Showing papers on "Blackout published in 2022"

Identifying and assessing power system vulnerabilities to transmission asset outages via cascading failure analysis

Abstract: Power systems as critical infrastructure are an integral part of human society and are therefore of paramount importance to modern life. Vulnerabilities in the system, that are revealed either by accidental or deliberate events, can cause large losses of power supply with sever social and economic consequences. A tool that identifies the vulnerabilities in a power system can provide the operators the means to support reliable power system operations. This paper presents a methodology for power system vulnerability assessment that couples an AC based cascading failure simulation model and a meta-heuristic optimization procedure. The objectives of the assessment are to (1) rank the most important branches in the transmission grid, and (2) identify sets of branches if simultaneously tripped will cause the cascade with highest intensity. The first objective is achieved by ranking the criticality of the branches using two criteria (i) the impact that each branch failure has on the DNS and (ii) the frequency of line overload. The second objective is achieved by hard linking an AC based cascading failure simulation model and a meta-heuristic based optimization procedure. The methodology allows the generation and the identification of vulnerability scenarios, and therefore, provides insights that can be used by operators in developing strategies to minimize the effects of accidental and deliberate events. The algorithm developed for the purpose of this study is applied to the IEEE 118-bus test system and the Swiss power grid. The results demonstrate the capability of the proposed methodology for assessing power system vulnerability.

Risks in the European Transmission System and a Novel Restoration Strategy for a Power System after a Major Blackout

Abstract: Many citizens of European countries may soon experience a long and extensive blackout. The lack of predictability in the output of renewable energy sources, aggravating the problem of consistently matching supply with demand on electric grids, along with cyber-attacks or even worse unpredictable incidents in the electric grid are some factors that may mean a blackout is much more likely than in previous years. This paper covers the possibility of an extensive blackout in a country of the interconnected European electricity transmission system or, even worse, a blackout in a wide area of the European continent. The topic of this paper becomes even more important and timely given the energy crisis due to the war in Ukraine, which has made the possibility of a blackout in the winter of 2022–2023 high. First, the major European blackouts that occurred in the past 20 years are presented, examining their causes. On 8 January 2021, the European electricity grid was divided into two separate sections, with different frequencies; some additional scenarios are considered which, if they had happened, could have led to blackouts in some European countries or, even worse, a wide area of Europe. This work also examines how to avoid such an eventuality, as well as how European TSOs should react in case a blackout occurs. Focused on the fast and reliable supply of consumers after a blackout, a novel restoration strategy based on the A* Algorithm is presented. Its efficiency is validated in the IEEE-39 and IEEE-68 bus systems.

Blackout and supply chains: Cross-structural ripple effect, performance, resilience and viability impact analysis

Abstract: Increased electricity consumption along with the transformations of the energy systems and interruptions in energy supply can lead to a blackout, i.e., the total loss of power in an area (or a set of areas) of a longer duration. This disruption can be fatal for production, logistics, and retail operations. Depending on the scope of the affected areas and the blackout duration, supply chains (SC) can be impacted to different extent. In this study, we perform a simulation analysis using anyLogistix digital SC twin to identify potential impacts of blackouts on SCs for scenarios of different severity. Distinctively, we triangulate the design and evaluation of experiments with consideration of SC performance, resilience, and viability. The results allow for some generalizations. First, we conceptualize blackout as a special case of SC risks which is distinctively characterized by a simultaneous shutdown of several SC processes, disruption propagations (i.e., the ripple effect), and a danger of viability losses for entire ecosystems. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of blackouts, mitigation and recovery strategies. The major observation from the simulation experiments is that the dynamics of the power loss propagation across different regions, the blackout duration, simultaneous unavailability of supply and logistics along with the unpredictable customer behavior might become major factors that determine the blackout impact and influence selection of an appropriate recovery strategy. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of blackouts on the SCs and viability and develop mitigation and recovery strategies. The paper is concluded by summarizing the most important insights and outlining future research agenda toward SC viability, reconfigurable SC, multi-structural SC dynamics, intertwined supply networks, and cross-structural ripple effects.

