相关论文
Causes of the 2003 major grid blackouts in North America and Europe, and recommended means to improve system dynamic performance
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Abstract:On August 14, 2003, a cascading outage of transmission and generation facilities in the North American Eastern Interconnection resulted in a blackout of most of New York state as well as parts of Pennsylvania, Ohio, Michigan, and Ontario, Canada. On September 23, 2003, nearly four million customers lost power in eastern Denmark and southern Sweden following a cascading outage that struck Scandinavia. Days later, a cascading outage between Italy and the rest of central Europe left most of Italy in darkness on September 28. These major blackouts are among the worst power system failures in the last few decades. The Power System Stability and Power System Stability Controls Subcommittees of the IEEE PES Power System Dynamic Performance Committee sponsored an all day panel session with experts from around the world. The experts described their recent work on the investigation of grid blackouts. The session offered a unique forum for discussion of possible root causes and necessary steps to reduce the risk of blackouts. This white paper presents the major conclusions drawn from the presentations and ensuing discussions during the all day session, focusing on the root causes of grid blackouts. This paper presents general conclusions drawn by this Committee together with recommendations based on lessons learned.
摘要：2003年8月14日，北美东部互联的输电和发电设施的级联中断导致纽约州大部分地区以及宾夕法尼亚州、俄亥俄州、密歇根州和加拿大安大略省的部分地区停电。2003年9月23日，在斯堪的纳维亚半岛发生连锁停电后，丹麦东部和瑞典南部近400万用户断电。几天后，9月28日，意大利和中欧其他国家之间的一场连锁停电使意大利大部分地区陷入黑暗。这些大停电是过去几十年来最严重的电力系统故障之一。IEEE PES电力系统动态性能委员会的电力系统稳定和电力系统稳定控制小组委员会发起了一场由来自世界各地的专家参加的全天小组会议。专家们描述了他们最近在电网停电调查方面的工作。会议为讨论可能的根本原因和减少停电风险的必要步骤提供了一个独特的论坛。本白皮书介绍了从全天会议期间的演讲和随后的讨论中得出的主要结论，重点是电网停电的根本原因。本文件介绍了本委员会得出的一般性结论以及根据经验教训提出的建议。
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Cascading Outage Simulation Based on Dynamic Fast Decoupled Load Flow Model
ArXiv
2017
摘要
Abstract—Frequency is an important indicator of balance between active power generation and load. Active powerfrequency dynamics analysis is an important task of power system operation. This paper proposes a novel cascading outage simulation model based on dynamic Fast Decoupled Load Flow (FDLF) considering frequency deviation. A distributed slack bus model is considered in such a way that all of the dispatched generating units share the power imbalance according to their power frequency characteristics. It can reflect the frequency dynamics based on steady-state load flow calculation in the simulation of cascading outage. Also the frequency characteristics of the loads in response to the power imbalance are considered. A novel AC-OPF model introducing the system frequency deviation as a new state variable is proposed to search for a new operating condition when dynamic FDLF is not convergent. The case studies on a two-area, 4-machine power system and a Northeastern Power Coordinating Council (NPCC) 48-machine, 140-bus power system validate the proposed model. Frequency deviation obtained from dynamic FDLF model matches very well with that at the steady-state of time-domain simulation. The statistics of cascading outage samples indicates the frequency insecurity has great impacts on the severity of the cascading outage.
Risk based multi-objective security control and congestion management
2007
摘要
xii CHAPTER 1: INTRODUCTION 1 1.1 Power System Security Definition 1 1.2 Power System Security Assessment 3 1.2.1 Deterministic Approach 3 1.2.2 Probabilistic Approach 5 1.3 Security Control and Optimization 6 1.3.1 Power System Control 6 1.3.2 Security Constrained Optimization 8 1.3.3 Optimization Methods Summary 9 1.4 Enhancing Market Security Based on Price Signal 12 1.5 Problem Statement 13 1.6 Dissertation Organization 16 CHAPTER 2: AN OVERVIEW OF RISK BASED SECURITY ASSESSMENT 18 2.
