Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Sensitivity analysis for transient stability studies

The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.

Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Transient stability indices from a hybrid approach

This paper deals with hybrid method for transient stability analysis combining time domain simulation and a direct method. Nowadays, the step-by-step simulation is the best available tool for allowing the uses of detailed models and for providing reliable results. The main limitation of this approach involves the large time of computational simulations and the absence of stability margin. On the other hand, direct methods, that demand less CPU time, did not show ample reliability and applicability yet. The best way seems to be using hybrid solutions, in which a direct method is incorporated in a time domain simulation tool. This work has studied a direct method using the transient potential and kinetic energy of the critical machine only. In this paper the critical machine is identified by a fast and efficient method, and the proposal is new for using to get stability margins from hybrid approaches. Results from systems, like 16-machine, show stability indices to dynamic security assessment. © 2001 IEEE.

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

A simulation tool for transient stability analysis on vector computers

This paper deals with transient stability analysis based on time domain simulation on vector processing. This approach requires the solution of a set of differential equations in conjunction of another set of algebraic equations. The solution of the algebraic equations has presented a scalar as sequential set of tasks, and the solution of these equations, on vector computers, has required much more investigations to speedup the simulations. Therefore, the main objective of this paper has been to present methods to solve the algebraic equations using vector processing. The results, using a GRAY computer, have shown that on-line transient stability assessment is feasible.

Modelling of induction motors for system faults and transient stability studies

The research carried out in this thesis was mainly concerned with the effects of large induction motors and their transient performance in power systems. Computer packages using the three phase co-ordinate frame of reference were developed to simulate the induction motor transient performance. A technique using matrix algebra was developed to allow extension of the three phase co-ordinate method to analyse asymmetrical and symmetrical faults on both sides of the three phase delta-star transformer which is usually required when connecting large induction motors to the supply system. System simulation, applying these two techniques, was used to study the transient stability of a power system. The response of a typical system, loaded with a group of large induction motors, two three-phase delta-star transformers, a synchronous generator and an infinite system was analysed. The computer software developed to study this system has the advantage that different types of fault at different locations can be studied by simple changes in input data. The research also involved investigating the possibility of using different integrating routines such as Runge-Kutta-Gill, RungeKutta-Fehlberg and the Predictor-Corrector methods. The investigation enables the reduction of computation time, which is necessary when solving the induction motor equations expressed in terms of the three phase variables. The outcome of this investigation was utilised in analysing an introductory model (containing only minimal control action) of an isolated system having a significant induction motor load compared to the size of the generator energising the system.

Stability analysis of power systems described with detailed models by automatic method

The power system stability analysis is approached taking into explicit account the dynamic performance of generators internal voltages and control devices. The proposed method is not a direct method in the usual sense since conclusion for stability or instability is not exclusively based on energy function considerations but it is automatic since the conclusion is achieved without an analyst intervention. The stability test accounts for the nonconservative nature of the system with control devices such as the automatic voltage regulator (AVR) and automatic generation control (AGC) in contrast with the well-known direct methods. An energy function is derived for the system with machines forth-order model, AVR and AGC and it is used to start the analysis procedure and to point out criticalities. The conclusive analysis itself is made by means of a method based on the definition of a region surrounding the equilibrium point where the system net torque is equilibrium restorative. This region is named positive synchronization region (PSR). Since the definition of the PSR boundaries have no dependence on modelling approximation, the PSR test conduces to reliable results. (C) 2008 Elsevier Ltd. All rights reserved.

A Model-Based Approach for Small-Signal Stability Assessment of Unbalanced Power Systems

In this paper, a modeling technique for small-signal stability assessment of unbalanced power systems is presented. Since power distribution systems are inherently unbalanced, due to its lines and loads characteristics, and the penetration of distributed generation into these systems is increasing nowadays, such a tool is needed in order to ensure a secure and reliable operation of these systems. The main contribution of this paper is the development of a phasor-based model for the study of dynamic phenomena in unbalanced power systems. Using an assumption on the net torque of the generator, it is possible to precisely define an equilibrium point for the phasor model of the system, thus enabling its linearization around this point, and, consequently, its eigenvalue/eigenvector analysis for small-signal stability assessment. The modeling technique presented here was compared to the dynamic behavior observed in ATP simulations and the results show that, for the generator and controller models used, the proposed modeling approach is adequate and yields reliable and precise results.

