A neural network-based approach for on-line dynamic stability assessment using synchronizing and damping torque coefficients

This paper presents an artificial neural network (ANN)-based on-line approach to evaluate the dynamic stability of a single machine infinite bus system. The proposed on-line assessment scheme is based on estimating the synchronizing and damping torque coefficients as dynamic performance indices. The two performance indices are estimated from on-line measurements of the changes in the rotor angle, speed and electromagnetic torque using a three-layer feedforward neural network with back propagation. The results show that the proposed method is very promising and encouraging for fast real-time evaluation of the dynamic performance of power systems.     

Simulation Study on On-Line MTPA/MTPV Trajectory Tracking in PMSMs with Power Management

Abstract

This paper proposes an on-line maximum torque per ampere (MTPA)/maximum torque per voltage (MTPV) trajectory tracking method in permanent magnet synchronous machines (PMSMs) with power management. The on-line MTPA/MTPV machine current trajectory tracking algorithm is developed from PMSM model. Maximum source current and machine current are regulated to enhance hardware protection during machine current trajectory tracking. The maximum source current management is achieved by iterating within the current trajectory tracking algorithm over continuous torque command modifications based on power flow analysis, and the maximum machine current management is achieved by torque command limiting based on current angle modulation. Different from the existing techniques in literature, the proposed method has an unique feature of providing on-line regulation of source current, while maintaining on-line MTPA/MTPV trajectory tracking in PMSMs. It also provides machine and inverter overcurrent regulation to enhance their protection. In addition, the proposed method is flexible to tune and does not require off-line calibration. The effectiveness of the proposed method is confirmed by simulation results in MATLAB.     

DYNAMIC BRAKING RESISTOR-REACTOR SWITCHING STRATEGIES THROUGH A NOVEL LINEAR TRANSFORMATION TECHNIQUE

ABSTRACT

Optimum switching strategies for dynamic braking resistor and shunt reactor is proposed for transient stability of a single machine infinite bus power system. The strategy is derived through a novel method of transforming the nonlinear dynamic model of the system to linear one. The simple optimum strategies derived from the linear model was observed to be very effective in stabilization.     

AN APPROACH TO IMPROVING DYNAMIC STABILITY OF SUPERCONDUCTING GENERATOR USING Q-AXIS DAMPER WINDING FEEDBACK CONTROL

Abstract

Q-axis damper Minding feedback control offers a means for improving dynamic performance of superconducting generator.This paper is an investigation of dynamic characteristics of a machine with such a control system. A model based on Park's equations in the form of Fourier Transform of the machine is proposed and used to simulate the dynamic behaviour of the generator after the occurance of a small disturbance of torque or voltage of the power source.From the computer simulation results, it was proved that the system can offer sufficient damping effects and an optimum design can be reached by choosing parameters of the control system carefully. Also,it is a more economic method compared with those proposed by others [4,5,6].     

DETERMINING TOPOLOGICAL CHANGES AND CRITICAL LOAD LEVELS OF A POWER SYSTEM BY MEANS OF ARTIFICIAL NEURAL NETWORKS

ABSTRACT

In this paper, an investigation is done of the possibilities of implementing multi-layered artificial neural networks in analyzing the dynamic stability of an power system during load and topology changes. To solve this problem, a multi-layered neural network is used whose inputs are the state vector components, and whose outputs are encoded line outages and the real component of dominant eigenvalues of the system state matrix of the power system. The neural network is trained through the error back-propagation method. The proposed methodology is tested on an power system with ten nodes and four generators. The obtained results indicate the attractiveness of “on-line” application possibilities of multi-layered neural networks in order to efficiently evaluate the stability of an power system during conditions of load and topology change.     

CORRESPONDENCE: THE FLUX-BRIDGE MACHINE

ABSTRACT

This note describes a new kind of electromagnetic machine whose action is based on the change of flux linkage between two stationary coils-field and armature coils-when a segmental rotor moves between them. The machine differs from conventional inductor machines in having a dynamic component of emf in addition to the usual pulsation component, and also the windings are disposed on separate machine members. The basic principles are outlined and simple analysis is attempted. Possible modes of application are proposed.     

A ROBUST ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR DYNAMIC STABILITY ASSESSMENT

ABSTRACT

This paper presents a robust artificial neural network technique to assess the on-line dynamic stability of power system. Efforts have been made to minimize the error in dynamic stability assessment by optimising the size and introducing more sensitive information in training vector. The problem has been attempted with Kohonen's self-organising feature map (SOFM) to classify the states of power system. The main reason which inspired the authors to apply Kohonen's SOFM technique is to avoid local minima that saturate the learning process in back-propagation algorithm. Conventional QR algrithm in conjunction with S-matrix method is used to allocate dynamic stability indices to output neurons.     

