Power System Disturbances Research Articles

Modeling Protection Systems in Time-Domain Simulations: A New Method to Detect Mis-Operating Relays for Unstable Power Swings

Large power system disturbances can cause stable or unstable power swings. Unstable power swings result in generator pole slipping. A generator or group of generators may accelerate or decelerate, leading to voltage depression at the electrical center along with generator tripping. This voltage depression may cause protective relay mis-operation and unintentional separation of the system. In order to avoid unintentional islanding, the potentially mis-operating relays should be blocked from tripping. This paper proposes a novel method to determine the location of the mis-operating relays at the planning phase. Blocking these mis-operating relays, combined with an appropriate islanding scheme, help avoid a system-wide collapse. The proposed method is tested on data from the Western Electricity Coordinating Council. A triple line outage of the California-Oregon Intertie is studied. The electrical center is determined and appropriate out-of-step blocking schemes are identified. The results show that the correct design of out-of-step protective relays improves the dynamic performance of the power system and causes less fluctuations in voltage and frequency throughout the system.

Disturbance location determination based on electromechanical wave propagation in FNET/GridEye: a distribution‐level wide‐area measurement system

This study presents a method to locate power system disturbances using wide-area synchropahsor measurements. The merits of the proposed method include robustness and ease of visualisation. In addition, the proposed method facilitates the calculation of electromechanical wave propagation speed distribution. Examples of locating the disturbance and generating the propagation speed distribution are demonstrated using the FNET/GridEye system, a distribution-level wide-area measurement system. Without losing generality, the proposed method can be implemented in any other wide-area measurement system.

Ferroresonance Signal Analysis with Wavelet Transform on 500 kV Transmission Lines Capacitive Voltage Transformers

This paper deals with ferroresonance detection on an transmission line utilizing wavelet transform. The ferroresonance involving linear capacitor and non-linear inductor was triggered by the disturbances of power system, such as lightning strike, switching operation and ground fault. The primary voltage of capacitive voltage divider (CVT) was observed as response of the triggered ferroresonance. The voltage signal was processed using wavelet daubechies (db5) until 9 levels. The cyclic cumulative energy for each condition was then calculated and compared. The result shows that the cyclic cumulative energy ratio and duration of period of cumulative energy deviation can be used as ferroresonance detection parameters.

Analytical Methods for Characterizing Frequency Dynamics in Islanded Microgrids With Gensets and Energy Storage

Microgrids with increased penetration of renewables experience serious challenges due to large frequency excursions under power system disturbances. An energy storage system can provide frequency regulation, but the effectiveness depends on whether it is configured for the grid-forming or grid-following mode of operation. For this purpose, two critical parameters are studied for frequency regulation in distribution systems; first, the initial rate-of-change-of-frequency (ROCOF), and second, the minimum value of frequency, also known as frequency nadir, following a load change. The aim of this paper is to identify analytical methods for accurately calculating the frequency parameters like ROCOF and frequency nadir. Reduced-order models are developed to determine the frequency deviation against power system disturbances. The results are verified against simulation models validated by testing at the Consortium for Electric Reliability Technology Solutions Microgrid test bed.

Optimal design of fuzzy-AGC based on PSO & RCGA to improve dynamic stability of interconnected multi area power systems

Quickly getting back the synchronism of a disturbed interconnected multi area power system due to variations in loading condition is recognized as prominent issue related to automatic generation control (AGC). In this regard, AGC system based on fuzzy logic, i.e., so-called FLAGC can introduce an effectual performance to suppress the dynamic oscillations of tie-line power exchanges and frequency in multi-area interconnected power system. Apart from that, simultaneous coordination scheme based on particle swarm optimization (PSO) along with real coded genetic algorithm (RCGA) is suggested to coordinate FLAGCs of the all areas. To clarify the high efficiency of aforementioned strategy, two different interconnected multi area power systems, i.e., three-area hydro-thermal power system and five-area thermal power system have been taken into account for relevant studies. The potency of this strategy has been thoroughly dealt with by considering the step load perturbation (SLP) in both the under study power systems. To sum up, the simulation results have plainly revealed dynamic performance of FLAGC as compared with conventional AGC (CAGC) in each power system in order to damp out the power system oscillations.

