Cascading Outages Research Articles

An Optimal Control Approach to Identify the Worst-Case Cascading Failures in Power Systems

Cascading failures in power systems normally occur as a result of initial disturbances or faults on electrical elements, closely followed by situational awareness errors of human operators. It remains a great challenge to systematically trace the source of cascading failures in power systems. In this paper, we develop a mathematical model to describe the cascading outages of transmission lines in power networks. In particular, the direct current power-flow equation is employed to calculate the power flow on the branches. By regarding the disturbances on branches as the control inputs, the problem of identifying the initial disruptive disturbances is formulated with optimal control theory, which provides a systematic approach to explore the most disruptive disturbances that give rise to changes of branch admittance in addition to direct branch outages. Moreover, an iterative search algorithm is proposed to look for the optimal solution leading to the worst-case cascading failures. Theoretical analysis guarantees the asymptotic convergence of the iterative search algorithm. Finally, numerical simulations are carried out on the IEEE test systems to validate the proposed approach.

Sub-Synchronous Control Interaction Detection: A Real-Time Application

Power grids have recently become more susceptible to sub-synchronous control interactions (SSCI) due to the increasing penetration of renewable resources and series-compensated lines. SSCI is a purely electrical and fast-growing phenomenon. Therefore, without an expeditious detection and mitigation solution, it can cause serious damage to renewable and transmission facilities, consequently leading to cascading outages. This paper proposes an effective algorithm to detect SSCI within 45 ms and reliably send a trip signal within 95 ms. First, a comprehensive SSCI analysis is suggested to improve the preprocessing of the measured signal. Then, the proposed algorithm utilizes mode identification approaches in conjunction with a moving fast fourier transform (FFT) to capture and process the frequency and magnitude of oscillations to issue a reliable trip command in the case of an SSCI event. To evaluate the algorithm, a portion of the Electric Reliability Council of Texas (ERCOT) grid with relatively high penetration of renewable generation resources is utilized. The proposed detection algorithm is implemented on a real-time target device and is tested with an SSCI signal from the ERCOT grid under real-time operating conditions. The results indicate the efficiency and accuracy of the method with successful detection within the acceptable time frame.

Impact of Cascading and Common-Cause Outages on Resilience-Constrained Optimal Economic Operation of Power Systems

Common-cause and cascading outages in extreme power system conditions may challenge traditional N-k transmission security strategies. This paper proposes a resilience index (RI) to evaluate the power system adaptability to extreme conditions and establishes the resilience-constrained economic dispatch (RCED) model and solution methodology in power system operations. A three-stage outage sampling method is presented to assess the proposed RI in severe weather conditions culminating in common-cause and cascading outages. In the proposed RCED model, customized contingency constraints are introduced to represent common-cause and cascading outages in extreme events and two penalty terms are considered that can adjust power transmission flows for lowering outage risks in a power grid. An optimization method is presented to solve the RCED model efficiently with an absolute value function introduced in both objective function and constraints. A sufficient and necessary condition is proposed to ensure the optimality of the linearized solution is the same as that of the original problem. Case studies show the effectiveness of the proposed model and methodology.

An Intrusion Detection Method for Line Current Differential Relays

The U.S. Department of Homeland Security (DHS) has recently identified digital relays as targets vulnerable to cyber-attacks. The DHS has also noted that attacks to multiple relays can bring about cascading outages of transmission lines, leading to blackouts. As a result, making protective relays cyber-resilient is a prominent security issue in power networks. Line current differential relays (LCDRs) are among the potentially vulnerable digital relays that are increasingly deployed for protecting critical transmission lines. LCDRs, however, lack the required resiliency against cyber attacks, due to their high dependence on communication systems. This paper unveils that such susceptibilities can result in unwarranted trip signals through false data injection attacks (FDIAs), and so cause instability if several attacks are coordinated. It also presents a solution for detecting FDIAs and distinguishing them from real internal faults. To detect attacks, the proposed method compares the estimated and locally measured voltages at an LCDR’s terminal for both the positive sequence (PS) and negative sequence (NS). To estimate the local voltage for each sequence, the proposed technique uses an unknown input observer (UIO), the state-space model of the faulty line, and remote and local measurements, all associated with that sequence. The difference between the measured and estimated local voltages for each sequence remains close to zero during real internal faults because, in this condition, the state-space model based on which the UIO operates correctly represents the line. Nevertheless, the state-space model mismatch during FDIAs leads to a large difference between measured and estimated values in both sequences. The effectiveness of the proposed method is corroborated using simulation results for the IEEE 39-bus network.

