Transient Security Assessment Research Articles

Power system preventive control aided by a graph neural network-based transient security assessment surrogate

In the context of the clean energy revolution and the high penetration of renewables and power electronics, the uncertainty level of operating states significantly increases, which brings new challenges to the safe and stable operation of power grids. Power system preventive control is an important measure to ensure the safe and stable operation of power systems by adjusting the active generation and nodal voltage of generators. In this paper, a power system preventive control algorithm aided by a Graph Neural Network (GNN)-based Transient Security Assessment (TSA) surrogate is proposed. A GNN-based fast contingency scanning model is constructed based on power network topology, which can predict the contingency scanning results rapidly only based on the power flow by transforming the original contingency scanning problem into the node classification problem on the GNN. The obtained GNN is then used as a surrogate model for TSA to speed up the solution of particle swarm optimization-based transient security-constrained optimal power flow. Numerical Tests are carried out in the IEEE-39 system and the test results indicate that the proposed method can significantly improve the efficiency without affecting the solution accuracy.

Power system transient security assessment based on multi-channel time series data mining

In the context of the clean energy revolution and the high penetration of renewables and power electronics, data-driven Transient Security Assessment (TSA) models can significantly reduce the computational burden of power system TSA and adapt to the quickly changing operating states of modern power systems. In this paper, a multi-channel time series data mining framework is proposed to enhance the performance of data-driven TSA models. During the training procedures, a Lagrangian dual framework is adopted to enhance the feature extraction ability of different types of disturbed system trajectories. The proposed method is adopted to an ordinary Long Short-Term Memory (LSTM) model and numerical tests are carried out in the IEEE-39 system. The test results show that the proposed method can effectively improve the performance and generalization ability of the data-driven TSA model.

Power system transient security assessment based on deep learning considering partial observability

Due to the ever-increasing complexity of power systems, transient stability analysis has been reshaped into a complicated and critical issue. The real-time identification of the transient stability status would assist the power system operators in decision-making during critical events. This paper proposes a combined transient security assessment (TSA) method based on convolutional neural networks (CNNs) and a novel feature selection technique using sensitivity analysis. CNN benefits from the keen ability to understand raw data features, which decreases the required memory space. The proposed sensitivity analysis technique for feature selection can lead to a trade-off between dependency on measurable data, accuracy, and computational complexity. Furthermore, in the proposed method, an information-theoretic measure, namely mutual information (MI), is used to handle partial observability conditions. The simulation results validate the proposed method's accuracy and robustness using several metrics and comparisons with the state-of-the-art and previously presented methods.

Preventive control for power system transient security based on XGBoost and DCOPF with consideration of model interpretability

This paper proposes a new approach for online power system transient security assessment (TSA) and preventive control based on XGBoost and DC optimal power flow (DCOPF). The novelty of this proposal is that it applies the XGBoost and data selection method based on the 1-norm distance in local feature importance evaluation which can provide a certain model interpretability. The method of SMOTE+ENN is adopted for data rebalancing. The contingency-oriented XGBoost model is trained with databases generated by time domain simulations to represent the transient security constraint in the DCOPF model, which has a relatively fast speed of calculation. The transient security constrained generation rescheduling is implemented with the differential evolution algorithm, which is utilized to optimize the rescheduled generation in the preventive control. Feasibility and effectiveness of the proposed approach are demonstrated on an IEEE 39-bus test system and a 500-bus operational model for South Carolina, USA.

Trajectory sensitivity based preventive transient stability control of power systems against wind power variation

The penetration of high-level wind power has significantly made the power system’s operation complicated. The random power variation of the wind farms may deteriorate the power system’s transient stability degree since it alters the operating state of the power system. In this paper, based on trajectory sensitivity and Extended Equal Area Criterion (EEAC) method, a new preventive control approach is proposed to optimally balance the wind power variation by rescheduling synchronous generators while maintaining the transient stability for credible contingencies. The whole problem is formulated to a programming problem with linear stabilization constraints. The proposed method is validated on the New-England 10-machine 39-bus system by using commercial simulation software Transient Security Assessment Tool (TSAT), and both single- and multiple-contingency cases are tested. Simulation results verify its satisfactory performance on control effectiveness, computational efficiency, transparency, and accuracy.

Synchronised measurements based transient security assessment of power systems using AdaBoost classifiers

This study proposes an adaptive boosting (AdaBoost) algorithm for precise and accurate prediction of transient security assessment of power systems using synchronised measurements. The proposed approach (PRPA) also determines the generator coherent state as well as the synchronism status of each generating unit. The PRPA consists of three classifier models, in which classifier I determines the transient security status and classifier II is used to determine the generator coherency. Classifier III is a hybrid classifier, which determines the individual generator synchronism state for a given operating condition. This hybrid classifier consists of an array of parallel classifiers, where one classifier is assigned to each generating unit of the power system. For this assessment, the measured rotor angles of the generators are used as inputs to the proposed classifier models. In classification stage, several weak classifiers are combined in a linear manner to construct a strong classifier. The performance of the AdaBoost algorithm is further improved by a new weight updation strategy using fuzzy clustering thresholding technique. Simulation results obtained from IEEE 14-bus, IEEE 30-bus and Indian 246-bus systems reveal that the PRPA can enhance the overall monitoring and assessment of power system using synchronised measurements.

