation and temporal information between electrical network branches intuitively and vividly, we have proposed a fault chain-based cascading fault graph (CFG) that considers the topological, physical, and fault operational features from an overload mechanism perspective. The proposed CFG is used to construct metrics to identify vulnerable branches of an electrical network. Furthermore, because the vulnerable branch rankings change with the changing fault chain length, the ranking results’ change rules are investigated. As a result, the branch vulnerabilities’ characteristics are found to be different at different stages under sequential attacks. Inspired by the characteristics, the CFGs are divided into three sub-CFGs, based on load shedding threshold, to identify the vulnerable branches at different stages. The proposed method is used to identify the vulnerable branches of the IEEE 39- and 118-bus systems, and its effectiveness is validated by investigating load shedding of the systems under deliberate attacks.

ACS Style

Xiaoguang Wei; Shibin Gao; Tao Huang. Analysis of electrical network vulnerability using segmented cascading faults graph. Computers & Electrical Engineering 2019, 81, 106519 .

AMA Style

Xiaoguang Wei, Shibin Gao, Tao Huang. Analysis of electrical network vulnerability using segmented cascading faults graph. Computers & Electrical Engineering. 2019; 81 ():106519.

Chicago/Turabian Style

Xiaoguang Wei; Shibin Gao; Tao Huang. 2019. "Analysis of electrical network vulnerability using segmented cascading faults graph." Computers & Electrical Engineering 81, no. : 106519.

Journal article
Published: 02 December 2019 in IEEE Access
Reads 0
Downloads 0
ACS Style

Lei Chen; Jun Wang; Zhang Sun; Tao Huang; Fan Wu. Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN. IEEE Access 2019, 7, 172718 -172727.

AMA Style

Lei Chen, Jun Wang, Zhang Sun, Tao Huang, Fan Wu. Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN. IEEE Access. 2019; 7 ():172718-172727.

Chicago/Turabian Style

Lei Chen; Jun Wang; Zhang Sun; Tao Huang; Fan Wu. 2019. "Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN." IEEE Access 7, no. : 172718-172727.

Journal article
Published: 01 October 2019 in IEEE Access
Reads 0
Downloads 0

As the last link of an integrated future energy system, the smart home energy management system (HEMS) is critical for a prosumer to intelligently and conveniently manage the use of their domestic appliances, renewable energies (RES) generation, energy storage system (ESS), and electric vehicle (EV). In this paper, we propose a holistic model to center the preference of users when scheduling the involved physical equipment of different natures. Further, a dedicatedly designed charging and discharging strategy for both the ESS and EV considering their capital cost is proposed to integrate them into the HEMS for providing a better flexibility and economic advantages as well as to prolong the life of the batteries. Based on the mixed integer linear programming (MILP) and the proposed model, the energy schedule of the smart home can be derived to guarantee both the lowest cost and the comfort for the users. An illustrative case study is employed to demonstrate the effectiveness of the proposed method.

ACS Style

Xuan Hou; Jun Wang; Tao Huang; Tao Wang; Peng Wang. Smart Home Energy Management Optimization Method Considering Energy Storage and Electric Vehicle. IEEE Access 2019, 7, 144010 -144020.

AMA Style

Xuan Hou, Jun Wang, Tao Huang, Tao Wang, Peng Wang. Smart Home Energy Management Optimization Method Considering Energy Storage and Electric Vehicle. IEEE Access. 2019; 7 (99):144010-144020.

Chicago/Turabian Style

Xuan Hou; Jun Wang; Tao Huang; Tao Wang; Peng Wang. 2019. "Smart Home Energy Management Optimization Method Considering Energy Storage and Electric Vehicle." IEEE Access 7, no. 99: 144010-144020.

