Athula D. Rajapakse

Support Vector Machine-Based Algorithm for Post-Fault Transient Stability Status Prediction Using Synchronized Measurements

The paper first shows that the transient stability status of a power system following a large disturbance such as a fault can be early predicted based on the measured post-fault values of the generator voltages, speeds, or rotor angles. Synchronously sampled values provided by phasor measurement units (PMUs) of the generator voltages, frequencies, or rotor angles collected immediately after clearing a fault are used as inputs to a support vector machines (SVM) classifier which predicts the transient stability status. Studies with the New England 39-bus test system and the Venezuelan power network indicated that faster and more accurate predictions can be made by using the post-fault recovery voltage magnitude measurements as inputs. The accuracy and robustness of the transient stability prediction algorithm with the voltage magnitude measurements was extensively tested under both balanced and unbalanced fault conditions, as well as under different operating conditions, presence of measurement errors, voltage sensitive loads, and changes in the network topology. During the various tests carried out using the New England 39-bus test system, the proposed algorithm could always predict when the power system is approaching a transient instability with over 95% success rate.

Online Monitoring of Voltage Stability Margin Using an Artificial Neural Network

In this paper, an artificial neural network (ANN) based method is developed for quickly estimating the long-term voltage stability margin. The investigation presented in the paper showed that node voltage magnitudes and the phase angles are the best predictors of voltage stability margin. Further, the paper shows that the proposed ANN based method can successfully estimate the voltage stability margin not only under normal operation but also under N-1 contingency situations. If the voltage magnitudes and phase angles are obtained in real-time from phasor measurement units (PMUs) using the proposed method, the voltage stability margin can be estimated in real time and used for initiating stability control actions. Finally, a suboptimal approach to determine the best locations for PMUs is presented. Numerical examples of the proposed techniques are presented using the New England 39-bus test system and a practical power system which consists of 1844 buses, 746 load buses, and 302 generator buses.

Electromagnetic transients simulation models for accurate representation of switching losses and thermal performance in power electronic systems

This work presents an electrothermal model of an insulated-gate bipolar transistor (IGBT) switch suitable for the simulation of switching and conduction losses in a large class of voltage-sourced converter (VSC)-based flexible ac transmission systems (FACTS) devices. The model is obtained by mathematical derivation of loss equations from the known submicrosecond device switching characteristics, and through the selection of appropriate differential equation parameters for representing the thermal performance. The model is useful in determining the devices heat generation, its junction temperature, as well as the cooling performance of the connected heat sinks. The model provides accurate results without recourse to an unreasonably small time step.

A Pattern Recognition Approach for Detecting Power Islands Using Transient Signals—Part I: Design and Implementation

A novel, pattern-recognition-based approach for fast detection of power islands in a distribution network is investigated. The proposed method utilizes transient signals generated during an islanding event to detect the formation of the island. A decision-tree classifier is trained to categorize the transient generating events as “islanding” or “non-islanding.” The feature vectors required for classification were extracted from the transient current and voltage signals through discrete wavelet transform. The proposed technique is tested on a medium-voltage distribution system with multiple distributed generators. The results indicate that this technique can accurately detect islanding events very fast.

Rotor Angle Instability Prediction Using Post-Disturbance Voltage Trajectories

A new method for predicting the rotor angle stability status of a power system immediately after a large disturbance is presented. The proposed two-stage method involves estimation of the similarity of post-fault voltage trajectories of the generator buses after the disturbance to some pre-identified templates and then prediction of the stability status using a classifier which takes the similarity values calculated at the different generator buses as inputs. The typical bus voltage variation patterns after a disturbance for both stable and unstable situations are identified from a database of simulations using fuzzy C-means clustering algorithm. The same database is used to train a support vector machine classifier which takes proximity of the actual voltage variations to the identified templates as features. Development of the system and its performance were demonstrated using a case study carried out on the IEEE 39-bus system. Investigations showed that the proposed method can accurately predict the stability status six cycles after the clearance of a fault. Further, the robustness of the proposed method was examined by analyzing its performance in predicting the instability when the network configuration is altered.