Transient Stability Assessment Using Individual Machine Equal Area Criterion PART III: Reference Machine

The analysis of the transient stability of a multimachine system via the use of a few machines is a promising technique for transient security assessment. This paper proposes a genuine nonglobal direct-time-domain method that is developed from the previous COI-reference-based IMEAC method. In this paper, the reference machine (RM) is chosen as a real machine that does not separate from the system after fault clearing. The key concept of this paper is to select the reference machine (RM) first and then replace the COI with the RM during the post-fault period in the transient security assessment. In this manner, the motions of all machines in the system are redefined in RM reference. Furthermore, it is found that the Kimbark curve of the RM-reference-based critical machine has a distinctive quasi-sinusoidal characteristic, and thus the curve is predictable after fault clearing. Following the individual-machine thinking, the stability analysis of the multimachine system is transformed into monitoring the stability state of a few RM-reference-based critical machines, which completely avoids the usage of COI. The simulation results show the effectiveness of the proposed method in the transient stability analysis of multimachine systems.

Damping Nomogram Method for Small-Signal Security Assessment of Power Systems

This paper reviews the main concepts about power systems security assessment and describes the voltage security assessment (VSA), the transient security assessment (TSA) and the small-signal security assessment (SSA) of electrical power systems. Most methods of SSA are based on the calculation of oscillation modes of power systems and the evaluation of their damping factors. The objective of the power system security assessment is to determine the distance that these systems are to certain security boundary. In small-signal security assessment case, the security limits are, in general, associated to a minimum secure damping factor of the oscillation modes. This paper proposes a nomogram method based on the analysis of oscillation damping factors to be used for small-signal security assessment of power systems and describes its computational development.

Preventive Control for Transient Security with Generation Rescheduling Based on Rotor Trajectory Index

The increasing need to improve transient security assessment of existing or forecasted operating conditions of networks by power system operators is major concern of the power system security monitoring problem at the Energy Management Systems. This paper proposes a preventive control of transient stability with generation rescheduling based on rotor trajectory index obtained using time domain simulations. This index may help power engineers in making operational decision and to obtain a generation configuration with better transient security dispatch. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus New England system for a three phase fault at different loading conditions with single and multiple line outage cases.

STATCOM을 사용한 다기 전력 계통의 버스 전압 조절을 위한 모델 기반 PID 제어기 설계

The complexity and severe nonlinearity of multi-machine power systems make it difficult to design a control input for voltage regulation using modern control theory. This paper presents a model-based PID control scheme for the regulation of the bus voltage to a desired value. To this end, a fourth-order linear system is constructed using input and output data obtained using the TSAT (Transient Security Assessment Tool); the input is assumed to be applied to the grid through the STATCOM (STATic synchronous COMpensator) and the output from the grid is a bus voltage. On the basis of the model, it is identified as to which open-loop poles of the system make the response to a step input oscillatory. To reduce this oscillatory response effectively, a model-based PID control is designed in such a way that the oscillatory poles are no longer problematic in the closed loop. Simulation results show that the proposed PID control dampens the response effectively.

Measurement-based Estimation of the Composite Load Model Parameters

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

Classification and Assessment of Power System Security Using Multiclass SVM

Security assessment and classification are the major concerns in real-time operation of electric power systems. This paper proposes a multiclass support vector machine (SVM) classifier for static and transient security assessment and classification. A straightforward and quick procedure called the sequential forward selection method is used for a feature selection process. The security status of any given operating condition is classified into four modes, viz., secure, critically secure, insecure, and highly insecure, based on the computation of a security index. The proposed SVM-based pattern classifier system is implemented and tested on standard benchmark systems. The simulation results of the multiclass SVM classifier are compared with least-squares, probabilistic neural network, extreme learning machine, and extreme SVM classifiers. The feasibility of implementation of the proposed classifier system for online security evaluation is also discussed.

Wind Farms With HVdc Delivery in Inertial Response and Primary Frequency Control

This paper develops a coordination control strategy for wind farms with line commutated converter-based HVdc delivery for participating in inertial response and primary frequency control. The coordination philosophy is to feedback the grid frequency and its derivative and adjust the delivery power of the HVdc link according to the feedback signals. The feedback loop employing the derivative of the grid frequency aims to improve the inertial response while the feedback loop employing the grid frequency deviation introduces a droop at the rectifier control loop. When the grid frequency is too high or too low, active power flow through the HVdc link will be ramped down or up. In turn, the wind generation will increase or decrease the blade angles to reduce or increase the captured wind power through pitch control. A case study demonstrates the effectiveness of the inertial enhancement and frequency droop in HVdc control. Simulation results in transient security assessment tool are given.