Journal article
Published: 22 August 2019 in IEEE Systems Journal
Reads 0
Downloads 0

This article proposes an adjacent graph based on the spontaneous faults of an electrical network to assess the electrical network vulnerabilities from the perspective of the overload mechanism. To reveal the propagation features and the adjacent relationships among branches from different angles, fault probability, load shedding, and topological structure-based indices are proposed to define the weights of the directed edges in the adjacent graph. On this basis, according to the physical features of the graph mapped to the electrical network, the improved betweenness based on the complex network theory is proposed to identify the critical branches of the electrical network. Numerical results on an IEEE 118-bus system demonstrate the effectiveness of the proposed method.

ACS Style

TianLei Zang; Shibin Gao; Tao Huang; Xiaoguang Wei; Tao Wang. Complex Network-Based Transmission Network Vulnerability Assessment Using Adjacent Graphs. IEEE Systems Journal 2019, 14, 572 -581.

AMA Style

TianLei Zang, Shibin Gao, Tao Huang, Xiaoguang Wei, Tao Wang. Complex Network-Based Transmission Network Vulnerability Assessment Using Adjacent Graphs. IEEE Systems Journal. 2019; 14 (1):572-581.

Chicago/Turabian Style

TianLei Zang; Shibin Gao; Tao Huang; Xiaoguang Wei; Tao Wang. 2019. "Complex Network-Based Transmission Network Vulnerability Assessment Using Adjacent Graphs." IEEE Systems Journal 14, no. 1: 572-581.

Journal article
Published: 01 July 2019 in IEEE Access
Reads 0
Downloads 0

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 which 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 French grid are employed to validate the effectiveness of the proposed method.

ACS Style

TianLei Zang; Jieyu Lei; Xiaoguang Wei; Tao Huang; Tao Wang; Mario J. Perez-Jimenez; Hua Lin. Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches. IEEE Access 2019, 7, 88927 -88936.

AMA Style

TianLei Zang, Jieyu Lei, Xiaoguang Wei, Tao Huang, Tao Wang, Mario J. Perez-Jimenez, Hua Lin. Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches. IEEE Access. 2019; 7 (99):88927-88936.

Chicago/Turabian Style

TianLei Zang; Jieyu Lei; Xiaoguang Wei; Tao Huang; Tao Wang; Mario J. Perez-Jimenez; Hua Lin. 2019. "Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches." IEEE Access 7, no. 99: 88927-88936.

Journal article
Published: 23 April 2019 in Reliability Engineering & System Safety
Reads 0
Downloads 0

This paper aims to identify the vulnerability of electrical cyber-physical systems (CPSs) through fault propagation under cyber attacks. First, we propose a fault propagation model mainly considering the impact of interruptions on some nodes of the cyber network on the electrical physical systems. Secondly, two graphs, i.e. propagation graph and attack graph are proposed to reveal the physical fault propagation mechanisms and analyze the attack intensity of combinations of different communication nodes, respectively. Thirdly, a set of traditional vulnerable indices based on the propagation and attack graphs are employed to identify both the critical physical branches and communication nodes in the CPS. Finally, comparative analyses with and without considering the CPS on both IEEE 118- and 300- bus systems show that the fault propagation among are more sophisticated and the wrong decisions that the control center makes causes the higher vulnerability of the electrical network due to the interruption of the transmission information in the cyber system under cyber attacks.

ACS Style

TianLei Zang; Shibin Gao; Baoxu Liu; Tao Huang; Tao Wang; Xiaoguang Wei. Integrated fault propagation model based vulnerability assessment of the electrical cyber-physical system under cyber attacks. Reliability Engineering & System Safety 2019, 189, 232 -241.

AMA Style

TianLei Zang, Shibin Gao, Baoxu Liu, Tao Huang, Tao Wang, Xiaoguang Wei. Integrated fault propagation model based vulnerability assessment of the electrical cyber-physical system under cyber attacks. Reliability Engineering & System Safety. 2019; 189 ():232-241.

