Grid Vulnerability Research Articles

Study on the smart grid vulnerability index based on the moment-generating function and distortion function

Although smart grids are characterized by self-healing, economy, high efficiency, and security, many hidden dangers exist in the development of smart grids due to a gradually expanding power grid and the continuous access of new energy to the power grid. Therefore, the development of smart grids, especially their reliability, security, and vulnerability, warrants further investigation. In this study, the vulnerability of smart grids is identified, and the vulnerability elements of smart grids are selected. Based on relevant theories, such as credibility and the combination of the credibility-based moment-generating function and the distortion function, a calculation model and framework of the vulnerability index of a smart grid are constructed. An empirical analysis is also conducted. This study provides a scientific basis for analyzing the vulnerability of smart grids and suggesting reasonable preventive measures and auxiliary decision-making information for relevant planning, design, and operation personnel, which contributes to the sustainable and healthy development of smart grids.

Forced Oscillation Grid Vulnerability Analysis and Mitigation Using Inverter-Based Resources: Texas Grid Case Study

Forced oscillation events have become a challenging problem with the increasing penetration of renewable and other inverter-based resources (IBRs), especially when the forced oscillation frequency coincides with the dominant natural oscillation frequency. A severe forced oscillation event can deteriorate power system dynamic stability, damage equipment, and limit power transfer capability. This paper proposes a two-dimension scanning forced oscillation grid vulnerability analysis method to identify areas/zones in the system that are critical to forced oscillation. These critical areas/zones can be further considered as effective actuator locations for the deployment of forced oscillation damping controllers. Additionally, active power modulation control through IBRs is also proposed to reduce the forced oscillation impact on the entire grid. The proposed methods are demonstrated through a case study on a synthetic Texas power system model. The simulation results demonstrate that the critical areas/zones of forced oscillation are related to the areas that highly participate in the natural oscillations and the proposed oscillation damping controller through IBRs can effectively reduce the forced oscillation impact in the entire system.

Vulnerability analysis of power system by modified H-index method on cascading failure state transition graph

The mechanism of the cascades and the vulnerability of the power grids have been widely concerned due to the blackouts around the word in recent years. It is urgent to propose an effective method to estimate the vulnerability of the power grids. In this paper, a modified H-index method is proposed to identify the critical lines in power grids based on the cascading failure state transition graph. First, a two-level cascading failure state transition graph is constructed according to the power flow transfer on transmission lines after the cascading failures to describe the state transfer relationship when the transmission line is cut off. Then, the state transition graph is decomposed into the fault propagation graph and the fault infection graph, respectively in view of the infectiousness and propagation of the line faults. And a vulnerable line identification method is proposed based on the modified H-index method. Finally, the simulations on the IEEE-39 bus system and the NE power grid show that the transmission lines which are prone to propagate faults or have weak anti-interferences can be identified effectively by the proposed method.

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands’ grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios.

Technology Pathways Could Help Drive the U.S. West Coast Grid's Exposure to Hydrometeorological Uncertainty

AbstractPrevious studies investigating deep decarbonization of bulk electric power systems and wholesale electricity markets have not sufficiently explored how future grid pathways could affect the grid's vulnerability to hydrometeorological uncertainty on multiple timescales. Here, we employ a grid operations model and a large synthetic weather ensemble to “stress test” a range of future grid pathways for the U.S. West Coast developed by ReEDS, a well‐known capacity planning model. Our results show that gradual changes in the underlying capacity mix from 2020 to 2050 can cause significant “re‐ranking” of weather years in terms of annual wholesale electricity prices (with “good” years becoming bad, and vice versa). Nonetheless, we find the highest and lowest ranking price years in terms of average electricity price remain mostly tied to extremes in hydropower availability (streamflow) and load (summer temperatures), with the strongest sensitivities related to drought. Seasonal dynamics seen today involving spring snowmelt and hot, dry summers remain well‐defined out to 2050. In California, future supply shortfalls in our model are concentrated in the evening and occur mostly during periods of high temperature anomalies in late summer months and in late winter; in the Pacific Northwest, supply shortfalls are much more strongly tied to negative streamflow anomalies. Under our more robust sampling of stationary hydrometeorological uncertainty, we also find that the ratio of dis‐patchable thermal (i.e., natural gas) capacity to wind and solar required to ensure grid reliability can differ significantly from values reported by ReEDS.