A model predictive approach to protect power systems against cascading blackouts

Large scale blackouts normally go through several sequential phases according to the propagation speed of branch outages and the disruption level of power grids. It is crucial to eliminate the propagation of cascading outages in its infancy. In this paper, a model predictive approach is proposed to protect power grids against cascading blackouts. First of all, the cascading dynamics of power grids is described by the outage model of transmission lines and the DC power flow equation, which allows us to predict the cascading failure path. Then a nonlinear convex optimization formulation is established to terminate the cascading outages by adjusting the injected power on buses. Afterwards two protection schemes are designed according to the optimization formulation: one scheme carries out protective actions to terminate cascading outages once for all, while the other takes protection measures in two consecutive steps. Saddle point dynamics is employed to provide a numerical solution to the proposed optimization problem, and its global convergence is guaranteed in theory. Finally, numerical simulations on IEEE test systems are implemented to validate the proposed approach.

New sequential approach based on graph traversal algorithm to investigate cascading outages considering correlated wind farms

One of the effective methods to reduce the risk of load shedding and its subsequent blackout is to evaluate the risk of cascading outages and detection of key links in a power system. This risk assessment is getting more complicated considering the plans for integration of high wind energy. Therefore, in this study, a new sequential time approach has been proposed to evaluate risk of cascading outages considering the high penetration of correlated wind farms. The cascading processes are investigated using the extended OPA model using the graph traversal algorithm. Therefore, the problem of non-convergence situations caused by the island formation is resolved. To deal with the future wind farms integration, a correlation is defined between them by a proposed method based on the Copula theory. The numerical results confirm that in evaluation of risk, the limited scenarios cannot always be reliable. The extended OPA model is then compared with a simple OPA to confirm the importance of islanding detection in the cascade simulation. Different aspects of cascading outages, i.e. fractional load shedding, cascade propagation level and number of line interruptions have been investigated. Finally, the impact of wind penetration and correlation of wind farms on results have been presented.

A novel searching method of fault chains for power system Cascading outages based on quantitative analysis of dynamic interaction between system and components

Because the traditional searching method of fault chains for cascading outages usually only consider theover-load protection or simulate the action of protection and control deterministically, a novel searching method of fault chains for power system cascading outages which is based on quantitative analysis of dynamic interaction between system and components is proposed. Based on fault chain model, an evaluating index is established. This index is used to quantize the action situation of protection and control of key elements. Furthermore, according to the index, the action probability of protection and control of key elements under critical condition is figured out to confirm subsequent events of fault chains for cascading outages. Finally, high risk fault chains are screened out based on the risk index. Taken some actual power system under the summer peak load condition in 2017 as an example, the simulation result proves reliability and effectiveness of the proposed method.

Reducing Short Circuit Level in 400 kV Iraqi Grid System by Using FACTS Device

Electrical power systems are different in their sizes because of their amount of generation power stations, substations, transmission lines and loads. Therefore, these factors may impact on short circuit levels values. Capacity of power stations and dummy transmission lines in Extra high voltage grid (400kV) of the Iraqi Electrical power grids cause high short circuit levels values such that exceed both rating of the peak and breaking capacity of switchgear equipment's. Reduction of short-circuit levels by using Fast-acting Flexible Alternating Current Transmission Systems (FACTS) types devices in power grids maintain the operation of power grids with acceptable value of short circuit levels for their electrical equipment's and preventing cascading event outages which may lead to blackouts. This paper mainly studies strategies on how to add Short Circuit Current Limiter (SCCL) device by determining its number, value and location of connection in power grids by programing with (PSS™E version 30.3 Package Program). IEEE 25-bus system is used for testing the adding series SCCL at power transmission lines method procedure. The results of adding series SCCL with power transmission lines give significant reducing short circuit levels for the stations have highest short circuit levels in order to prevent the blackouts of overall power grid.

