Tripping Control for Transient Stability in Coordinated Hydro and Wind Generation

Over-frequency generator tripping (OFGT) is used to cut off extra generation to balance power and loads in an isolated system. In this paper the impact of OGFT as a consequence of grid-connected wind farms and under-frequency load shedding (UFLS) is analysed. The paper uses a power system model to demonstrate that wind power fluctuations can readily render OFGT and UFLS maloperation. Using combined hydro and wind generation, the paper proposes a coordinated strategy which resolves problems associated with OFGT and UFLS and preserves system stability.

Active use of DFIG based Wind Farms for Transient Stability Improvement during Grid Disturbances

The doubly-fed induction generator (DFIG) now represents the dominant technology in wind turbine design. One consequence of this is limited damping and inertial response during transient grid disturbances. A dasiadecoupledpsila strategy is therefore proposed to operate the DFIG grid-side converter (GSC) as a static synchronous compensator (STATCOM) during a fault, supporting the local voltage, while the DFIG operates as a fixed-speed induction generator (FSIG) providing an inertial response. The modeling aspects of the decoupled control strategy, the selection of protection control settings, the significance of the fault location and operation at sub- and super-synchronous speeds are analyzed in detail. In addition, a case study is developed to validate the proposed strategy under different wind penetrations levels. The simulations show that suitable configuration of the decoupled strategy can be deployed to improve system voltage stability and inertial response for a range of scenarios, especially at high wind penetration. The conclusions are placed in context of the practical limitations of the technology employed and the system conditions.

Impact of Wind Generation Mix on Transient Stability for an Interconnected Power System

The rapid growth of wind generation in many European countries is pushing power systems into
uncharted territory. As additional wind generators are installed, the changing generation mix may
impact on power system stability. This paper adopts the New England 39 bus system as a test
system for transient stability analysis. Thermal generator models are based on a likely future plant
mix for existing systems, while varying capacities of fixed-speed induction generators (FSIG) and
doubly-fed induction generators (DFIG) are considered. The main emphasis here has been placed
on the impact of wind technology mix on inter-area oscillations following transient grid
disturbances. In addition, both rotor angle stability and transient voltage stability are examined, and
results are compared with current grid code requirements and standards. Results have shown that
FSIGs can reduce tie-line oscillations and improve damping following a transient disturbance, but
they also cause voltage stability and rotor angle stability problems at high wind penetrations. In
contrast, DFIGs can improve both voltage and rotor angle stability, but their power output
noticeably oscillates during disturbances.

Transient Stability Analysis of a Power System with High Wind Penetration

This paper presents transient stability analysis for a power system with high wind penetration. The transient stability has been evaluated based on two stability criteria: rotor angle stability and voltage stability. A modified IEEE-14 bus system has been used as the main study network and simulations have been conducted at several wind power penetration levels, defined as a fraction of total system generation. A wide range of scenarios have been presented based on the wind farm voltage at the point of connection, i.e. low voltage (LV) distribution level and high voltage (HV) transmission level, and the type of wind generator technology, i.e. fixed speed induction generator (FSIG) and doubly-fed induction generator (DFIG).

An efficient and robust case sorting for algorithm for transient stability assessment

An efficient and robust case sorting algorithm based on Extended Equal Area Criterion (EEAC) is proposed in this paper for power system transient stability assessment (TSA). The time-varying degree of an equivalent image system can be deduced by comparing the analysis results of Static EEAC (SEEAC) and Dynamic EEAC (DEEAC), the former of which neglects all time-varying factors while the latter partially considers the time-varying factors. Case sorting rules according to their transient stability severity are set combining the time-varying degree and fault messages. Then a case sorting algorithm is designed with the “OR” logic among multiple rules, based on which each case can be identified into one of the following five categories, namely stable, suspected stable, marginal, suspected unstable and unstable. The performance of this algorithm is verified by studying 1652 contingency cases from 9 real Chinese provincial power systems under various operating conditions. It is shown that desirable classification accuracy can be achieved for all the contingency cases at the cost of very little extra computational burden and only 9.81% of the whole cases need to carry out further detailed calculation in rigorous on-line TSA conditions.

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.

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.

Efficient probabilistic contingency analysis through a stability measure considering wind perturbation

The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.

Direct stability evaluation of power systems with detailed generator models using structure-preserving energy functions

Energy-based direct methods for transient stability analysis are potentially useful both as offline tools for planning purposes as well as for online security assessment. In this paper, a novel structure-preserving energy function (SPEF) is developed using the philosophy of structure-preserving model for the system and detailed generator model including flux decay, transient saliency, automatic voltage regulator (AVR), exciter and damper winding. A simpler and yet general expression for the SPEF is also derived which can simplify the computation of the energy function. The system equations and the energy function are derived using the centre-of-inertia (COI) formulation and the system loads are modelled as arbitrary functions of the respective bus voltages. Application of the proposed SPEF to transient stability evaluation of power systems is illustrated with numerical examples.