Impact and Vulnerability Analysis of IEC61850 in Smartgrids Using Multiple HIL Real-Time Testbeds

Due to the increasing use of smart components in smart grids, interoperability among them is a crucial aspect to address. IEC61850 is a communication standard that has been already used in substations because of its instant data transfer and the ability to enable data exchange between a variety of smart energy-related digital technologies. This article studies the application of the communication protocols defined by the IEC61850 standard in Intelligent Electronic Devices (IEDs) by using a prototype testbed architecture running on a real-time digital device. The goal of this activity is to study the impact of smart simulations and the vulnerability in terms of cyber-security. This testbed includes the supervisor, the substation bus, and the process bus communication layer creating a local network exchanging data at distinct levels. Different fault protection scenarios are discussed using both physical and emulated IEDs, and the communication protocols implemented in each scenario are explained showing that additional delays are introduced. In the first two scenarios, the operation of the testbed using physical versus emulated IEDs is analyzed and compared, ensuring the robustness of this methodology in situations where the use of a physical IED would be unfeasible. In these scenarios, the functionality and robustness of the protection mechanisms and communication protocols are confirmed. In the third scenario vulnerability of smart grids that use IEC61850 as their primary communication protocol to data injection attacks is studied. Sniffing the local network, packets are captured and monitored. Spoofed data with the same structure are injected into the network to conduct false data injection attacks on the supervisory unit. Vulnerability to cyber attacks of the IEC61850 protocol in specific situations is shown.

Electric vehicle attack impact on power grid operation

The increasing need for reducing greenhouse gas emissions and the drive for green cities have promoted the use of electric vehicles due to their environmental benefits. In fact, countries have set their own targets and are offering incentives for people to purchase EVs as opposed to traditional gasoline-powered cars. Manufacturers have been hastily deploying charging stations to meet the charging requirements of the EVs on the road. This rapid deployment has contributed to the EV ecosystem’s lack of proper security measures. raising multiple questions related to the power grid security and vulnerability. In this paper, we offer a complete examination of the EV ecosystem from the vulnerability to the attacks and finally the solutions. We start by examining the existing vulnerabilities in the EV ecosystem that can be exploited to control the EV charging and launch attacks against the power grid. We then discuss the non-linear nature of the EV charging load and simulate multiple attacks that can be launched against the power grid using these EVs. EV loads have high reactive power demand which can have a larger impact on the grid compared to residential loads. We perform simulations on two power grids and demonstrate that while the grid can recover after a 48 MW attack utilizing traditional residential loads, a smaller 30 MW EV load attack can completely destabilize the system. Finally, we suggest several patches for the existing vulnerabilities and discuss two methods aimed at detecting EV attacks.

A Multi-Layer Security Scheme for Mitigating Smart Grid Vulnerability against Faults and Cyber-Attacks

To comply with electric power grid automation strategies, new cyber-security protocols and protection are required. What we now experience is a new type of protection against new disturbances namely cyber-attacks. In the same vein, the impact of disturbances arising from faults or cyber-attacks should be surveyed by network vulnerability criteria alone. It is clear that the diagnosis of vulnerable points protects the power grid against disturbances that would inhibit outages such as blackouts. So, the first step is determining the network vulnerable points, and then proposing a support method to deal with these outages. This research proposes a comprehensive approach to deal with outages by determining network vulnerable points due to physical faults and cyber-attacks. The first point, the network vulnerable points against network faults are covered by microgrids. As the second one, a new cyber-security protocol named multi-layer security is proposed in order to prevent targeted cyber-attacks. The first layer is a cyber-security-based blockchain method that plays a general role. The second layer is a cyber-security-based reinforcement-learning method, which supports the vulnerable points by monitoring data. On the other hand, the trend of solving problems becomes routine when no ambiguity arises in different sections of the smart grid, while it is far from a big network’s realities. Hence, the impact of uncertainty parameters on the proposed framework needs to be considered. Accordingly, the unscented transform method is modeled in this research. The simulation results illustrate that applying such a comprehensive approach can greatly pull down the probability of blackouts.