Cloud Computing Strategies for Enhancing Smart Grid Performance in Developing Countries
2018
摘要
vi
Modeling and detection of high impedance arcing fault in medium voltage networks
2007
摘要
of Doctoral Dissertation iii
A method of identifying and analyzing irrational system behavior in a system of systems
Syst. Eng.
2019
摘要
ing away from physical components and subsystems to the functional level can help practitioners to consider potential new initiating event sources that otherwise may bemissed. • Step 2, Part 2: Remove all flows from the list of potential irrationality initiators that are alreadymodeled as initiating events throughother failure analysis methods, such as FFIP and PRA. • Step 2, Part 3: Identify any potentially impossible candidate irrationality initiators that cannot be emitted by the generic black box system. Before eliminating a candidate irrationality initiator, the practitioner must attempt to identify ways that the irrationality initiator may be able to be generated even if it is highly implausible or unlikely. For instance, almost any material can produce spectral emissions that would normally be unexpectedwith sufficient energy applied to thematerial. • Step 2, Part 4: Assign probabilities of occurrence to each of the irrationality initiators remaining on the list. We advocate that practitioners follow initiating event probability guidance from PRA, such as Refs. 10 and 49. Now that potential irrationality initiators within an SoS that may impact the SoI have been identified and probabilities assigned, the flow paths by which the irrationality initiators enter the system must be defined. Irrationality initiators may be introduced to a system along nominal flow paths or along non-nominal flow paths, such as the uncoupled failure flow paths advanced in the UFFSR method.24 Additions to or modifications of the failure model for a systemmay be necessary to sufficiently capture irrationality initiator entry points. 3.3 Analysis of potential irrationality initiators The next step in the method is to conduct failure analysis on the SoI using the identified potential irrationality initiators. We advocate for and use in the case study the FFIP family of failure analysis tools to conduct failure analysis on the SoI. In order to produce a more accurate analysis of potential irrationality initiators using FFIP and F IGURE 2 Steps to developing irrationality initiators VANBOSSUYT ET AL. 525 related tools, we recommend that the analysis be performed using data collected from the proposed physical architecture that solves the functional architecture of the SoI. The number of potential failure scenarios, often called “cut-sets” in PRA and sometimes in FFIP, resulting from the analysis of irrationality initiators, is directly related to thenumberof irrationality initiators and the functionalmodel of the SoI. Each irrationality initiatormayproceed along many different flow paths in an SoI, causing functional failure along the way, which in turn may lead to system failure. The number of potential failure scenariosmay further be expanded by havingmultiple potential component solutions available for specific functions before down-selection of component solutions has been conducted. While probabilities for specific irrationality initiators were calculated in a prior step in the method, there are several options for how irrationality initiators are analyzed based on what type of analysis results a practitioner is interested in reviewing. These include an uninformative prior and an informative prior. Further, irrationality initiators that are either independent or dependent can be considered to provide additional insights into potential irrational failure scenarios, such as when multiple irrationality initiators often occur together. Informative and uninformative priors, and independent and dependent irrationality initiators may be combined together. Further explanation immediately follows: 3.3.1 Uninformative and informative priors In order to understand the sensitivity of an SoI to irrationality initiators, the uninformative prior sets all irrationality initiators to the same probability of occurrence. It should be noted that using the uninformative prior approachdoes not allow for direct comparisonof resultswith other FFIP results. The results are specifically useful to understand what high severity failure outcomes are present that otherwise may be truncated during computation. The uninformative prior method can also be used to perform a sensitivity analysis on the irrationality initiators by changing their probabilities and comparing results. This may help to identify irrationality initiators that are not particularly sensitive to changes in their probabilities of occurrence and may also identify specific irrationality initiators that warrant extended scrutiny to ensure a higher degree of accuracy and realism in the probability statistics. In contrast to the uninformative prior that uses arbitrarily assigned probabilities to determine potential low probability but very severe outcomes and to examine irrationality initiator probability sensitivity, the informative prior uses probabilities of occurrence that were already developed in a previous step of the methodology and that are based in reality. This allows for direct comparison of irrationality