A new BVM based approach to transient security assessment

AbstractMachine Learning techniques have been extensively used in Power Systems Analysis during the last years. This paper describes a ball vector machine based algorithm for on‐line transient security assessment of large‐scale power systems. The proposed ball vector machine based security assessment reduces the training time and space complexities in comparison with support vector machines, artificial neural networks, and other machine learning based algorithms. In addition, the proposed algorithm has less support vectors and therefore is faster than existing algorithms for on‐line applications. A new decision tree based feature selection technique has been presented, too. The proposed ball vector machine based algorithm has been applied to New England 39‐bus test system. The simulation results show the effectiveness of the proposed algorithm for on‐line transient security assessment procedure. Copyright © 2010 John Wiley & Sons, Ltd.

Evaluation of small signal stability of a power system

In reality, a power system is never in steady-state, as there are persistent fluctuations in load levels with associated adjustments in generation. The growing complexity of power systems, as well as the system exposition to various contingencies, have exacerbated the system's steady-state condition. Small disturbances that are always present in power system networks include small variations in loads, generation and switching operation of power system equipment. It is important to maintain the load-generation balance such that the system frequency remains nominal. Multiple severe contingencies with complex interaction would cause system instabilities, and thus deteriorate the system condition. This paper explores transient stability of a power system subjected to small disturbances using time domain analysis, eigen-values analysis, participation factors analysis, and transient security assessment using transient security index. Simulations have been conducted on the IEEE 14-bus system and the results presented.

A new ultra‐fast contingency screening algorithm without time‐domain simulation for online transient security assessment

AbstractThis paper proposes a new ultra‐fast contingency screening (CS) method for the transient security assessment (TSA). The method is based on the Single Machine Equivalent (SIME), but computes the critical clearing times (CCT) for given disturbances without the use of time‐domain simulations. All generators and loads are represented by a classical model and constant impedance model, respectively. The critical clustering is done using two stability indices, which are defined as the ratio of the accelerating power to the synchronizing power coefficient and the accelerating area to the decelerating area, respectively. Finally, the CCT is calculated using the equal‐area criterion to the equivalent one‐machine infinite‐bus system with the assumption that the rotor angles of the critical generators increase uniformly and the rotor angles of the non‐critical ones remain constant. The proposed CS method is tested on the 950‐bus, 230‐machine, 60‐Hz KEPCO system. Copyright © 2007 John Wiley & Sons, Ltd.

A novel tool for transient stability analysis of large-scale power systems: Its application to the KEPCO system

Time-domain simulation is an important tool for power system dynamic analysis. We solve a set of differential and algebraic equations (DAE) in order to study the dynamic behavior of power systems. These power systems include thousands of generators, exciters, turbine-governors, loads, and other devices. The resultant large-scale DAEs are very difficult to handle and solve. Nevertheless, solution techniques are needed to not just guarantee accuracy but have computational efficiency. In this paper, we report on a novel tool that we developed to deal with time-domain simulation for dynamic analysis and operation of large-scale power systems. The tool has several major features related to transient stability analysis, contingency screening, and ranking. We mainly discuss the structure of this tool and the accuracy of the included dynamic models. Also, the paper proposes a new load model to overcome the low-voltage problem. The proposed technique provides a good performance and convergence when the terminal voltage is below some predefined value. Compared to the commercial tools, the developed tool is numerically well conditioned by introducing the ZIP model algorithm. This tool has been used to support and enhance power engineering education at both the undergraduate and graduate levels. In the case study, simulation results were validated through comparative simulations with the Power System Simulator for Engineering (PSS/E) and Transient Security Assessment Tool (TSAT).

Damping Analysis using IEEEST PSS and PSS2A PSS

This paper scrutinized the damping effects of installing the prototype PSSs by a transient analysis for eight buses of faults in the South Korean power system. The PSSs used have the co-PSS blocks for IEEEST model with a single input and the co+power PSS blocks for PSS2A model with dual inputs. The simulation tool was a TSAT(Transient Security Assessment Tool) developed by Powertech Labs Inc. The voltages of the transmission line for simulations were 765kV and 345kV, and the faults for eight cases were sequenced by considering the open state and the close state of the lines. In the simulations, the three-phase line to ground (L-G) fault generated different points for each region. The simulations were compared to the cases of no PSS, partial IEEEST and PSS2A, absolute IEEEST, and absolute PSS2A to show that the power system oscillation can be effectively damped by PSS modules. Simulations were conducted to confirm the effectiveness for the KEPCO (Korea Electric Power Corporation) power system.

Transient security assessment using multivariate polynomial approximation

This paper presents an efficient method for transient security assessment. The proposed method exploits the computational efficiency of linear estimation methods to determine an accurate nonlinear mapping function. The novelty of the proposed method is that a nonlinear transformation is applied to the original variables, voltage magnitudes and phase angles, so that the mapping function is approximately linear in terms of the transformed variables. The linear function obtained using the transformed variables is indeed nonlinear in terms of original variables. The attractiveness of this method is that the estimated function is not a linearized approximation although a linear estimation method is used. The potential of the proposed method is demonstrated using the New England 39-bus system and a larger power system with 470 buses.

A New Tool for Large Scale Power System Transient Security Assessment

A New Tool for Large Scale Power System Transient Security Assessment