Influence of Self-Tuning Control Techniques on the Dynamics of a Synchronous Generator Unit

ABSTRACT

The recent development In microprocessor technology makes Implementation of advanced control strategies feasible at the generating level. A self-tuning (ST) proportional-plus-lntegral-plus-derivative (PID) digital automatic voltage regulator (DAVR) for a large synchronous machine is proposed and the influence of this regulator on the generator dynamic and transient stability is investigated. The algorithm for this regulator combines a least-square estimator with a digital PID control algorithm. The parameters of the PID control algorithm are computed and updated according to the estimated model. The dynamic performance of the machine when equipped with a digital PID governor is also presented. A comparison of the computer results as obtained from the simulation study are compared with the available experimental results.     

DESIGN OF VARIABLE STRUCTURE CONTROLLER FOR STATIC VAR COMPENSATOR

ABSTRACT

Static Var Compensator (SVC) is a relatively new kind of reactive power and voltage control device. It can be used not only to improve dynamic and transient stability of power system, but is especially suitable for voltage control of long distance bulk power transmission lines. To enhance the performance of SVC, in addition to voltage control (main control), a supplementary control (auxiliary control) is required. Variable Structure (VS) Stabilizer is proposed in this paper, as supplementary controller to SVC. The machine, excitation and SVC dynamics are considered. In this paper, a systematic procedure for evaluating gains for sliding mode to occur is presented. The switching vector is constructed using pole-assignment method. Trial and error, and heuristics approach is completely avoided for evaluating the gains in the sliding mode     

DESIGN CONSIDERATIONS FOR A 2000 MVA SUPERCONDUCTING GENERATOR WITH ROTOR INERTIAL SHIELDING PROTECTION*

ABSTRACT

The principle of the double rotor superconducting machine is applied to the design of a 2000 MVA generator. The basic form of the machine is described as well as the main considerations and objectives of the design. The effects of faults are studied and compared to those of an identical conventional superconducting generator. The dynamic stability under steady-state and fault transient conditions is examined. Finally, the specific dimensions and characteristic parameters of the 2000 MVA machine are given as applied to several different designs of the free Electromechanical Inertial Shield.     

An Improved On-line Contingency Screening for Power System Transient Stability Assessment

This paper presents a contingency screening method and a framework for its on-line implementation. The proposed method carries out contingency screening and on-line stability assessment with respect to first-swing transient stability. For that purpose, it utilizes the single machine equivalent method and aims at improving the prior developed contingency screening approaches. In order to determine vulnerability of the system with respect to a particular contingency, only one time-domain simulation needs to be performed. An early stop criteria is proposed so that in a majority of the cases the simulation can be terminated after a few hundred milliseconds of simulated system response. The method’s outcome is an assessment of the system’s stability and a classification of each considered contingency. The contingencies are categorized by exploiting parameters of an equivalent one machine infinite bus system. A novel island detection approach, appropriate for an on-line application since it utilizes efficient algorithms from graph theory and enables stability assessment of individual islands, is also introduced. The New England and New York system as well as the large-scale model of the Continental-European interconnected system are used to test the proposed method with respect to assessment accuracy and computation time.     

Theory and application of dynamic aging for life estimation inmachine insulation

After a brief discussion on possible on-line indicators of aging, this paper presents a concept of dynamic aging theory (DAT). Based on the philosophy of a DAT, a dynamic multistress aging model is proposed. Necessary DAT formulation and software have been developed for testing the model against laboratory aging data. In this study, dynamic stagnation voltage (DSV), a derived partial discharge parameter, and the groundwall insulation response to a traveling acoustic wave have been found to be the most appropriate parameters for assessment of remaining insulation machine life. This approach is shown to be a meaningful and practical solution to a very complex problem. Although this study is in its initial stage, it does show significant promise as an on-line tool for dynamically predicting remaining life based on DAT and other appropriate feedback measures     

On-Line Transient Stability Assessment and Enhancement by Pattern Recognition Techniques

Abstract

This paper presents a new candidate method for on-line transient security assessment and enhancement based on Pattern Recognition techniques.

Transient state variables are used as primary features and the classifier is obtained in two phases, through the combination of an optimum discriminant transformation together with a probabilistic procedure. The proposed security functions can be further refined by means of a second level classifier based on an optimal discriminant plane and using a weighted K nearest neighbour rule.