Fast and secure detection technique for loss of field occurrence in synchronous generators

Loss of field (LOF) phenomenon in synchronous generators may cause serious damages and voltage drop in the power system, which can result in a blackout. Conventional methods, which detect LOF on the basis of the measured impedance from terminal viewpoint, are slow and may exhibit mal-operation in the face of other phenomena, e.g. stable power swing (SPS). In this paper, a novel technique is proposed to detect LOF in synchronous generators on the basis of some electrical quantities variations including voltage of terminal (V), current (I), active power (P), reactive power (Q) and power angle (δ). To evaluate the performance of the proposed algorithm, some cases are simulated under various operation conditions. Obtained results show that this algorithm on the basis of V, Q and δ not only can be considered as a fast LOF detector in comparison with the conventional impedance-based schemes, but also it is a robust and secure technique in the face of SPS and other power system disturbances. The proposed algorithm is tested by using an experimental setup including the laboratory synchronous generators, too. The obtained results show that the proposed technique can exhibit suitable performance in the actual conditions.

AGC performance enrichment of multi-source hydrothermal gas power systems using new optimized FOFPID controller and redox flow batteries

Redox flow batteries (RFB) showcase extremely long charge-discharge life cycle and outstanding quick response to alleviate the oscillations under sudden disturbances in power system. The assimilation of energy storage units in power system can curtail the oscillations energetically by contributing fast active power compensation. Hence, in this paper, RFB are tried to integrate into multi-source power systems and their efficacy in boosting automatic generation control (AGC) performance is executed. A new fractional order fuzzy PID (FOFPID) controller is employed to enhance the system performance. FOFPID controller parameters are optimized maidenly by utilizing imperialist competitive algorithm (ICA). The controller is designed and implemented on more realistic single/two-area multi-source hydrothermal gas system with/without RFB. The potency of FOFPID is established by contrasting its responses with optimal and lately developed hSFS-PS, DE, TLBO and IPSO optimized controllers. To check the efficacy of the approach, the study is further conducted under the presence of important non-linearites like GDB and GRC. Analysis of results reveals that the advocated approach with/without RFB improves the system performance significantly in comparison to the prevalent methods. The robustness of the method is demonstrated against wide variations in system parameters under the presence/absence of RFB/GDB-GRC and at higher and variable step load demands.

A Numerical Approach for Hybrid Simulation of Power System Dynamics Considering Extreme Icing Events

The global climate change leads to more extreme meteorological conditions such as icing weather, which have caused great losses to power systems. Comprehensive simulation tools are required to enhance the capability of power system risk assessment under extreme weather conditions. A hybrid numerical simulation scheme integrating icing weather events with power system dynamics is proposed to extend power system numerical simulation. A technique is developed to efficiently simulate the interaction of slow dynamics of weather events and fast dynamics of power systems. An extended package for PSS/E enabling hybrid simulation of icing event and power system disturbance is developed, based on which a hybrid simulation platform is established. Numerical studies show that the functionality of power system simulation is greatly extended by taking into account the icing weather events.

Study of the Different Transmission Line Faults for a Grid Connected Wind Farm with Different Types of Control Method for RSC

<p>Wind power stations, many located in remote areas; so they are characterized by weak grids and are often submitted to power system disturbance like faults. In this paper, the behaviour of a wind energy conversion system that uses the control of the rotor side converter (RSC) by three different methods under faulty conditions is presented. The behaviour of these systems during a grid failure is an important issue. DFIG is analysed and simulated under differing faulty conditions in the environment of MATLAB/SIMULINK. Simulation results show that the proposed method has proper operation during fault conditions.</p><p> </p>

Detection, Classification and Location of Overhead Line Faults using Wavelet Transform

Objectives: To develop a wavelet Transform method to identify and categorize transmission line faults and also determines the location of the fault. Method: A Simulink model is developed for the test system. Various faults at different locations are simulated. DWT coefficients of the current signals are obtained. Fault index is calculated and is used to identify and categorize the fault. Findings: The method proposed using wavelet transform in the present work will accurately discriminate between normal and fault condition, identify the type of fault and determine its location. The method proposed is relatively very simple and can be easily realized and practically implemented. Application/Improvements: Transmission line protection relay should be highly reliable, selective and act quickly so that minimum damage is caused, area affected by power interruption is less and stability of the system is not lost. Hence, efficient fault detection methods are necessary to help operators to take required measures during power system disturbances. This will ensure the secure and stable operation of the power system.