Smart dielectric materials for next-generation electrical insulation

Abstract: Smart dielectric materials with bioinspired and autonomous functions are expected to be designed and fabricated for next-generation electrical insulation. Similar to organisms, such dielectrics with self-adaptive, self-reporting, and self-healing capabilities can be employed to avoid, diagnose, and repair electrical damage to prevent catastrophic failure and even a blackout. Compared with traditional dielectrics, the utilization of smart materials not only increases the stability and durability of power apparatus but also reduces the costs of production and manufacturing. In this review, researches on self-adaptive, self-reporting, and self-healing dielectrics in the field of electrical insulation, and illuminating studies on smart polymers with autonomous functions in other fields are both introduced. The principles, methods, mechanisms, applications, and challenges of these materials are also briefly presented.

Controlled Islanding Strategy Considering Uncertainty of Renewable Energy Sources Based on Chance-constrained Model

Abstract: Controlled islanding plays an essential role in preventing the blackout of power systems. Although there are several studies on this topic in the past, no enough attention is paid to the uncertainty brought by renewable energy sources (RESs) that may cause unpredictable unbalanced power and the observability of power systems after islanding that is essential for back-up black-start measures. Therefore, a novel controlled islanding model based on mixed-integer second-order cone and chance-constrained programming (MISOCCP) is proposed to address these issues. First, the uncertainty of RESs is characterized by their possibility distribution models with chance constraints, and the requirements, e. g., system observ-ability, for rapid back-up black-start measures are also considered. Then, a law of large numbers (LLN) based method is employed for converting the chance constraints into deterministic ones and reformulating the non-convex model into convex one. Finally, case studies on the revised IEEE 39-bus and 118-bus power systems as well as the comparisons among different models are given to demonstrate the effectiveness of the proposed model. The results show that the proposed model can result in less unbalanced power and better observability after islanding compared with other models.

Quantitative Risk Assessment of Cyber Attacks on Cyber-Physical Systems using Attack Graphs

Abstract: Over the past decade, the number of cyber attack incidents targeting critical infrastructures such as the electrical power system has increased. To assess the risk of cyber attacks on the cyber-physical system, a holistic approach is needed that considers both system layers. However, the existing risk assessment methods are either qualitative in nature or employ probabilistic models to study the impact on only one system layer. Hence, in this work, we propose a quantitative risk assessment method for cyber-physical systems based on probabilistic and deterministic techniques. The former uses attack graphs to evaluate the attack likelihood, while the latter analyzes the potential cyber-physical impact. This is achieved through a dynamic cyber-physical power system model, i.e., digital twin, able to simulate power system cascading failures caused by cyber attacks. Additionally, we propose a domain-specific language to describe the assets of digital substations and thereby model the attack graphs. Using the proposed method, combined risk metrics are calculated that consider the likelihood and impact of cyber threat scenarios. The risk assessment is conducted using the IEEE 39-bus system, consisting of 27 user-defined digital substations. These substations serve as the backbone of the examined cyber system layer and as entry-points for the attackers. Results indicate that cyber attacks on specific substations can cause major cascading failures or even a blackout. Thereby, the proposed method identifies the most critical substations and assets that must be cyber secured.

Load prioritization technique to guarantee the continuous electric supply for essential loads in rural microgrids

Abstract: Microgrid (MG) is one of the practical and best concepts to provide energy access to rural communities, where electric grid extension is not techno-economically feasible. Since the trend of load consumption is not uniform with a low load factor in a rural area, the required rating of the system becomes very high. Similarly, the generation is fixed for these MGs, whereas the load increases continuously over time. Such a system faces supply deficit issues triggering a high number of interruptions that may cause frequent blackouts. Hence, rolling blackout and load clipping techniques are preferred during the peak load period in most of the rural MGs. These issues lead to an unreliable power supply and low satisfaction level of the user. This paper presents the load prioritization technique to guarantee the continuous supply for the essential loads within the rural community. A day-ahead energy allocation technique is mathematically formulated and optimized to maximize the total hours of energy served. This technique maximized the hours of energy served to the load with higher priority followed by the load with lower priorities. From this study, it is found that the proposed strategy helps to improve the hours of energy served in the overall system, by improving the state of charge (SoC) level of the battery system. The result shows that the user satisfaction level has been improved by 5% through 100% of continuity for the essential loads.

