Post-disturbance Voltage Research Articles

Short-term voltage instability prediction using pre-identified voltage templates and machine learning classifiers

System operators use different procedures to detect disturbances which can lead to short-term voltage instability. These schemes are designed using the domain knowledge and generally specific for the corresponding system. The design procedure of such schemes is heuristic and cannot be directly applied to any other power system. This paper proposes a data-driven approach to predict short-term voltage stability using set of post-disturbance voltage templates and a machine learning-based classifier. In this scheme, a set of voltage templates corresponding to stable/unstable events is identified for selected buses using a suitably generated training data set. The proximity of real-time voltage trajectory to each of the template is computed and input to a trained machine learning classifier to predict the short-term voltage stability status. The proposed approach is validated using IEEE Nordic test system. The investigations show that this method provides accurate short-term voltage stability predictions. Furthermore, impact of adverse phenomena such as measurement noise and missing data on the proposed method is analyzed to confirm the robustness of this scheme in particle environments. © 2017 Elsevier Inc. All rights reserved.

Transient stability assessment application using post-disturbance voltage fluctuations in a multi-machine power system

Transient stability analysis programs are typically based on step-by-step numerical integrations of power-system models to simulate system dynamic behaviors. Unfortunately, these approaches are inadequate for dealing with the changing overall system conditions. For years, direct methods have held the promise of providing real-time stability assessments; however, they have presented several challenges with rotor angle-based theories. The angle-based common reference, such as the center of inertia, must be updated in each measurement instant, and this calculation requires the connectivity status of all generators. In addition, the field-angle difference data can suffer from errors, and an ex-post analysis needs many phasor measurement units. This study addresses these challenges with novel methods provided with voltage-based theoretical foundations because voltage is an easily available information. The proposed method monitors or simulates the post-disturbance voltages and calculates the product voltage deviation and rate of voltage change as an indicator of the post-disturbance transient instability. A relationship between the proposed index and the transient stability in a multi-machine power system is formulated, and the method effectiveness is tested through a simulation on a New England power system.

The Extension of the Method for the Out-of-step Condition Prediction using Post-disturbance Voltage Fluctuations in a Three-machine Power System

The Extension of the Method for the Out-of-step Condition Prediction using Post-disturbance Voltage Fluctuations in a Three-machine Power System

The Novel Method for Out-of-step Condition Prediction using Post-disturbance Voltage Deviations

The Novel Method for Out-of-step Condition Prediction using Post-disturbance Voltage Deviations

An Accelerated Preventive Agent Based Scheme for Postdisturbance Voltage Control and Loss Reduction

In this paper, a novel agent based dynamic Volt/Var control approach is introduced, by which the voltage security (i.e., voltage profile and mid- and long-term stability) can be improved and also power loss is reduced under postdisturbance condition and in a wide-area manner. The proposed scheme employs organized multiagent system to preserve voltage magnitude of all busbars within permissible range and reduction of power losses after any disturbance through appropriate coordination of reactive power sources. To accelerate exploitation of on-load tap changers (OLTCs) as well as suppressing the possibility of encountering voltage instability which may be initiated by them, a preventive scheme based on sensitivity analysis is proposed which determines efficient number of multitap changes of OLTCs. To evaluate the effectiveness of the introduced algorithm, different scenarios have been performed in Nordic 32 test system, where the numerical results in all cases demonstrate the effectiveness and reliability of the proposed scheme.

Dynamic Voltage Support by TL-PV Systems to Mitigate Short-Term Voltage Instability in Residential DN

Recently, transformerless (TL) inverters are being extensively used in small-scale photovoltaic (PV) systems due to their compact-size, lighter-weight, lower-cost and higher-efficiency compared to their counterpart with transformer. However, the growing penetration of these small-scale based PV systems and low-inertia induction motor (IM) loads in low-voltage distribution networks (DNs) make the grid more vulnerable to short-term voltage stability (STVS). Hence, this paper thoroughly examines the STVS of DN with high-penetration of TL-PV units, and provides countermeasures by TL-PV systems to mitigate any short-term voltage instability. The detailed dynamic model of the TL inverter is developed first. Next, three control strategies: (1) constant peak current (CPC), (2) constant active current (CAC), and (3) constant active power (CAP) with low voltage ride through (LVRT) and dynamic voltage support (DVS) capabilities are proposed to improve STVS. The impacts of different level of PV penetrations and LVRT capability of TL-PV inverters on the STVS are explored. Moreover, countermeasures, such as LVRT with CAC and CAP controls and DVS by the TL-PV systems are designed and implemented. Several case studies are carried out on an IEEE 4 bus system first, and later extended to IEEE 13 node test feeder. The results show that DVS can further improve STVS in residential DNs. In addition, CAP and CAC control strategies can speed-up the postdisturbance voltage recovery compared with the conventional CPC control.