Finally it is shown that this method provides also an efficient and simple tool for on-line preventive control.

Extensive results obtained for several contingencies in the CIGRE test system are presented and discussed.     

INDUCTION MOTOR DRIVE STABILIZATION WITH STATOR CURRENT FEEDBACK

ABSTRACT

The use of state feedback to control Induction motor drive systems is examined. Using the machine currents and speed as the system states, a general linearized formulation of the problem is derived. This formulation has the advantages of previous forms based on complex variable analysis, but is not subject to the limitations of that method.

The proposed model Is used to study machine control with stator current feedback. The results show that stator current feedback can be used to improve the dynamic characteristics of the drive system. Comparisons of stator current control with the uncontrolled machine and with the slip controlled machine are presented over the range of operating speed, load, and inertia. In all cases, advantages of current controlled operation can be seen.     

A GENETIC-BASED POWER SYSTEM STABILIZER

ABSTRACT

A Genetic-based Power System Stabilizer (GPSS) is presented in this paper to improve power system dynamic stability. The proposed GPSS parameters are optimized using Genetic Algorithms (GA). The main advantage of the proposed GPSS is that far less information than other design techniques is required without the need for linearization process. Time domain simulations of a synchronous machine subject to major disturbances are investigated. The performance of the proposed GPSS is compared with that of conventional lead-lag power system stabilizer (CPSS) to demonstrate the superiority of the proposed GPSS. The effect of parameter changes on the proposed stabilizer performance is also examined. The results show the robustness of the proposed GPSS and its capability to enhance the system damping over a wide range of operating conditions and system parameter variations.     

Prediction of dynamic voltage stability status based on Hopf and limit induced bifurcations using extreme learning machine

Evaluation of voltage stability status considering its dynamic boundaries is a key issue for saving global stability of power systems. However, this evaluation is a computationally demanding task and its implementation is very hard (if not impossible) for on-line environments such as dispatching centers of power systems. In this paper, a new viewpoint for the problem based on modeling it as a forecast process is proposed, which can be implemented with a low computation burden for practical power systems. For this purpose, a voltage stability classification model considering Hopf and limit induced bifurcations is proposed and a new forecast strategy to predict voltage stability class label based on the proposed classification is suggested. The suggested forecast strategy is composed of an information theoretic feature selection technique, extreme learning machine (ELM) as the forecast engine and a line search procedure to fine-tune the settings. The effectiveness of the proposed classification model and forecast strategy is extensively illustrated on the New England 39-bus and IEEE 145-bus test systems.     

DETERMINATION,BY KOHONEN NETWORK,OF THE GENERATOR COHERENCY IN DYNAMIC STUDIES

ABSTRACT

For on-line security assessment, mere is a need for a tool which, during a disturbance, will quickly recognize impacted system components. A Kohonen artificial neural network is described which can be used for coherency identification among generators. Additional information provided by this method makes it better than the conventional approach used to identify coherency for dynamic equivalencing. The method is tested on two representative power systems.     

A feed-forward artificial neural network with enhanced feature selection for power system transient stability assessment

This paper describes an approach where an artificial neural network is used to predict the stability status of the power system. This efficient and robust approach combines the advantages of the time–domain integration schemes and artificial neural network for on-line transient stability assessment of the power system. The transient stability index has been obtained by the extended equal area criterion method and is used as an output of the neural network. Two feature selection techniques have been used to identify the input variables best suitable for training. The proposed technique predicts the transient stability index correctly, without any false alarm. In addition, the transient stability index as an output of the neural network helps to implement possible control actions. The results obtained demonstrate the potential for neural network to be a part of any on-line dynamic security assessment tool.     

Dynamic single machine equivalent techniques for on-line transient stability assessment

According to the post-fault trajectory duration characteristics, power system disturbances, which may cause transient stability problems, are classified into three types: short, long and extremely long duration ones. An improved method using dynamic single machine equivalent system (SMES) model for on-line first swing critical clearing time (CCT) estimation for both short and long duration disturbances on multi-machine power systems is developed in this paper. This dynamic SMES model substitutes for a large power system to provide fast, on-line transient stability assessment (TSA). Techniques such as assessment of energy margin, identification of a group of machines called the ‘dominant critical machines’ and an interpolation formula for CCT evaluation are proposed in this method to achieve high speed and accuracy in TSA. Test results on real size power systems are reported to show that the method is reliable for CCT assessment of both short and long post-fault duration disturbances.