Fast Screening of Vulnerable Transmission Lines in Power Grids: A PageRank-Based Approach

In power system operation, there are usually a few vulnerable lines (VLs) which are prone to exacerbate the propagation of cascading failures and lead to severe blackouts with high probability. To facilitate preventing the power grid from cascading blackouts, in this paper, a PageRank-based fast screening method is derived to identify VLs. To this end, we extend the concept of interaction graph to model cascading outages as a directed weighted graph, where impacts of hidden failures are first taken into account. Based on the graph, we modify the celebrated PageRank algorithm to derive an ultra-fast VLs screening algorithm for large-scale power grids. Simulations carried out on the IEEE 118-bus system show that the proposed method can achieve high-accuracy VLs screening while the speed can be enhanced for several orders of magnitude compared with cascading failure simulation methods. Tests on a 1122-bus real power grid in China demonstrate that it can discriminate the most VLs in a practical power grid within only several minutes, showing its great potential for on-line application.

Evaluation of power system robustness in order to prevent cascading outages

Power system robustness against overload condition is a challenging issue in the fields of power system planning and operation. In this paper, two indices are proposed to evaluate power system robustness. The proposed indices are used to identify critical lines whose failure is due to overload, leading the power system to cascading outages and blackout. The first proposed index is a linear index. The second index is based on graph theory metrics. To prevent cascading outages, system robustness is calculated for all N-1 and N-2 contingencies. The lines whose outages lead to the smallest robustness values are considered as critical lines. The proposed indices are validated by applying to the IEEE 118-bus test system. Simulation results demonstrate the capability of both indices in identifying critical lines. Therefore, the purposed indices could be used as a reliable metric to apply preventive actions against possible cascading outages and blackouts.

Mitigation of Cascading Outages Using a Dynamic Interaction Graph-Based Optimal Power Flow Model

Online decision support for effective mitigation actions against propagating cascading outages in a power grid still poses a big challenge to grid operators. This paper proposes an online mitigation strategy against cascading outages using an optimal power flow model based on a Dynamic Interaction Graph. For a given power grid, its interaction graph, also called an interaction model, was proposed in recent literature, which is composed of components and links that have large contributions to outage propagation. Differing from a conventional interaction graph, a Dynamic Interaction Graph can adaptively update its parameters with changes of grid topology and hence is more accurate in online identification of the most vulnerable transmission lines and likely outage propagation paths for mitigation. Further, the paper introduces an optimal power flow model based on the proposed Dynamic Interaction Graph for determining the optimal control strategy to maintain transfer margins of vulnerable transmission lines and effectively mitigate outage propagation. The numerical results on the IEEE 118-bus system demonstrate the effectiveness of the proposed models and associated control strategy.

Analysis on Integrated Energy System Cascading Failures Considering Interaction of Coupled Heating and Power Networks

As the coupling and integration of multi-energy flow in the integrated energy system (IES) deepen increasingly, the cascading failure will develop across different energy systems more easily and widely through the energy hub (EH). And it brings great challenges to the security and reliability of IES. The defects of the present cascading failure model of IES have been summarized, and a novel search strategy of fault chains in IES combined heating and power network was proposed in this paper. First, the initial risk assessment index of each energy branch is proposed to form the initial fault sets. Then, combined heat and power control (CHPC) strategies are introduced to deal with the branch overload conditions during the cascading failure. What is more, in order to reduce the workload and overcome the limitation of present methods, we analyzed the relevance of the branches to be predicted by using the kernel fuzzy C-means (KFCM) clustering algorithm and select the branches with the highest value of relevance as the subsequent failure. Based on the predicted fault chain, vulnerability analysis is presented to locate critical component and find out the correlation between cascading outages. The comprehensive evaluation index is also established to effectively evaluate the impact severity of cascading failure. Finally, the case studies are carried out on the combined heating and power systems to demonstrate the effectiveness of the proposed method.