Chicago/Turabian Style

TianLei Zang; Shibin Gao; Baoxu Liu; Tao Huang; Tao Wang; Xiaoguang Wei. 2019. "Integrated fault propagation model based vulnerability assessment of the electrical cyber-physical system under cyber attacks." Reliability Engineering & System Safety 189, no. : 232-241.

Journal article
Published: 26 March 2019 in IEEE Access
Reads 0
Downloads 0

Assessment of electrical network vulnerability based on complex network theory (CNT) has attracted increasing attention. However, CNT focuses on analyzing 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., impactability 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 impactability and susceptibility in CNT.

ACS Style

Xiaoguang Wei; Shibin Gao; Tao Huang; Tao Wang; TianLei Zang. Electrical Network Operational Vulnerability Evaluation Based on Small-World and Scale-Free Properties. IEEE Access 2019, 7, 181072 -181082.

AMA Style

Xiaoguang Wei, Shibin Gao, Tao Huang, Tao Wang, TianLei Zang. Electrical Network Operational Vulnerability Evaluation Based on Small-World and Scale-Free Properties. IEEE Access. 2019; 7 (99):181072-181082.

Chicago/Turabian Style

Xiaoguang Wei; Shibin Gao; Tao Huang; Tao Wang; TianLei Zang. 2019. "Electrical Network Operational Vulnerability Evaluation Based on Small-World and Scale-Free Properties." IEEE Access 7, no. 99: 181072-181082.

Research article
Published: 13 March 2019 in Complexity
Reads 0
Downloads 0

Communication networks as smart infrastructure systems play an important role in smart girds to monitor, control, and manage the operation of electrical networks. However, due to the interdependencies between communication networks and electrical networks, once communication networks fail (or are attacked), the faults can be easily propagated to electrical networks which even lead to cascading blackout; therefore it is crucial to investigate the impacts of failures of communication networks on the operation of electrical networks. This paper focuses on cascading failures in interdependent systems from the perspective of cyber-physical security. In the interdependent fault propagation model, the complex network-based virus propagation model is used to describe virus infection in the scale-free and small-world topologically structured communication networks. Meanwhile, in the electrical network, dynamic power flow is employed to reproduce the behaviors of the electrical networks after a fault. In addition, two time windows, i.e., the virus infection cycle and the tripping time of overloaded branches, are considered to analyze the fault characteristics of both electrical branches and communication nodes along time under virus propagation. The proposed model is applied to the IEEE 118-bus system and the French grid coupled with different communication network structures. The results show that the scale-free communication network is more vulnerable to virus propagation in smart cyber-physical grids.

ACS Style

Tao Wang; Xiaoguang Wei; Tao Huang; Jun Wang; Luis Valencia-Cabrera; Zhennan Fan; Mario J. Pérez-Jiménez. Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids. Complexity 2019, 2019, 1 -15.

AMA Style

Tao Wang, Xiaoguang Wei, Tao Huang, Jun Wang, Luis Valencia-Cabrera, Zhennan Fan, Mario J. Pérez-Jiménez. Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids. Complexity. 2019; 2019 ():1-15.

Chicago/Turabian Style

Tao Wang; Xiaoguang Wei; Tao Huang; Jun Wang; Luis Valencia-Cabrera; Zhennan Fan; Mario J. Pérez-Jiménez. 2019. "Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids." Complexity 2019, no. : 1-15.

Journal article
Published: 21 February 2019 in IEEE Access
Reads 0
Downloads 0
ACS Style

Xia Lei; Tao Huang; Yi Yang; Yong Fang; Peng Wang. A Bi-Layer Multi-Time Coordination Method for Optimal Generation and Reserve Schedule and Dispatch of a Grid-Connected Microgrid. IEEE Access 2019, 7, 44010 -44020.

AMA Style

Xia Lei, Tao Huang, Yi Yang, Yong Fang, Peng Wang. A Bi-Layer Multi-Time Coordination Method for Optimal Generation and Reserve Schedule and Dispatch of a Grid-Connected Microgrid. IEEE Access. 2019; 7 ():44010-44020.