initiator-derived failure scenario probabilities with failure scenario probabilities produced from FFIP. In the event that a probability was unable to be developed previously because of a lack of information, we suggest using a probability value that is 3x the highest probability of the highest known irrationality initiator probability. Using a 3x higher probability may help to ensure that any potential high consequence failure scenarios are identified and will help to motivate the development of a better estimation of the probability. If a failure scenario of a particular irrationality initiator that used the 3x higher probability is sufficiently probable, then this indicates the irrationality initiator probability needs to be better understood. However, if no failure scenarios are within a few orders of magnitude of the most likely failure scenario, then this is an indication that there is likely no further refinement of that irrationality initiator’s probability. It is worth noting that we do not advocate for setting the multiplier higher than 3x for irrationality initiators without well-founded probabilities. While such an approach would almost certainly highlight every single potential failure scenario caused by the irrationality initiator in question, setting the irrationality initiator probability needlessly high without a rigorous analysis to back up the choice is likely to overwhelm a user of this method with many failure scenarios that masquerade as being of high likelihood while in reality being of vanishingly small probability. This in turn may lead to much wasted time and effort to disprove all of the failure scenarios. The suggestion of a 3x multiplier is based on our prior professional experience as risk analysts and reliability engineers and from examining the sensitivity of several failure models to which we have access to changing initiating event probabilities.Whilewe believe the 3x multiplier is a good starting point, we recommend that systems engineering practitioners carefully examine the sensitivity of their own systems to initiating event probabilities and make adjustments as warranted and using their professional engineering judgment. We recommend that both the informative and uninformative prior methods are used to analyze irrationality initiators in the SoI. The uninformative prior can shed light on potential high consequence failure scenarios that otherwise may be missed and can also be used to perform sensitivity studies on the irrationality initiators. The informative prior quantifies failure scenarios in a way that can be directly compared with standard FFIP results. This may help practitioners to prioritize wheremoney and time is spent tomitigate potential issues. 3.3.2 Independent and dependent irrationality initiators In almost every implementation of FFIP that we have encountered, initiating events are exclusively considered to be independent from each other. The same is true in many PRA analyses. However, we suspect based on our professional practice and observations that irrationality initiators may have a higher likelihood of being dependent upon one another to some extent. In other words, if one irrationality initiator occurs, then it is more likely that another will occur at the same time. We propose that irrationality initiators should be modeled both as independent and dependent events. By analyzingmultiple irrationality initiators as single events, a practitioner can gain insight into scenarios where a system in an SoS begins emitting many irrationality initiators. This may help to identify “worst case scenarios” where completely unanticipated emergent system behaviors occur due to the SoI receiving several irrationality initiators at once. Recent research on external initiating events for autonomous robotic systems has indicated that unique emergent system behaviors not predicted by other research 526 VANBOSSUYT ET AL. methods can be caused by several external initiating events simultaneously occurring and interacting with one another inside of an SoI.59,89 We suggest that all possible irrationality initiator-dependent combinations be investigated. For example, in the case of three irrationality initiators [A, B, C], the following initiator-dependent combinations should be investigated: [A & B], [A & C], [B & C], and [A, B, & C]. A generalized formula to determine the number of dependent combinations is shown by Equation (1). Note that the formula intentionally subtracts 1 to acknowledge that the baseline case of no irrationality initiators being present in the SoI is assumed to have been previously assessed.
Optimum Simultaneous DG and Capacitor Placement on the Basis of Minimization of Power Losses
2013
摘要
and the results will also be discussed in detail.
SIGNIFICANCE OF LOAD MODELLING IN POWER SYSTEM DYNA
2006
摘要
ad modelling is a perennial source of consternation. Postmortem analyses of disturbance clude that load models must be adjusted to achieve an adequate match between m ulated behaviour. However the development of load models that are accurate over a w tem conditions requires, 1) testing that is undesirable for customers, and/or 2) mea aviour during infrequent disturbances. Furthermore, the stochastic nature of many lo d models that are accurate at one time may be inaccurate a short time later.