Enhancement of Transient Stability of the Nigeria 330 kV Transmission Network Using Fault Current Limiter

The dynamic responses of generators when subjected to disturbances in an interconnected power system have become a major challenge to power utility companies due to increasing stress on the power network. Since the occurrence of a disturbance or fault cannot be completely avoided, hence, when it occurs, control measures need to be put in place to limit the fault current, which invariably limit the level of the disturbances. This paper explores the use of Superconductor Fault Current Limiter (SFCL) to improve the transient stability of the Nigeria 330 kV Transmission Network. During a large disturbance, the rotor angle of the generator is enhanced by connecting a Fault Current Limiter (FCL) which reduces the fault current and hence, increases transient stability of the power network. In this study, the most affected generator was taken into consideration in locating the SFCL. The result obtained reveals that the Swing Curve of the generator without FCL increases monotonically which indicates instability, while the Swing Curve of the System with FCL reaches steady state.

Detection and evaluation of effective factors on flicker phenomenon in diesel-engine driven generators

Diesel-Engine Driven Generators (DDGs) are a kind of distributed generation (DG) units and similar to other DGs, cause power quality disturbances in power system. Flicker is one of the most important power quality disturbances having bad effects on the sensitive loads. In DDGs, Inherent Torque Fluctuations (ITFs), Misfiring (MF) in various cylinders, Gearbox Tooth Crashing (GTC), governor and exciter errors in presence of the mentioned factors are some of the faults, which produce flicker. Therefore, it is necessary to recognize any faults causing flicker to prevent serious problem in DDGs. Also, identifying these factors is effective in accelerating process of repair and maintenance for DDGs. Therefore, in this paper firstly, all faults that cause flicker are modeled and simulated, then a pattern recognition method is presented for their detection. In the proposed method, Discrete Wavelet Transform (DWT) and Discrete S-Transform (DST) are used for feature extraction and Gram-Schmidt (GS) is used for feature selection. Afterwards, a classifier based on K-Nearest Neighbors (KNN) is used to detect the faults. Also, the impact of faults on flicker severity has been evaluated by short-term severity of flicker (Pst index).

A semi-distributed energy-based framework for the analysis and visualization of power system disturbances

In this paper, a semi-distributed tool for monitoring and analysis of power systems disturbances using wide-area sensors is proposed. The proposed framework can be used to integrate and process large amounts of multimodal, multi-type observational data from various monitoring technologies or data concentrators to assess the power system health in near-real time.First, a framework for fusing data from multiple sensors based on multivariate statistical tools is introduced and a model of the collected data is developed. Drawing on this model, a novel a data-driven strategy based on both, local and global energy metrics for the analysis of major system disturbances is proposed. The approach is tested using time domain simulations on the IEEE 118 bus system under various scenarios and different levels of observability of the system. The approach is complemented with a visualization technique to provide further means to analyze the system after a disturbance.

Fuzzy Logic Based Fine-tuning Approach for Robust Load Frequency Control in a Multi-area Power System

This article addresses the design procedure and numerical validation of a robust fuzzy logic-based fine-tuning approach devised to enhance load frequency control capabilities in multi-area power systems. The founded robust fuzzy logic-based fine-tuning approach is intended for judicial parameter tuning of a proportional-integral controller encountering fault occurrences or severe changes in system loading conditions. Unlike conventional proportional-integral controllers that are generally designed for fixed operating conditions, the outlined approach demonstrates robust performance with power system uncertainties and disturbances. In this context, the projected robustness is principally emanated due to a fuzzy logic extensibility feature, furnishing the established framework to have a proliferated observability on control space. The design procedure of a robust fuzzy logic-based fine-tuning controller is substantially nourished by expert knowledge regarding the overall system performance. Apt fuzzified and defuzzified rule-based mechanisms are wisely included as the key building blocks of the fuzzy inference engine. Extensive numerical studies are launched in a thorough investigation of the proposed approach. As well, the robust fuzzy logic-based fine-tuning performance is compared with that of two extra robust methods, namely the H∞-iterative linear matrix inequality as well as the hybrid genetic algorithm and linear matrix inequality. The obtained results are deeply analyzed.

Detection and Classification of Power Quality Disturbances Using Double Resolution S-Transform and DAG-SVMs

The accurate detection and classification of power quality (PQ) disturbances in power systems is a key step to determine the causes of these events before any proper countermeasure could be taken. This paper presents a new algorithm for detection and classification of PQ disturbances based on the combination of double-resolution S-transform (DRST) and directed acyclic graph support vector machines (DAG-SVMs). The proposed method first employs DRST for an effective feature extraction from power signals. Then, the DAG-SVMs are used to predict the classes of PQ disturbances. The DRST not only has better time–frequency localization and stronger robustness but also reduces the computational complexity without losing the useful information of the original signal in comparison with the traditional S-transform. Through the combined use of DRST and DAG-SVMs, the algorithm can be easily implemented in embedded real-time applications. Finally, the implementation of the proposed algorithm in a digital signal processor + advanced reduced instruction set computing machine-based hardware test platform is introduced. The effectiveness of the proposed method is demonstrated by means of computer simulations and practical experiments with single and combined PQ disturbances.