Tropical cyclone-blackout-heatwave compound hazard resilience in a changing climate

Abstract: Abstract Tropical cyclones (TCs) have caused extensive power outages. The impacts of TC-caused blackouts may worsen in the future as TCs and heatwaves intensify. Here we couple TC and heatwave projections and power outage and recovery process analysis to investigate how TC-blackout-heatwave compound hazard risk may vary in a changing climate, with Harris County, Texas as an example. We find that, under the high-emissions scenario RCP8.5, long-duration heatwaves following strong TCs may increase sharply. The expected percentage of Harris residents experiencing at least one longer-than-5-day TC-blackout-heatwave compound hazard in a 20-year period could increase dramatically by a factor of 23 (from 0.8% to 18.2%) over the 21 st century. We also reveal that a moderate enhancement of the power distribution network can significantly mitigate the compound hazard risk. Thus, climate adaptation actions, such as strategically undergrounding distribution network and developing distributed energy sources, are urgently needed to improve coastal power system resilience.

Energy storage for black start services: A review

Abstract: Abstract With the increasing deployment of renewable energy-based power generation plants, the power system is becoming increasingly vulnerable due to the intermittent nature of renewable energy, and a blackout can be the worst scenario. The current auxiliary generators must be upgraded to energy sources with substantially high power and storage capacity, a short response time, good profitability, and minimal environmental concern. Difficulties in the power restoration of renewable energy generators should also be addressed. The different energy storage methods can store and release electrical/thermal/mechanical energy and provide flexibility and stability to the power system. Herein, a review of the use of energy storage methods for black start services is provided, for which little has been discussed in the literature. First, the challenges that impede a stable, environmentally friendly, and cost-effective energy storage-based black start are identified. The energy storage-based black start service may lack supply resilience. Second, the typical energy storage-based black start service, including explanations on its steps and configurations, is introduced. Black start services with different energy storage technologies, including electrochemical, thermal, and electromechanical resources, are compared. Results suggest that hybridization of energy storage technologies should be developed, which mitigates the disadvantages of individual energy storage methods, considering the deployment of energy storage-based black start services.

Black-Start and Service Restoration in Resilient Distribution Systems With Dynamic Microgrids

Abstract: The resilience of distribution systems has been challenged by power outages caused by natural disasters, which calls for novel solutions to system restoration. However, the existing black-start (BS) techniques are mainly developed at the transmission level. This problem can be resolved by adopting dynamic microgrids (MGs), i.e., MGs with dynamic and adjustable boundaries nested in the distribution systems. This article proposes a restoration procedure that adopts self-organizing inverters as BS units and achieves distribution system restoration in the context of dynamic MGs. The proposed restoration procedure is structured as a two-stage approach and designed to restore a complete blackout distribution system to the state where the system is ready for seamless main grid reconnection. A framework of dynamic MG operation is developed, which improves the self-healing capability of off-grid distribution systems with automatic sectionalization and flexible reconfiguration. A sequence of actions during restoration is defined, along with distributed controllers designed with considerations of practical operating challenges. The proposed restoration procedure is validated on a 34-bus system using real-time hardware-in-the-loop simulation.