Power System Equipment Cyber-Physical Risk Assessment Based on Architecture and Critical Clearing Time
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
2018
摘要
With the trend of constructing Internet protocol (IP)-based systems, modern power grids are involving into integrated networks made up of cyber and physical infrastructure with the goal of improving stability, reliability, and efficiency. Cyber technology is the backbone of modern power grid operation, yet vulnerabilities in the cyber network can introduce cyber-enabled disruption of physical components, which may lead catastrophic outcomes. Thus, cyber-physical equipment assessment is needed for modern power grids to better prepare against unexpected contingencies. In this paper, the digital relay is representative of cyber-physical equipment in power grids since it is a connector between the cyber network and the physical infrastructure. This paper presents two methods to evaluate cyber-physical risk of all digital relays in a power system. These methods are based on cyber-physical architecture and critical clearing time respectively. The analysis is conducted on an 8-substation model with its cyber network and cyber-physical architecture. The ranks of each digital relay provide useful information for situational awareness in modern power grids. An online framework that evaluates cyber-physical assets in power systems from these two perspectives is presented.
A PMU-Based Method for Smart Transmission Grid Voltage Security Visualization and Monitoring
2017
摘要
With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading margin using PMU data from a wide-area monitoring system (WAMS) to construct the voltage stability boundary (VSB) of a transmission grid. Specifically, a new approach for online loading margin estimation that considers system load trends is proposed based on the Thevenin equivalent (TE) technique and the Mobius transformation (MT) technique. A VSB is then computed by means of real-time PMU measurements and is presented in a complex load power space. VSB can be utilized as a visualization tool that is able to provide real-time visualization of the current voltage stability situation. The proposed method is fast and adequate for online voltage security assessment. Furthermore, it enables us to significantly increase a system operator’s situational awareness for operational decision making. Simulation studies were carried out using different sized power grid models under various operating conditions. The simulation results are shown to validate the capability of the proposed method.
A Distribution Network Islanding Strategy Based on Topological Characteristics to Improve System Resiliency
2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)
2018
摘要
With the penetration of smart grid technologies, the reliability and stability of modern power systems could be further improved. However, large-scale power outages could still be caused when the power system is exposed to extreme conditions. The utilization of distributed generators (DGs) has risen significantly in the power system, and it plays a critical role to modernize the current power grid. The emerging smart grid technology, which attempts to enable more resilient power systems with DGs, makes a quick and efficient restoration of power systems possible. In this paper, DGs are introduced to enhance the restoration efficiency and success rate at the preliminary stage of network restoration. Then, the effect of DG's switching in points on areas of restoration islands in distribution network is investigated. Furthermore, based on the topological characteristics of scale-free networks and the discrete particle swarm optimization (DPSO) algorithm, an islanding scheme which aims to restore as many important loads as possible is proposed. The DGs are turned out to be effective resiliency resources for power system restoration. This paper will provide some useful insight into enhancing the power system resiliency in the face of extreme events such as natural or man-made disasters.
Multi-objective power management on smart grid
Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
2014
摘要
With the increasing number of unpredictable accidents and power shortages on utility systems, the need to improve the reliability and security of electric power networks is imminent. Energy management systems that use traditional computer-aided tools to monitor and control generation and transmission systems using supervisory control and data acquisition (SCADA) actually have low sampling and update rates. In recent years, wide area monitoring system (WAMS) can possibly meet these challenges based on the state-of-the-art data retrieval technology. WAMS makes it possible to monitor power utility networks in a real-time dynamic manner using phasor measurement units. These sensor devices can provide synchronized measurements using global positioning satellite systems (GPS). In this paper, we study the power management problem under different scenarios. We present several multi-objective optimization models which can provide a deeper insight into operations on smart grid. We also consider contingency constraints and optimal allocation of these sensor devices on utility systems.
Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines
International journal of environmental research and public health
2020
摘要
With the increasing demand for electricity transmission and distribution, single-phase grounding accidents, which cause great economic losses and casualties, have occurred frequently. In this study, a Bayesian network (BN)-based risk assessment model for representing single-phase grounding accidents is proposed to examine accident evolution from causes to potential consequences. The Bayesian network of single-phase grounding accidents includes 21 nodes that take into account the influential factors of environment, management, equipment and human error. The Bow-tie method was employed to build the accident evolution path and then converted to a BN. The BN conditional probability tables are determined with reference to historical accident data and expert opinion obtained by the Delphi method. The probability of a single-phase grounding accident and its potential consequences in normal conditions and three typical accident scenarios are analyzed. We found that “Storm” is the most critical hazard of single-phase grounding, followed by “Aging” and “Icing”. This study could quantitatively evaluate the single-phase grounding accident in multi-hazard coupling scenarios and provide technical support for occupational health and safety management of power transmission lines.
Power System Structural Vulnerability Assessment Based on an Improved Maximum Flow Approach
IEEE Transactions on Smart Grid
2018
摘要
With the increasing complexity of the power grid and the concerns on major blackouts, there is an urgent need for an efficient and effective tool to assess the power system structural vulnerability. To tackle this challenge, this paper proposes a maximum flow-based complex network approach to identify the critical lines in a system. The proposed method consists of two major steps. First, the power network is modeled as a graph with edges (transmission lines, transformers, etc.) and nodes (buses, substations, etc.). The critical scenarios are identified by using the principal component analysis and convex hull. Then the second step is to use an improved maximum flow-based complex network approach for topology analysis. Weighted vertices in the network are considered, enabling taking the selected operating conditions into consideration when identifying the vulnerable lines. The proposed method is validated using the western Danish power system. The vulnerable lines in the network are ranked. Simulation results demonstrate the effectiveness of the method by intentional attacks and comparison with the planning strategy from the system operator.
Blackout risk analysis and control of power system integrated with wind farm
2016 Chinese Control and Decision Conference (CCDC)
2016
摘要
With the increase of wind power penetration, the characteristics of the wind farm have brought a significant impact on the security of power system. It is urgent to study how to reduce the risk of cascading failures while improving the environmental benefits. In this paper, a cascading failure model containing wind farm is proposed, which considers wind power characteristics, such as the structure of wind farm, the randomness of power of wind farm, the virtual inertia control of wind turbine, and the disconnection response of wind turbine after short-circuit faults. In order to identify the key factors of blackout, decision tree is used to analyze results generated from this blackout model. Preventive control is adopted to decrease the probability or effect of critical attributes that can be found in decision tree. The blackout risk of IEEE 30 test system integrated with wind farm is analyzed. Several key factors, such as disconnection of wind turbines from the grid and certain transmission lines, are identified by decision tree. Besides, the effectiveness of the virtual inertial control of wind turbine, reactive power compensation and line construction is verified by simulation.
Risk assessment of power system security based on component importance and operation state
2014 International Conference on Power System Technology
2014
摘要
With the great increasing of power system scale and complexity, the risk of power system operating security has been a focus for researchers. The power system security is not only involve the real operation state of the system, which is the practice of traditional assessment methods generally used, but also needed to synthetically consider other important issues such as the influence of system structure and the otherness of different components. This paper presents a new method for risk assessment of the power system security. First of all, from the perspective of systematology, a component comprehensive importance index model was built considering the inherent properties of components in the system. Secondly, an improved low-voltage severity index and an improved overload severity index were built via introducing the component comprehensive importance model into the risk assessment method as the weight factor. And then, a severity model was set to characterize the severity of the balance of grid power flow distribution and the load losing, basing on the operation state of the system and the power flow entropy theory, Therefore, a risk assessment method of power grid security based on both component importance and operation state was proposed, At last, the simulation results of IEEE-30 system illustrates the rationality of the proposed method to assess grid N-1 contingency risk and better accuracy in identifying the risk of every grade in N-k fault series comparing to the traditional methods, thus the validity and feasibility of proposed method is proved.