A Three-Stage Procedure for Controlled Islanding to Prevent Wide-Area Blackouts

Controlled islanding has been proposed as a last resort action to stop blackouts from happening when all standard methods have failed. Successful controlled islanding has to deal with three important issues: when, and where to island, and the evaluation of the dynamic stability in each island after islanding. This paper provides a framework for preventing wide-area blackouts using wide area measurement systems (WAMS), which consists of three stages to execute a successful islanding strategy. Normally, power system collapses and blackouts occur shortly after a cascading outage stage. Using such circumstances, an adapted single machine equivalent (SIME) method was used online to determine transient stability before blackout was imminent, and was then employed to determine when to island based on transient instability. In addition, SIME was adopted to assess the dynamic stability in each island after islanding, and to confirm that the chosen candidate island cutsets were stable before controlled islanding was undertaken. To decide where to island, all possible islanding cutsets were provided using the power flow (PF) tracing method. SIME helped to find the best candidate islanding cutset with the minimal PF imbalance, which is also a transiently stable islanding strategy. In case no possible island cutset existed, corresponding corrective actions such as load shedding and critical generator tripping, were performed in each formed island. Finally, an IEEE 39-bus power system with 10 units was employed to test this framework for a three-stage controlled islanding strategy to prevent imminent blackouts.

Extended Enumeration of Hypothesized Substations Outages Incorporating Overload Implication

The risk of cascading outages is often associated with overloading. As a result of electrical short circuits, protective relaying picks up the faults and electrically disconnects overloaded transmission lines through circuit breakers. With similar disturbance and implication, disruptive switching cyberattacks in one or more compromised substations can initiate such events that will aggravate system's operating conditions, leading to a widespread blackout. This paper proposes an extended enumeration of substation outages that excludes the overloaded lines from a power flow model. First, the exhaustive combination which starts from the initial combination size k=1 is enumerated searching for nonconvergent solutions of the hypothesized contingencies associated with the outages of single or more substations. The depth k=S is the level of contingencies which determines when the evaluation will halt. Each combination is then integrated with the overloaded effect that de-energizes transmission lines under the hypothesized scenarios. Nonconvergent solutions on both attack and overloading are carried to the next level of enumerations. This may include islanding that splits a system into multiple areas. The proposed power flow verification is validated using IEEE test cases as well as evaluation of parallel computing to determine its effectiveness of nonconvergent enumeration within a reasonable timeframe.

Prediction and control of transient stability using system integrity protection schemes

Prediction of the transient stability in real-time can be a boon in preventing the occurrence of catastrophic events in a particular area that could potentially affect the entire grid and cause blackouts. Synchronised voltage angle measurements procured from the installed phasor measurement units in the network have been used to devise an index for assessment of transient stability in the system. The behaviour of the trend of the acceleration at the instant of the critical clearing angle has been used in this study as the basis for differentiating between a stable and an unstable power swing. Upon detection of an unstable condition, the generator, which is most likely to be going out of step is detected, and appropriate control action is suggested for mitigating the predicted out of step condition. Moreover, the distance relay maloperations caused during a stable power swing can also be a reason for triggering cascading outages. Suitable remedial measures to avoid such maloperations of the distance relay have been proposed. The efficacy of the proposed philosophy has been tested on a single machine infinite bus system, WSCC-9 bus system and New England 39 bus system modelled in Power Factory/DIgSILENT.

A Three Stages Decision Tree-Based Intelligent Blackout Predictor for Power Systems Using Brittleness Indices

Cascading outage is one of the main mechanisms for propelling power system toward blackout. Predicting the potential and trend of power system toward blackout helps operator to decide what to do as preventive action against blackout. In this paper, for predicting the size of potential blackout, a three stages-based decision tree predictor is proposed for estimating the size of the possible blackout. For this purpose, the ability for simulating the process of cascading events is embedded within power factory software by modeling distance, load shedding, out-of-step, and under/over frequency relays. During the process of cascading failures and trend of power system toward blackout, for monitoring brittle condition of power systems, system operational variables are obtained from WAMS by which a series of online brittleness indices are continuously evaluated at the consecutive time intervals. The proposed three stages predicting scheme enables one to discriminate the severity of cascading failures and system brittle condition into three sizes of blackout, namely, ${\alpha }$ , ${\beta }$ , and ${\gamma }$ ( ${\alpha } ) for which the estimation process are conducted individually for each size but coordinated. The proposed intelligent scheme is demonstrated on 39-bus New England test system and Iran 1063-bus power system with promising results.