A Wavelet Based Tool to Assist the Automated Analysis of Waveform Disturbances Records in Power Generators

This paper presents an automated disturbance analysis scheme for electrical power generating units. It proposes a method based on wavelet transform applied to transient (waveform) records of disturbances. The objectives are to detect faults in generators, perform a segmentation of the records and extract information that characterize the faults. The output of the method is a set of representative information of the monitored signals, which can be used in a classification system for automated fault diagnosis. The large volume of data produced by the digital recorders of power system disturbances justifies the search for automated analysis methods that can be employed to assist the utilities engineers. Tests were conducted to determine the best mother wavelet in the segmentation process. The proposed method was applied to five case studies with real disturbance data and the obtained results confirmed its efficiency.

Investigation of Boost Converter to Track Maximum Power Point for the Doubly Fed Induction Generators in the Wind Farm

Background/Objectives: In this paper, tracking the Maximum Power Point for the Doubly Fed Induction Generators in the Wind Farm through a boost converter is analyzed. Methods/Statistical Analysis: Achieving maximum power at wind farm and subsequently improving power quality disturbances in power systems is very important. Methods used to track the maximum power point are: 1-TSR control 2-P&O control 3-ORB control This paper, presents a combination of P&O and ORB control method to extract maximum power at Doubly Fed Induction Generators (DFIG). Findings: In this method, there is no need to anemometer and the recent information of wind speed. In addition, the little Fluctuations near the maximum power point, is an improved factor in this technique. Simulation results using Matlab software, proves the truth of this claim.

Investigating the impacts of the SVCs and the SCs affecting to the transient stability in multi-machine power system

A new algorithm simulating the impacts of the VAR supporting devices such as the static var compensators (SVCs) and the synchronous condensers (SCs) under condition of symmetrical disturbances in multi-machine power system is mentioned. Some typical numerical examples are presented in this article.
 The comparisons of variation of the state parameters, such as the voltage, frequency, reactive power outputs and asynchronous torques…are simulated under condition of the action of the automatic voltage regulation systems of generators and of the VAR supporting devices.
 The transient energy margins are calculated and compared to assess the transient stability in multi-machine power system. Basing on this algorithm, the PC program uses the elements of the eigen-image matrix to bring the specific advantages for the simulation of the transient features of state variables.

A Distributed Multi-Agent Based Emergency Control Approach Following Catastrophic Disturbances in Interconnected Power Systems

This paper presents a decentralized emergency control approach for preventing voltage instability by controlling the reactive power and voltage of the system. The proposed control algorithm is based on a distributed architecture of intelligent agents to identify the affected region and to activate timely countermeasures to achieve a fast and accurate response. By dividing the network into several areas, the voltage instability problem can be localized and countermeasures can be directed to the most affected area by the authorized local agent. This facilitates quick decision making within the system. To achieve effective voltage and reactive power support, a sensitivity based zone formation is proposed. The Nordic32 74-bus test system has been used for testing the proposed multi-agent emergency control (MAEC). The results from the case studies demonstrate the effectiveness of the proposed MAEC approach.

Robust nonlinear adaptive backstepping excitation controller design for rejecting external disturbances in multimachine power systems

This paper proposes a new approach to design a robust adaptive backstepping excitation controller for multimachine power systems in order to reject external disturbances. The parameters which significantly affect the stability of power systems (also called stability sensitive parameters) are considered as unknown and the external disturbances are incorporated into the power system model. The proposed excitation controller is designed in such a way that it is adaptive to the unknown parameters and robust to external disturbances. The stability sensitive parameters are estimated through the adaptation laws and the convergences of these adaptation laws are obtained through the negative semi-definiteness of control Lyapunov functions (CLFs). The proposed controller not only provides robustness property against external disturbances but also overcomes the over-parameterization problem of stability sensitive parameters which usually appears in some conventional adaptive methods. Finally, the performance of the proposed controller is tested on a two-area four machine 11-bus power system by considering external disturbances under different scenarios and is compared to that of an existing nonlinear adaptive backstepping controller. Simulation results illustrate the robustness of the proposed controller over an existing one in terms of rejecting external disturbances.