Wide area controls for transient and dynamic stability enhancement

This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

Mode matching pursuit for estimating dominant modes in bulk power grid

This study presents a general approach to identify dominant oscillation modes in bulk power system by using wide-area measurement system. To automatically identify the dominant modes without artificial participation, spectral characteristic of power system oscillation mode is applied to distinguish electromechanical oscillation modes which are calculated by stochastic subspace method, and a proposed mode matching pursuit is adopted to discriminate the dominant modes from the trivial modes, then stepwise-refinement scheme is developed to remove outliers of the dominant modes and the highly accurate dominant modes of identification are obtained. The method is implemented on the dominant modes of China Southern Power Grid which is one of the largest AC/DC paralleling grids in the world. Simulation data and field-measurement data are used to demonstrate high accuracy and better robustness of the dominant modes identification approach.

Design of a nonlinear excitation controller using inverse filtering for transient stability enhancement

This paper proposes a nonlinear excitation controller to improve transient stability, oscillation damping and voltage regulation of the power system. The energy function of the predicted system states is used to obtain the desired flux for the next time step, which in turn is used to obtain a supplementary control input using an inverse filtering method. The inverse filtering technique enables the system to provide an additional input for the excitation system, which forces the system to track the desired flux. Synchronous generator flux saturation model is used in this paper. A single machine infinite bus (SMIB) test system is used to demonstrate the efficacy of the proposed control method using time-domain simulations. The robustness of the controller is assessed under different operating conditions.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

Battery energy storage systems to improve power system frequency response

Battery energy storage systems (BESS) are becoming feasible to provide system frequency support due to recent developments in technologies and plummeting cost. Adequate response of these devices becomes critical as the penetration of the renewable energy sources increases in the power system. This paper proposes effective use of BESS to improve system frequency performance. The optimal capacity and the operation scheme of BESS for frequency regulation are obtained using two staged optimization process. Furthermore, the effectiveness of BESS for improving the system frequency response is verified using dynamic simulations.

A Fixed Order Model Matching Approach for the Design of Robust Power System Oscillation Damper

This book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems.

Eigenvalue Analysis of a DFIG Based Wind Power System under Different Modes of Operations

This chapter discussed the various modes of operation of the Doubly Fed Induction Generator (DFIG) based wind farm system. The impact of a auxiliary damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using Bacteria Foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system under Super/Sub-synchronous speed of operation. The robustness issue of the damping controller is also investigated.

Sectionalizing strategies for minimizing outage durations of critical loads in parallel power system restoration with bi-level programming

Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Application of inverse filtering technique in power system studies

This paper demonstrates the application of inverse filtering technique for power systems. In order to implement this method, the control objective should be based on a system variable that needs to be set on a specific value for each sampling time. A control input is calculated to generate the desired output of the plant and the relationship between the two is used design an auto-regressive model. The auto-regressive model is converted to a moving average model to calculate the control input based on the future values of the desired output. Therefore, required future values to construct the output are predicted to generate the appropriate control input for the next sampling time.

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.

Optimisation techniques for planning automatic under frequency load shedding in New Zealand’s power system

Electricity generation is vital in developed countries to power the many mechanical and electrical devices that people require. Unfortunately electricity generation is costly. Though electricity can be generated it cannot be stored efficiently. Electricity generation is also difficult to manage because exact demand is unknown from one instant to the next. A number of services are required to manage fluctuations in electricity demand, and to protect the system when frequency falls too low. A current approach is called automatic under frequency load shedding (AUFLS). This article proposes new methods for optimising AUFLS in New Zealand’s power system. The core ideas were developed during the 2015 Maths and Industry Study Group (MISG) in Brisbane, Australia. The problem has been motivated by Transpower Limited, a company that manages New Zealand’s power system and transports bulk electricity from where it is generated to where it is needed. The approaches developed in this article can be used in electrical power systems anywhere in the world.