Risk-based method to secure power systems against cyber-physical faults with cascading impacts: a system protection scheme application

The utilization levels of the transmission network can be enhanced by the use of automated protection schemes that rapidly respond to disturbances. However, such corrective systems may suffer from malfunctions that have the potential to exacerbate the impact of the disturbance. This paper addresses the challenge of jointly optimizing the dispatch of generators and protection settings in this context. This requires a holistic assessment of the cyber (protection logic) and physical (network) systems, considering the failures in each part and their interplay. Special protection schemes are used as a prototypical example of such a system. An iterative optimization method is proposed that relies on power system response simulations in order to perform detailed impact assessments and compare candidate solutions. The candidate solutions are generated on the basis of a security-constrained dispatch that also secures the system against a set of cyber failure modes. A case study is developed for a generation rejection scheme on the IEEE reliability test system (RTS): candidate solutions are produced based on a mixed integer linear programming optimisation model, and loss-of-load costs are computed using a basic cascading outage algorithm. It is shown that the partial security approach is able to identify solutions that provide a good balance of operational costs and loss-of-load risks, both in a fixed dispatch and variable dispatch context.

Exploiting Coarse-Grained Parallelism Using Cloud Computing in Massive Power Flow Computation

We present a novel architecture of parallel contingency analysis that accelerates massive power flow computation using cloud computing. It leverages cloud computing to investigate huge power systems of various and potential contingencies. Contingency analysis is undertaken to assess the impact of failure of power system components; thus, extensive contingency analysis is required to ensure that power systems operate safely and reliably. Since many calculations are required to analyze possible contingencies under various conditions, the computation time of contingency analysis increases tremendously if either the power system is large or cascading outage analysis is needed. We also introduce a task management optimization to minimize load imbalances between computing resources while reducing communication and synchronization overheads. Our experiment shows that the proposed architecture exhibits a performance improvement of up to 35.32× on 256 cores in the contingency analysis of a real power system, i.e., KEPCO2015 (the Korean power system), by using a cloud computing system. According to our analysis of the task execution behaviors, we confirmed that the performance can be enhanced further by employing additional computing resources.

Management of Cascading Outage Risk Based on Risk Gradient and Markovian Tree Search

Since cascading outages are major threats to power systems, it is important to reduce the risk of potential cascading outages. In this paper, a risk management method of cascading outages based on Markovian tree search is proposed. With the tree expansion on the cascading outage risk, risk gradient is computed efficiently by a forward-backward tree search scheme with good convergence, and it is then employed in an optimization model to minimize control cost while effectively reducing the cascading outage risk. To overcome the limitation with linearization in computing risk gradient, an iterative risk management (IRM) approach is further developed. Tests on the RTS-96 3-area system verify the accuracy of the computed risk gradient and its effectiveness for risk reduction. Time performance of the proposed IRM approach is tested on the RTS-96 system, a 410-bus US-Canada northeast system and a 1354-bus Mid-European system, and demonstrates its potentials for decision support on practical power systems online or on hourly basis.

Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties

The rapid growth of natural gas fuel consumption by gas-fired generators and the new emerging power-to-gas technology have intensified interdependency of electric power and natural gas systems. Consequently, such interdependency, together with heterogeneous uncertainties of the power system (e.g., power loads and renewable energy) and the gas system (e.g., gas loads), has brought new challenges to energy system operators for the secure and economic operation of interdependent power and gas systems. Specifically, uncertainties from one infrastructure could easily spread to the other, which consequently increase vulnerability and eventually lead to cascading outages of both systems. This paper proposes a two-stage adjustable robust model to study day-ahead coordinated optimal scheduling of the interdependent power and gas systems. Dual-fuel generating units are also considered for shaving gas fuel consumptions and ensuring the security of both systems during peak gas demand hours. Moreover, Weymouth gas flow constraints are linearized via Taylor series expansion, which facilitates the implementation of column-and-constraint generation algorithm to effectively solve the proposed two-stage adjustable robust model with nonlinear gas flow constraints in the second stage. Numerical case studies illustrate that dual-fuel units can enhance the secure and economical operation of interdependent power and gas systems, especially when natural gas demands present upward uncertainties. It is also demonstrated that power-to-gas facilities can facilitate a deeper penetration of volatile renewable energy by effectively converting excessive renewable generation into natural gas.