Location of DC Line Faults in Conventional HVDC Systems With Segments of Cables and Overhead Lines Using Terminal Measurements

Summary form only given. This paper presents a novel algorithm to determine the location of DC line faults in an HVDC system with a mixed transmission media consisting of overhead lines and cables, using only the measurements taken at the rectifier and inverter ends of the composite transmission line. The algorithm relies on the travelling wave principle, and requires the fault generated surge arrival times at two ends of the DC line as inputs. With accurate surge arrival times obtained from time synchronized measurements, the proposed algorithm can accurately predict the faulty segment as well as the exact fault location. Continuous wavelet transform coefficients of the input signal are used to determine the precise time of arrival of travelling waves at the DC line terminals. Two possible input signals, the DC voltage measured at the converter terminal and the current through the surge capacitors connected at the DC line end, are examined and both signals are found to be equally effective for detecting the travelling wave arrival times. Performance of the proposed fault-location scheme is analyzed through detailed simulations carried out using the electromagnetic transient simulation software PSCAD®. The impact of measurement noise on the fault location accuracy is also studied in the paper.

Traveling-Wave-Based Line Fault Location in Star-Connected Multiterminal HVDC Systems

Summary form only given. This paper presents a novel algorithm to determine the location of dc line faults in an HVDC system with multiple terminals connected to a common point, using only the measurements taken at the converter stations. The algorithm relies on the traveling-wave principle, and requires the fault-generated surge arrival times at the converter terminals. With accurate surge arrival times obtained from time-synchronized measurements, the proposed algorithm can accurately predict the faulty segment as well as the exact fault location. Continuous wavelet transform coefficients of the input signal are used to determine the precise time of arrival of traveling waves at the dc line terminals. Performance of the proposed fault-location scheme is analyzed through detailed simulations carried out using the electromagnetic transient simulation software PSCAD. The algorithm does not use reflected waves for its calculations and therefore it is more robust compared to fault location algorithms previously proposed for teed transmission lines. Furthermore, the algorithm can be generalized to handle any number of line segments connected to the star point.

Simulation tools for photovoltaic system grid integration studies

Photovoltaic power generation is growing at a rapid rate. Most new PV installations are grid-connected small-scale system. The impact of these installations on the grid operation need to be carefully studied to investigated. This paper presents the development of simulation tools required for such interconnection studies. The simulation tools were developed in the popular electromagnetic transient simulation program PSCAD/EMTDC and include a PV array model, maximum power point tracking controller model, and a grid connected inverter. An example of an interconnection study using the developed simulation tools is presented.

Isolation of Faults in Distribution Networks With Distributed Generators

This paper presents an agent-based protection scheme for distribution networks with distributed generators. The distribution network is divided into several network segments. The relay agents, which are located at the boundaries of these segments, can determine the direction of fault currents using the transients generated by the fault. Fault directions determined by the relay agents located at different points of the network are combined to determine the faulted segment. A fault direction identification technique, which uses the wavelet coefficient of the measured line currents, was developed for relay agents. The performance of the proposed protection scheme is investigated through simulation of a benchmark medium-voltage distribution system.

A Pattern-Recognition Approach for Detecting Power Islands Using Transient Signals—Part II: Performance Evaluation

Part I of this paper describes the design and implementation of an islanding detection method based on transient signals. The proposed method utilizes discrete wavelet transform to extract features from transient current and voltage signals. A decision-tree classifier uses the energy content in the wavelet coefficients to distinguish islanding events from other transient generating events. The verification tests performed in Part I, for a two generator test system having a synchronous generator and a wind farm, showed more than 98% classification accuracy with 95% confidence and a response time of less than two cycles. In Part II, the proposed methodology is applied to an extended test system with a voltage-source converter-based dc source. The proposed relays performance is compared with the existing passive islanding detection methods under different scenarios. Furthermore, the effect of noise on the performance of the proposed method is studied. The transient-based islanding detection methodology exhibits very high reliability and fast response compared to all other passive islanding detection methods and shows that the relay can be designed with a zero nondetection zone for a particular system.