Preventive Control Strategy of Cascading Fault considering Safety and Economy

The operation and structure of the power system are becoming increasingly complex, and the probability of cascading fault increases. To this end, this paper proposes a cascading fault preventive control strategy that considers safety and the economy. First is to give a mathematical form to discriminate the cascading fault according to the action characteristics of the current-type backup protection. Second, the safety and economy of the system are evaluated in terms of power grid safety margin and generation operation cost, respectively, the initial faults are selected based on the power grid vulnerability and safety margin, and a cascading fault preventive control model is constructed for different initial faults’ scenarios. The model is a two-layer optimization mathematical model, with the inner model being solved by particle swarm optimization to minimize the power grid safety margin. The outer model is solved by the multiobjective algorithm to minimize generation cost and maximizing power grid safety margin. Finally, the calculated Pareto set is evaluated using fuzzy set theory to determine the optimal generator output strategy. The feasibility of the proposed method is verified by conducting a simulation study with the IEEE39 node system as an example.

Stochastic optimal transmission Switching: A novel approach to enhance power grid security margins through vulnerability mitigation under renewables uncertainties

In this paper, a stochastic optimal transmission switching (SOTS) model is developed considering the uncertainty of load, wind power and photovoltaic generation, while minimizing the grid vulnerability. Scenario reduction technique is used for alleviating computational burden of the developed SOTS model. A three-step procedure, named the vulnerability-oriented SOTS (VO-SOTS), is proposed to consider the set of critical transmission lines, i.e., lines whose outage imposes the largest load curtailment. Moreover, to control the negative impacts of the uncertainties, conditional value at risk (CVaR) is used as the risk measure. The proposed VO-SOTS model is formulated as a mixed integer non-linear programming optimization problem and solved using GAMS optimization package. Also, the VO-SOTS model is implemented on the IEEE 118-bus, IEEE 300-bus, and large-scale IEEE 2869-bus standard test systems. Simulation results for these cases show that considering the set of critical lines allows the proposed VO-SOTS model to reduce generation costs while effectively minimizing system vulnerability and risk. In addition, it is shown through extensive case studies that switching off a line based on the proposed three-step VO-SOTS does not increase the grid’s exposure to vulnerability, in contrast to the conventional OTS.

Engineering Microgrids With Control Co-Design: Principles, methods, and metrics [Technology Leaders

The vulnerability of electrical grids to natural disasters, physical and cyberattacks, and other potential failures has become an increasingly concerning issue. Microgrids can provide the necessary resilience to critical public and private infrastructures while also offering grid-support services and economic and environmental benefits.

Cyber-Physical Vulnerability Assessment in Smart Grids Based on Multilayer Complex Networks.

In the last decade, the main attacks against smart grids have occurred in communication networks (ITs) causing the disconnection of physical equipment from power networks (OTs) and leading to electricity supply interruptions. To deal with the deficiencies presented in past studies, this paper addresses smart grids vulnerability assessment considering the smart grid as a cyber-physical heterogeneous interconnected system. The model of the cyber-physical system is composed of a physical power network model and the information and communication technology network model (ICT) both are interconnected and are interrelated by means of the communication and control equipment installed in the smart grid. This model highlights the hidden interdependencies between power and ICT networks and contains the interaction between both systems. To mimic the real nature of smart grids, the interconnected heterogeneous model is based on multilayer complex network theory and scale-free graph, where there is a one-to-many relationship between cyber and physical assets. Multilayer complex network theory centrality indexes are used to determine the interconnected heterogeneous system set of nodes criticality. The proposed methodology, which includes measurement, communication, and control equipment, has been tested on a standardized power network that is interconnected to the ICT network. Results demonstrate the model’s effectiveness in detecting vulnerabilities in the interdependent cyber-physical system compared to traditional vulnerability assessments applied to power networks (OT).

