Modeling, Simulation, and Analysis of Cascading Outages in Power Systems

Interconnected power systems are prone to cascading outages leading to large-area blackouts. Modeling, simulation, analysis, and mitigation of cascading outages are still challenges for power system operators and planners.Firstly, the interaction model and interaction graph proposed by [27] are demonstrated on a realistic Northeastern Power Coordinating Council (NPCC) power system, identifying key links and components that contribute most to the propagation of cascading outages. Then a multi-layer interaction graph for analysis and mitigation of cascading outages is proposed. It provides a practical, comprehensive framework for prediction of outage propagation and decision making on mitigation strategies. It has multiple layers to respectively identify key links and components, which contribute the most to outage propagation. Based on the multi-layer interaction graph, effective mitigation strategies can be further developed. A three-layer interaction graph is constructed and demonstrated on the NPCC power system.Secondly, this thesis proposes a novel steady-state approach for simulating cascading outages. The approach employs a power flow-based model that considers static power-frequency characteristics of both generators and loads. Thus, the system frequency deviation can be calculated under cascading outages and control actions such as under-frequency load shedding can be simulated. Further, a new AC optimal power flow model considering frequency deviation (AC-OPFf) is proposed to simulate remedial control against system collapse. Case studies on the two-area, IEEE 39-bus, and NPCC power systems show that the proposed approach can more accurately capture the propagation of cascading outages when compared with a conventional approach using the conventional power flow and AC optimal power flow models.Thirdly, in order to reduce the potential risk caused by cascading outages, an online strategy of critical component-based active islanding is proposed. It is performed when any component belonging to a predefined set of critical components is involved in the propagation path. The set of critical components whose fail can cause large risk are identified based on the interaction graph. Test results on the NPCC power system show that the cascading outage risk can be reduced significantly by performing the proposed active islanding when compared with the risk of other scenarios without active islanding

A Markovian influence graph formed from utility line outage data to mitigate large cascades

We use observed transmission line outage data to make a Markovian influence graph that describes the probabilities of transitions between generations of cascading line outages. Each generation of a cascade consists of a single line outage or multiple line outages. The new influence graph defines a Markov chain and generalizes previous influence graphs by including multiple line outages as Markov chain states. The generalized influence graph can reproduce the distribution of cascade size in the utility data. In particular, it can estimate the probabilities of small, medium and large cascades. The influence graph has the key advantage of allowing the effect of mitigations to be analyzed and readily tested, which is not available from the observed data. We exploit the asymptotic properties of the Markov chain to find the lines most involved in large cascades and show how upgrades to these critical lines can reduce the probability of large cascades

Real-Time Area Angle Monitoring Using Synchrophasors: A Practical Framework and Utility Deployment

This article develops a practical framework of Area Angle Monitoring (AAM) to monitor in real time the stress of bulk power transfer across an area of a power transmission system. Area angle is calculated from synchrophasor measurements in real time to provide alert to system operators if the area angle exceeds pre-defined thresholds. This article proposes a general method to identify the warning threshold of area angle and a simplified method to quickly update area angle thresholds under significant topology change. A mitigation strategy to relieve the area stress is also proposed. In order to handle the limited coverage of synchrophasor measurements, this article proposes a method to estimate phase angles for boundary buses without synchrophasor measurements, which extends the application scenario of AAM. AAM is verified for a power transmission area in the Western Electricity Coordinating Council system with both simulated data and synchrophasor measurements recorded from real events. A utility deployment for real-time application of AAM with livestream and recorded synchrophasor data is described

Towards Faster-than-real-time Power System Simulation Using a Semi-analytical Approach and High-performance Computing

This dissertation investigates two possible directions of achieving faster-than-real-time simulation of power systems. The first direction is to develop a semi-analytical solution which represents the nonlinear dynamic characteristics of power systems in a limited time period. The second direction is to develop a parallel simulation scheme which allows the local numerical solutions of power systems to be developed independently in consecutive time intervals and then iteratively corrected toward the accurate global solution through the entire simulation time period. For the first direction, the semi-analytical solution is acquired using Adomian decomposition method (ADM). The ADM assumes the analytical solution of any nonlinear system can be decomposed into the summation of infinite analytical expressions. Those expressions are derived recursively using the system differential equations. By only keeping a finite number of those analytical expressions, an approximation of the analytical solution is yielded, which is defined as a semi-analytical solution. The semi-analytical solutions can be developed offline and evaluated online to facilitate the speedup of simulations. A parallel implementation and variable time window approach for the online evaluation stage are proposed in addition to the time performance analysis. For the second direction, the Parareal-in-time algorithm is tested for power system simulation. Parareal is essentially a multiple shooting method. It decomposes the simulation time into coarse time intervals and then fine time intervals within each coarse interval. The numerical integration uses a computational cheap solver on the coarse time grid and an expensive solver on the fine time grids. The solution within each coarse interval is propagated independently using the fine solver. The mismatch of the solution between the coarse solution and fine solution is corrected iteratively. The theoretical speedup can be achieved is the ratio of the coarse interval number and iteration number. In this dissertation, the Parareal algorithm is tested on the North American eastern interconnection system with around 70,000 buses and 5,000 generators