Chicago/Turabian Style

Xia Lei; Tao Huang; Yi Yang; Yong Fang; Peng Wang. 2019. "A Bi-Layer Multi-Time Coordination Method for Optimal Generation and Reserve Schedule and Dispatch of a Grid-Connected Microgrid." IEEE Access 7, no. : 44010-44020.

Research article
Published: 16 January 2019 in Complexity
Reads 0
Downloads 0

This paper proposes a new framework to analyze two vulnerability features, impactability and susceptibility, in electrical networks under deliberate attacks based on complex network theory: these two features are overlooked but vital in vulnerability analyses. To analyze these features, metrics are proposed based on correlation graphs constructed via critical paths, which replace the original physical network. Moreover, we analyze the relationship between the proposed metrics according to degree from the perspective of load redistribution mechanisms by adjusting parameters associated with the metrics, which can change the load redistribution rules. Finally, IEEE 118- and 300-bus systems and a realistic large-scale French grid are used to validate the effectiveness of the proposed metrics.

ACS Style

Xiaoguang Wei; Shibin Gao; Tao Huang; Tao Wang; Wenli Fan. Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks. Complexity 2019, 2019, 1 -14.

AMA Style

Xiaoguang Wei, Shibin Gao, Tao Huang, Tao Wang, Wenli Fan. Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks. Complexity. 2019; 2019 ():1-14.

Chicago/Turabian Style

Xiaoguang Wei; Shibin Gao; Tao Huang; Tao Wang; Wenli Fan. 2019. "Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks." Complexity 2019, no. : 1-14.

Journal article
Published: 14 January 2019 in IEEE Access
Reads 0
Downloads 0

To reveal fault propagation paths is one of the most critical studies for the analysis of power system security; however, it is rather difficult. This paper proposes a new framework for the fault propagation path modeling method of power systems based on membrane computing. We first model the fault propagation paths by proposing the event spiking neural P systems (Ev-SNP systems) with neurotransmitter concentration, which can intuitively reveal the fault propagation path due to the ability of its graphics models and parallel knowledge reasoning. The neurotransmitter concentration is used to represent the probability and gravity degree of fault propagation among synapses. Then, to reduce the dimension of the Ev-SNP system and make them suitable for large-scale power systems, we propose a model reduction method for the Ev-SNP system and devise its simplified model by constructing single-input and single-output neurons, called reduction-SNP system (RSNP system). Moreover, we apply the RSNP system to the IEEE 14- and 118-bus systems to study their fault propagation paths. The proposed approach first extends the SNP systems to a large-scaled application in critical infrastructures from a single element to a system-wise investigation as well as from the post-ante fault diagnosis to a new ex-ante fault propagation path prediction, and the simulation results show a new success and promising approach to the engineering domain.

ACS Style

Tao Wang; Xiaoguang Wei; Tao Huang; Jun Wang; Hong Peng; Mario J. Perez-Jimenez; Luis Valencia-Cabrera. Modeling Fault Propagation Paths in Power Systems: A New Framework Based on Event SNP Systems With Neurotransmitter Concentration. IEEE Access 2019, 7, 12798 -12808.

AMA Style

Tao Wang, Xiaoguang Wei, Tao Huang, Jun Wang, Hong Peng, Mario J. Perez-Jimenez, Luis Valencia-Cabrera. Modeling Fault Propagation Paths in Power Systems: A New Framework Based on Event SNP Systems With Neurotransmitter Concentration. IEEE Access. 2019; 7 ():12798-12808.

Chicago/Turabian Style

Tao Wang; Xiaoguang Wei; Tao Huang; Jun Wang; Hong Peng; Mario J. Perez-Jimenez; Luis Valencia-Cabrera. 2019. "Modeling Fault Propagation Paths in Power Systems: A New Framework Based on Event SNP Systems With Neurotransmitter Concentration." IEEE Access 7, no. : 12798-12808.