How does the vulnerability of an evolving power grid change?

Topological robustness and fault tolerance of the power system are amongst the most studied topics when it comes to the assessment of grid vulnerability. The use of adequate methods and performance metric can greatly contribute to a number of actions, including operation planning, grid development and other specific measures. A shortcoming of several studies is that they fail to take the aspects of network evolution into consideration. In this paper the seven-decade historical dataset (1949–2019) of the Hungarian power system is used to perform vulnerability assessment applying a complex network approach. Damage tolerance of the network is examined against node and edge removals. The results show that the evolving grid has increased its tolerance against large disturbances very early, but vulnerability values show little variance from 1979, despite that the size of the network has increased significantly. It is also found that more efficient and more robust topologies impose slightly conflicting conditions for grid development planning.

Vulnerability and stability of power grids modeled by second-order Kuramoto model: a mini review

Vulnerability and stability of power grids modeled by second-order Kuramoto model: a mini review

Monitoring 4.0 of penstocks: digital twin for fatigue assessment

In Europe, the ambitious goal of targeting at least 64% of electricity production from renewables by 2050 requires some significant increase of power network ancillary services. A general extension of primary/secondary reserves is necessary to cope with the increasing penetration of stochastic renewable energies and maintain the grid vulnerability at acceptable levels. In this context, hydropower plants are called upon to play a major role due to their operational flexibility and ability to provide ancillary services. However, the provision of these services is not without consequences for the plant, as the increase of load variations and start/stop sequences enhances fatigue problems by soliciting the penstocks faster than originally expected. Given that the fatigue wear rate can be 10x higher when ancillary services are active, it is crucial to ensure the fitness-for-service of the penstocks by proper monitoring. Nevertheless, the number of sensors along the hydraulic circuit is often very limited, so that periodic stops of the plant and inspections are necessary to assess the health of the pipes. In this paper, we present how a digital twin of the power plant, namely the Hydro-Clone system, can be used to fill this gap by enabling real-time knowledge of the transient pressures throughout the water conduits. These pressures are correlated to the stress variations using either analytical formula or finite element modelling (FEM), depending on the geometry and embedding conditions of each penstock element. The validity of this approach is demonstrated by comparing the predicted stresses with measured values in the penstock of the 200 MW La Bâtiaz hydropower plant, owned by Electricité d’Emosson SA. To this end, strain gages are mounted at the bottom and top of the penstock, in front of the manifold and on the penstock protection valve. The appropriate conversion of pressure to stress at the strain gage location is derived through the analysis of FEM simulations. This work shows the benefits of using a digital twin for fatigue assessment and paves the way for real-time penstocks fatigue monitoring.

Stateflow-Based Energy Management Strategy for Hybrid Energy System to Mitigate Load Shedding

This study investigates the potential application of Stateflow (SF) to design an energy management strategy (EMS) for a renewable-based hybrid energy system (HES). The SF is an extended finite state machine; it provides a platform to design, model, and execute complex event-driven systems using an interactive graphical environment. The HES comprises photovoltaics (PV), energy storage units (ESU) and a diesel generator (Gen), integrated with the power grid that experiences a regular load shedding condition (scheduled power outages). The EMS optimizes the energy production and utilization during both modes of HES operation, i.e., grid-connected mode and the islanded mode. For islanded operation mode, a resilient power delivery is ensured when the system is subjected to intermittent renewable supply and grid vulnerability. The contributions of this paper are twofold: first is to propose an integrated framework of HES to address the problem of load shedding, and second is to design and implement a resilient EMS in the SF environment. The validation of the proposed EMS demonstrates its feasibility to serve the load for various operating scenarios. The latter include operations under seasonal variation, abnormal weather conditions, and different load shedding patterns. The simulation results reveal that the proposed EMS not only ensures uninterrupted power supply during load shedding but also reduces grid burden by maximizing the use of PV energy. In addition, the SF-based adopted methodology is envisaged to be a useful alternative to the popular design method using the conventional software tools, particularly for event-driven systems.