Cyber-Physical Coordinated Risk Mitigation in Smart Grids Based on Attack-Defense Game

Abstract: Since modern smart grids have various and deeply coupled cyber-physical components, they are vulnerable to malicious cyber attacks. Although regular defenses including firewall and IDS are deployed, they may be weakened by zero-day vulnerabilities and sophisticated attack schemes. Therefore, defense strategies to mitigate the risk of blackouts during cyber attacks are necessary. This paper proposes a cyber-physical coordinated defense strategy to overcome the disruption and minimize the risk as much as possible. At the cyber layer, a zero-sum multilevel Markovian Stackelberg game is proposed to model sequential actions of the attacker and the defender. The defender distributes defensive resources to protect lines in a real-time manner, according to the attacker's action. If cyber attacks should result in physical outages, defense at the physical layer is then employed. A security-constrained optimal power flow reserving security margin of critical components will be performed to minimize the blackout scale and potential future risk. To solve the corresponding optimization problem and further get the optimal defense strategy, this paper devises a novel “water-pouring” algorithm. Lastly, test results show that the proposed dynamic defense strategy mitigates risk significantly and outperforms existing methods.

Dynamic Modeling and Cascade Failure Analysis of the Mumbai Grid Incident of October 12, 2020

Abstract: The Mumbai region in India experienced a massive outage on October 12, 2020, due to cascade failure. The event taught some serious lessons to the grid operators and highlighted the need for energy security and reliability. In this incident, the cascade tripping of the external transmission network resulted in an unexpected island containing Mumbai city isolating it from the rest of Indian power grid. Although the Mumbai islanding scheme was operational, it failed to survive due to high rate of change of frequency (ROCOF). Globally, such blackouts occur due to low probability, high impact events. Major blackouts are caused by a set of triggering events that are usually preceded by some incidents that weaken the power system. Further, the failure of important security mechanisms and protections can compound the effect of disturbances. In view of this, the paper focuses on the consequences of cascading events that led to several blackouts in history. This paper analyses the October 12, 2020, Mumbai power grid failure by recreating various scenarios that resulted in the blackout through dynamic modelling on the PSS/E platform. The results were validated using data collected from phasor measurement units (PMUs) and SCADA. In this article various challenges faced during unfolding of the event are presented. Lessons learnt such as appropriate settings and tuning were identified to ensure the survival of islanding scheme. Assessment of Mumbai power system’s transfer capability is done to facilitate the optimal mix of imported and embedded generation.

Under-Frequency Load Shedding in a Standalone Power System With Wind-Turbine Generators Using Fuzzy PSO

Abstract: Under-frequency load shedding maintains a power grid resilient against a severe contingency. The under-frequency relay (such as 81L) with pre-determined settings is used to prevent blackout in the power grid by detecting a decreasing system frequency. In this work, the shed load and frequency setting at each stage for the 81L relay are determined in an offshore standalone power grid with wind power turbines. Possible scenarios including “N-2-2” outages and “N-3” outages as well as Markov models of diesel and wind generators are investigated. The total shed load is minimized and the frequency nadir is maximized using Takagi-Sugeno (TS)-based particle swarm optimization (PSO). Two sets of TS fuzzy rules are developed to tune the inertia weight and learning factors in the proposed PSO to obtain the optimal settings. A 31-bus standalone power grid with two wind turbines of 2×2 MW was studied to reveal the applicability of the proposed method.

Analysis and Proposed Remedies for Power System Blackouts around the Globe

Abstract: Stable operation of power systems contributes towards the economic growth of developed and developing countries around the globe. Blackouts due to technical faults put the whole power system in danger. In this paper, a comprehensive analysis of power system blackouts, their root causes, and potential impacts on the economy of developed and developing countries around the globe is presented, along with possible approaches to avoid and resolve power system blackouts. The paper also proposes ways to avoid cascaded events in case of power system failure at a single point resulting in cascaded events and a complete blackout.