A predictive agent-based scheme for post-disturbance voltage control

In this paper a predictive scheme for dynamic voltage control is proposed, which maintains voltage security (both voltage stability and voltage profile) of power system, in a wide area manner. The proposed algorithm, upon detecting any voltage violation (both under- and/or over-voltages), employs organized multi-agent system (OMAS) in order to coordinate the employment of reactive power devices in returning voltage magnitudes of all buses to the acceptable range and steady behaviour. In order to achieve high benefits of power system response, each agent takes advantage of a predictive scheme, which is based on the corresponding bus voltage trend. By this predictive characteristic, each agent coordinates its command for remedial action with the prediction of bus voltage destination. Moreover, this predictive characteristic is extended to consider incoming remedial actions (or to compensate the latency in activation of previously decided remedial actions). These predictive characteristics lead to making a smooth waveform and reducing the number of needed remedial actions. The performance of the proposed scheme against different scenarios in Nordic32 test system is presented, where the results illustrate effectiveness and robustness of the proposed scheme.

Post-Disturbance Transient Stability Status Prediction Using Synchrophasor Measurements

This paper presents a novel method to early predict the transient stability status of a power system after being subjected to a severe disturbance. The proposed technique is based on rate of change of voltage vs. voltage deviation $({\hbox {ROCOV}}\mathchar707B \Delta{\hbox {V}})$ characteristics of the post-disturbance voltage magnitudes obtained from synchrophasor measurements. Converging and diverging nature of the post-disturbance trajectories on ${\hbox {ROCOV}}\mathchar707B \Delta{\hbox {V}}$ plane is used to recognize the transient stability status. The proposed technique is computationally simple and fast compared to the rotor angle based transient stability prediction methods. Offline simulations and real-time experimental studies carried out for the IEEE 39-bus test system showed over 99% overall success rate under symmetrical and asymmetrical faults as well as changes in pre-disturbance conditions and network topology changes.

Overvoltages due to Synchronous Tripping of Plug-in Electric-Vehicle Chargers Following Voltage Dips

Plug-in electric vehicle (PEV) charging equipment incorporates protection that ensures that grid disturbances do not damage the charger or vehicle. When the grid voltage sags below 80% of nominal, undervoltage protection is likely to disconnect the charging load from the grid. Most PEV charging will occur overnight, when non-PEV load is at a minimum. This paper argues that PEV voltage-sag response, when synchronized across large numbers of PEVs, could result in the loss of a significant proportion of the total load. It is shown that this load loss can lead to unacceptably high voltages once the initiating event has been cleared. This paper explores the nature of this voltage-rise phenomenon. Analysis tools are developed to assist in determining PEV loading conditions that demarcate acceptable postdisturbance voltage response from unacceptable outcomes. Two examples, based on standard distribution test systems, are used to illustrate PEV-induced overvoltage behavior, and demonstrate applications of the analysis tools.

Application of a modal-based transient energy function to a large-scale stressed power system: Assessment of transient stability and transient voltage dip

In this paper a modal-based transient energy function (MTEF) is used to analyse a large-scale stressed power system exhibiting the inter-area mode phenomenon. The analysis consists of two parts. In the first part, direct transient stability analysis of the inter-area mode is conducted by determining the dominant modes of oscillation involved in the non-linear interaction. Using the machines that have large participation in these modes, relevant disturbed machine groupings are formed. These groupings are then used in the MTEF method for transient stability assessment. In the second part, the MTEF is also used to predict the post-disturbance voltage dip at various buses using an energy based criteria. The developed procedures are tested on a 161-generator coherency-based dynamic equivalent of the Northern States Power system which is part of the Mid-continent Area Power Pool in North America.