Review of Cyber-Physical Attacks in Smart Grids: A System-Theoretic Perspective

This paper presents a review of technical works in the field of cyber-physical attacks on the smart grid. The paper starts by discussing two reference mathematical frameworks proposed in the literature to model a smart grid under attack. Then, a review of cyber-physical attacks on the smart grid is presented, starting from works on false data injection attacks against state estimation. The aim is to present a systematic and quantitative discussion of the basic working principles of the attacks, also in terms of the inner smart grid vulnerabilities and dynamical properties exploited by the attack. The main contribution of the paper is the attempt to provide a unifying view, highlighting the fundamental aspects and the common working principles shared by the attack models, even when targeting different subsystems of the smart grid.

THREE-LEVEL METHODOLOGY FOR SECURE AND EFFICIENT GRID INTEGRATION OF ELECTRIC VEHICLE

The secure integration of electric vehicle (EV) plays a key role in the energy transition through a resilient and decarbonised economy. However, a massive EV penetration means a rise in electricity demand with negative consequences to the distribution systems (voltage drops, branches congestion, etc) if the charging infrastructure is not cybersecure and does not perform smart charging mechanisms. Furthermore, these new infrastructures and their operating procedures provide new chances to cyberattacks to be performed, aimed at either exploiting those grid vulnerabilities or acquiring some user’s private information. Therefore, to ease the secure integration of EV charging infrastructures in the future network, this paper presents a three-level actuation methodology for charging infrastructures, which includes active management of EV supply equipment (EVSE) to allow dynamic control of charges, installation of ancillary protection systems, planning of EVSE’s location within the distribution system and cybersecure management of the whole infrastructure. The presented methodology is based on a thorough analysis of the possible cyberattacks that may occur during the transactions of the charging process, as well as tests carried out on a real pilot, which demonstrate the possible impacts that an uncontrolled charging of the EV can have on the distribution network, thus identifying the vulnerabilities of the distribution network. Keywords: Smart Grid, electrification, electric vehicle, charging station, Charge point operator, cybersecurity, smart charging.

Empirical Electrical-Based Framework to Judge the Ability of Centrality Measures in Predicting Grid Vulnerability

We develop an empirical electrical-based framework to compare between centrality measures as to judge their ability to predict the vulnerability of smart grids and their elements under various attacks. The centrality measures considered are based on a weighted graph adjacency matrix representing the real power flows. The vulnerability is measured by the post-attack unsatisfied load (UL), which is determined through steady-state simulation using the MatPower v6.0. We introduce a generalized vulnerability curve as a plot of measures of electrical damage (e.g., the UL), versus physical damage. We consider various measures of physical damage such as the Fraction of Elements (FOE) removed and sums of centrality scores of elements removed. The area under the vulnerability curve (denoted as VPM) is shown to be a logical, reliable, and consistent indicator of the predictive power of a centrality measure. The VPM is simulated for several attacks including the Remove Most Central Elements First (RMCEF) attack. We show that degree centrality is the most predictive, when compared to eigenvector and betweenness centralities. Moreover, the degree-based RMCEF attack is the worst among the RMCEF and 5400 random attacks. The FOE-degree centrality VPM is the most predictive as well as the most computationally efficient.

Smart power grid vulnerability analysis in composite system through power grid modelling

<p>Though the number of traditional literature reviews most of the researchers in this area have concluded that modern intelligent electric network a referred standard new model which is considering for proposed power flow model analysis of Smart power grid vulnerability through composite network. By the theorem of Max-Flow and complex power network theorems that are represented the advance vulnerability indices for pick out endangered lines of the smart grid network. In other hand, the power flow model and existing models simulation are examined on the IEEE 39-bus test model. The results of the simulation introduced that the proposed concept of grid model, estimation and the index application are more adequate in smart grid weakness power and efficiency analysis. In this paper briefly summarize the methods and probabilities of a vulnerability index which was explained in specific in references. Therefore, it is imperative to further implement new models and new tools so as to reach the novel state and moderate the huge or massive potential shutoff.</p>