Two-Stage MILP Model for Optimal Skeleton-Network Reconfiguration of Power System for Grid-Resilience Enhancement

Abstract: Skeleton-network reconfiguration is an important task and plays a most important role during power system restoration (PSR) after a blackout. By determining the skeleton network, the power system can be restored as soon as possible to minimize the burden of network reconfiguration. In this paper, a resilience-based skeleton-network reconfiguration (NR) strategy, i.e., a two-stage mixed-integer linear programming (MILP)–based NR strategy for grid-resilience enhancement, is proposed to minimize the impact of emergency power outages on power systems. The start-up sequence for non-black-start generators (NBSGs) and line energization sequences are determined in the first-stage optimization model. A serial restoration constraint and a transient frequency constraint are considered to achieve the serial restoration scheme of NBSGs. Except for the generator power, all the variables attained during the first stage are assumed fixed in the second stage. The second-stage optimization model determines the optimal skeleton network by determining the target transmission lines and critical load pickup during the NR phase. Furthermore, the sets of metrics (i.e., system flexibility, power loss ratio, and recovery time resilience) are presented to determine the grid operational resilience in the skeleton-network reconfiguration. Then, two stages of skeleton-NR are formulated as MILP, and the branch-and-bound method is presented to solve both models. Finally, simulation studies are performed on the two modified power system test cases and the results validate that the proposed strategy can efficiently determine the robust skeleton network for practical and detailed PSR planning.

Two-Stage MILP Model for Optimal Skeleton-Network Reconfiguration of Power System for Grid-Resilience Enhancement

Abstract: Skeleton-network reconfiguration is an important task and plays a most important role during power system restoration (PSR) after a blackout. By determining the skeleton network, the power ...

Proposed Hybrid Power Optimization for Wind Turbine/Battery System

Abstract: This paper contributes to the feasibility of a wind turbine/battery system with a hybrid power optimization controller. The proposed method is based on a mathematical optimization approach and allows to achieve an efficient operation of the maximum power point tracking (MPPT) algorithms to obtain an optimal performance level of the wind system and a minimal stress on the battery storage. The different powers have been controlled by a power management control (PMC) method. The objectives of the PMC based are, in first part to satisfy the load power demand and in second part to maintain the state of charge of the battery bank to prevent blackout and to extend the batteries life. A measurement of wind speeds was made during a whole day using a data acquisition system at the laboratory. Also, the different wind turbine parameters were identified at the same Laboratory. All these parameters have been used in simulation models in order to obtain the most realistic mathematical models that are close to the experiment. Real time simulation is performed using RT LAB simulator and the obtained results were matching those obtained in numerical simulation using Matlab/Simulink. The obtained results under two different wind speed profile, with the different comparisons are presented to show the feasibility and the improvement of the proposed study in terms of power, efficiency, time response and effect on battery state of charge under two different wind speeds profile.

Safety Analysis in VVER-1000 Due to Large-Break Loss-of-Coolant Accident and Station Blackout Transient Using RELAP5/SCDAPSIM/MOD3.5

Abstract: Abstract It is crucial to do safety evaluation of different postulated transient scenarios in actual nuclear power plants (NPPs). Some of the common analyzed scenarios are primary coolant tube rupture and station blackout (SBO). In this research, it was supposed that after establishment of a steady-state condition, an instantaneous guillotine large-break loss-of-coolant accident (LB-LOCA) of 850-mm inside diameter in one of the reactor vessel cold legs occurred, accompanied with SBO. The event progression and the variation of different reactor parameters like loop pressures, mass flow rates, fuel and clad temperature, injection rate of accumulators (ACCs), decay, and reactor power were investigated using the RELAP5/SCDAPSIM/MOD3.5 thermal-hydraulic program. The reactor consequences due to availability and unavailability of passive ACCs were compared. These kinds of analyses assist in estimating the time available to perform operator safety actions. This in turn aids in emergency planning and severe accident management. The results reveal that fuel damage decreased after the introduction of ACCs. Actuation of ACCs at their actuation setpoints provided core cooling by injecting water into the reactor core. However, ACCs alone are inadequate to contain long-term core cooling during a persistent LB-LOCA. The results obtained in the research were compared with MELCOR 2.1 and ASTEC V1.3, and a cohesive agreement was obtained. Therefore, RELAP5/SCDAPSIM/MOD3.5 is capable of modeling a LB-LOCA and SBO in VVER-1000, and it provides a significant analytical capability of safety systems for specialists in the field in NPP safety.