Disturbance propagation mechanism based on the electromechanical wave theory
2016
摘要
With the development of power grid interconnection, the disturbances propagation behave as a sort of electromechanical waves. The study of the disturbance propagation mechanism in the interconnected power networks is of great importance for controlling the spreading of disturbance and improving the security level of power systems. In this study, the electromechanical wave equation is built based on the discrete inertia model of power networks. In order to describe the phase and amplitude variations, the wave transfer function is derived. Then, the propagation characteristics of different frequency disturbances are analysed. The corner frequency of the discrete inertia model is proposed. Furthermore, the frequency dispersion and local oscillation are revealed as well as their relationships with corner frequency. Computer simulations for a 50-generator chain network are used to verify the propagation characteristics of disturbances with different frequencies. The research work is beneficial to analyse the influence of disturbance and develop countermeasures for disturbance based on electromechanical wave theory.
The cut-off frequency of disturbance propagation in discrete inertia model of power networks
IEEE PES ISGT Europe 2013
2013
摘要
With the development of power grid interconnection, the disturbance propagation phenomena are more and more apparent which take the form of mechanical waves. Once a disturbance occurs, its propagation might cause cascading events and even large blackouts. However, with the help of advanced communications network in smart grid, new control strategies can be devised by the reveal of disturbance propagation mechanisms. In this paper, disturbance propagation in chained power network is studied from the point of view of network structure and parameters. The discrete inertia model of power systems is built. The increment motion equation of generator is formulated. Then, the wave transfer function is derived which can be used to describe the amplitude and phase variation of disturbance waves. The cut-off frequency of discrete inertia model is proposed to determine the upper limit of disturbance frequency. Furthermore, the computer simulations are carried out and the results demonstrate the validity of the proposed theory.
The disturbance propagation model of power grid considering induction-motor load
2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)
2015
摘要
With the development of power grid interconnection, once a disturbance occurs, the propagation of the disturbance take form of electromechanical waves. Therefore, the reveal of disturbance propagation mechanism is of great importance for the power system security. In this paper, the electromechanical transient process of induction-motor load is taken into consideration for the model of power grid in the electromechanical wave study. The consistence between generator and induction-motor load during disturbance propagation is proved. Then, the structural frame model of power networks considering induction-motor load for disturbance propagation is proposed based on structural frame model. Furthermore, the propagation equation of electromechanical wave in the basic unit of the proposed model is derived. Simulation results in IEEE 14 buses system are given to show the validity of the proposed model.
An Approach for Estimating Disturbance Arrival Time Based on Structural Frame Model
IEEE Transactions on Power Systems
2017
摘要
With the development of power grid interconnection, disturbance propagation phenomena are more and more apparent in the form of electromechanical waves. Once a disturbance occurs, its propagation might cause cascading events and even large blackouts. With the help of advanced communications networks in smart grids, new event-based protection systems can be devised by the reveal of disturbance propagation mechanisms. In this paper, a widely used measurement-based protection system is analyzed and the idea of event-based protection is proposed. By introducing the inverse process of lumped mass method, the impact scope of generator inertia is proposed. Then, the structural frame model of power networks for disturbance propagation is built, which is sectionalized homogeneously. The spatial heterogeneity of propagation velocity of the electromechanical waves is depicted. According to the constant velocity characteristic of the segments in the structural frame model, a weighted undirected graph is formulated. Then, the Dijkstra algorithm based shortest path searching method for arrival time of electromechanical wave is proposed. The simulations are carried out to demonstrate the effectiveness of the proposed electromechanical wave propagation model and disturbance arrival time estimation algorithm. The research work is one of the essential steps for realizing event-based protection strategies.
Blackout prevention: Managing complexity with technology
2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century
2008
摘要
With the development of electric power grid in China, some experiences in blackout analysis and prevention have been obtained. The experiences show that the security operations of bulk electric power systems depend not only on the technologies of system operation, analysis and control, but also on the management of power systems. This paper reviews the strategies of prevention cascading failures in China, and then discusses an emerging technology based on self-organized criticality theory for analyzing the cascading failures in the viewpoint of macro-scale. A framework of the future power system control centers to avoid blackouts is also described.