Multi-Layer Interaction Graph for Analysis and Mitigation of Cascading Outages

This paper proposes a multi-layer interaction graph on cascading outages of power systems as an extension of a single-layer interaction network proposed previously. This multi-layer interaction graph provides a practical framework for the prediction of outage propagation and decision making on mitigation actions. It has multiple layers to, respectively, identify key intra-layer links and components within each layer and key inter-layer links and components between layers, which contribute the most to outage propagation. Each layer focuses on one of several aspects that are critical for system operators\u27 decision support, such as the number of line outages, the amount of load shedding, and the electrical distance of outage propagation. Besides, the proposed integrated mitigation strategies can limit the propagation of cascading outages by weakening key intra-layer links. All layers are constructed offline from a database of simulated cascades and then used online. A three-layer interaction graph is presented in detail and demonstrated on the Northeastern Power Coordinating Council 48-machine 140-bus system. The key intra-and inter-layer links and key components revealed by the multi-layer interaction graph provide useful insights on the mechanism and mitigation of cascading outages, which cannot be obtained from any single-layer

Multi-Layer Interaction Graph For Analysis And Mitigation Of Cascading Outages

This paper proposes a multi-layer interaction graph on cascading outages of power systems as an extension of a single-layer interaction network proposed previously. This multi-layer interaction graph provides a practical framework for the prediction of outage propagation and decision making on mitigation actions. It has multiple layers to, respectively, identify key intra-layer links and components within each layer and key inter-layer links and components between layers, which contribute the most to outage propagation. Each layer focuses on one of several aspects that are critical for system operators\u27 decision support, such as the number of line outages, the amount of load shedding, and the electrical distance of outage propagation. Besides, the proposed integrated mitigation strategies can limit the propagation of cascading outages by weakening key intra-layer links. All layers are constructed offline from a database of simulated cascades and then used online. A three-layer interaction graph is presented in detail and demonstrated on the Northeastern Power Coordinating Council 48-machine 140-bus system. The key intra-and inter-layer links and key components revealed by the multi-layer interaction graph provide useful insights on the mechanism and mitigation of cascading outages, which cannot be obtained from any single-layer

Electromechanical Dynamics of High Photovoltaic Power Grids

This dissertation study focuses on the impact of high PV penetration on power grid electromechanical dynamics. Several major aspects of power grid electromechanical dynamics are studied under high PV penetration, including frequency response and control, inter-area oscillations, transient rotor angle stability and electromechanical wave propagation.To obtain dynamic models that can reasonably represent future power systems, Chapter One studies the co-optimization of generation and transmission with large-scale wind and solar. The stochastic nature of renewables is considered in the formulation of mixed-integer programming model. Chapter Two presents the development procedures of high PV model and investigates the impact of high PV penetration on frequency responses. Chapter Three studies the impact of PV penetration on inter-area oscillations of the U.S. Eastern Interconnection system. Chapter Four presents the impacts of high PV on other electromechanical dynamic issues, including transient rotor angle stability and electromechanical wave propagation. Chapter Five investigates the frequency response enhancement by conventional resources. Chapter Six explores system frequency response improvement through real power control of wind and PV. For improving situation awareness and frequency control, Chapter Seven studies disturbance location determination based on electromechanical wave propagation. In addition, a new method is developed to generate the electromechanical wave propagation speed map, which is useful to detect system inertia distribution change. Chapter Eight provides a review on power grid data architectures for monitoring and controlling power grids. Challenges and essential elements of data architecture are analyzed to identify various requirements for operating high-renewable power grids and a conceptual data architecture is proposed. Conclusions of this dissertation study are given in Chapter Nine