Analytical tools to assess the voltage stability of induction-based distributed generators

The installation of induction distributed generators should be preceded by a careful study in order to determine if the point of common coupling is suitable for transmission of the generated power, keeping acceptable power quality and system stability. In this sense, this paper presents a simple analytical formulation that allows a fast and comprehensive evaluation of the maximum power delivered by the induction generator, without losing voltage stability. Moreover, this formulation can be used to identify voltage stability issues that limit the generator output power. All the formulation is developed by using the equivalent circuit of squirrel-cage induction machine. Simulation results are used to validate the method, which enables the approach to be used as a guide to reduce the simulation efforts necessary to assess the maximum output power and voltage stability of induction generators. (C) 2011 Elsevier Ltd. All rights reserved.

Power system stability of a small sized isolated network supplied by a combined wind-pumped storage generation system: a case study in the Canary Islands

Massive integration of renewable energy sources in electrical power systems of remote islands is a subject of current interest. The increasing cost of fossil fuels, transport costs to isolated sites and environmental concerns constitute a serious drawback to the use of conventional fossil fuel plants. In a weak electrical grid, as it is typical on an island, if a large amount of conventional generation is substituted by renewable energy sources, power system safety and stability can be compromised, in the case of large grid disturbances. In this work, a model for transient stability analysis of an isolated electrical grid exclusively fed from a combination of renewable energy sources has been studied. This new generation model will be installed in El Hierro Island, in Spain. Additionally, an operation strategy to coordinate the generation units (wind, hydro) is also established. Attention is given to the assessment of inertial energy and reactive current to guarantee power system stability against large disturbances. The effectiveness of the proposed strategy is shown by means of simulation results.

Optimum switching point assessment of parallel braking resistor and serial current limiter for power system stability enhancement

A new control algorithm using parallel braking resistor (BR) and serial fault current limiter (FCL) for power system transient stability enhancement is presented in this paper. The proposed control algorithm can prevent transient instability during first swing by immediately taking away the transient energy gained in faulted period. It can also reduce generator oscillation time and efficiently make system back to the post-fault equilibrium. The algorithm is based on a new system energy function based method to choose optimal switching point. The parallel BR and serial FCL resistor can be switched at the calculated optimal point to get the best control result. This method allows optimum dissipation of the transient energy caused by disturbance so to make system back to equilibrium in minimum time. Case studies are given to verify the efficiency and effectiveness of this new control algorithm.

Mathematical methods in power system stability studies

In this thesis various mathematical methods of studying the transient and dynamic stabiIity of practical power systems are presented. Certain long established methods are reviewed and refinements of some proposed. New methods are presented which remove some of the difficulties encountered in applying the powerful stability theories based on the concepts of Liapunov. Chapter 1 is concerned with numerical solution of the transient stability problem. Following a review and comparison of synchronous machine models the superiority of a particular model from the point of view of combined computing time and accuracy is demonstrated. A digital computer program incorporating all the synchronous machine models discussed, and an induction machine model, is described and results of a practical multi-machine transient stability study are presented. Chapter 2 reviews certain concepts and theorems due to Liapunov. In Chapter 3 transient stability regions of single, two and multi~machine systems are investigated through the use of energy type Liapunov functions. The treatment removes several mathematical difficulties encountered in earlier applications of the method. In Chapter 4 a simple criterion for the steady state stability of a multi-machine system is developed and compared with established criteria and a state space approach. In Chapters 5, 6 and 7 dynamic stability and small signal dynamic response are studied through a state space representation of the system. In Chapter 5 the state space equations are derived for single machine systems. An example is provided in which the dynamic stability limit curves are plotted for various synchronous machine representations. In Chapter 6 the state space approach is extended to multi~machine systems. To draw conclusions concerning dynamic stability or dynamic response the system eigenvalues must be properly interpreted, and a discussion concerning correct interpretation is included. Chapter 7 presents a discussion of the optimisation of power system small sjgnal performance through the use of Liapunov functions.