Fault-tolerant wide-area control of power systems

In this thesis, the stability and performance of closed-loop systems following the loss of sensors or feedback signals (sensor faults) are studied. The objective is to guarantee stability in the face of sensor faults while optimising performance under nominal (no sensor fault) condition. One of the main contributions of this work is to deal effectively with the combinatorial binary nature of the problem when the number of sensors is large. Several fault-tolerant controller and observer architectures that are suitable for different applications are proposed and their effectiveness demonstrated. The problems are formulated in terms of the existence of feasible solutions to linear matrix inequalities. The formulations presented in this work are described in a general form and can be applied to a large class of systems. In particular, the use of fault-tolerant architectures for damping inter-area oscillations in power systems using wide-area signals has been demonstrated. As an extension of the proposed formulations, regional pole placement to enhance the damping of inter-area modes has been incorporated. The objective is to achieve specified damping ratios for the inter-area modes and maximise the closed-loop performance under nominal condition while guaranteeing stability for all possible combinations of sensors faults. The performances of the proposed fault-tolerant architectures are validated through extensive nonlinear simulations using a simplified equivalent model of the Nordic power system.Open Acces

Centralized wide area damping controller for power system oscillation problems

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, three different centralized control designs that vary on complexity are presented to damp inter-area oscillations in large power systems. All the controls are based on phasor measurements. The first two proposed architectures use simple proportional gains that consider availability of measurements from different areas of the system and fulfill different optimization functions. The third controller is based on a more sophisticated Linear Quadratic Gaussian approach which requires access to the state space model of the system under investigation. The novelty of the proposed scheme resides in designing a single control to command the most influence group of machines in the system. To illustrate the effectiveness of the proposed algorithms, simulations results in the IEEE New England model are presented

Detection of frequency deviations for monitoring of power systems

​© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this work an algorithm for identification of power system frequency deviation is presented. The proposed approach can be used to monitor frequency measurements from syncrophasor measurement units (PMU) and to store data only for important events and save storage in the local server. The detection algorithm use a sliding window that rise a flag if the measured frequency deviates from a predefined set point. If the alarm flag is constant over several sliding windows, an event is captured and locally stored for further analysis. To demonstrate the effectiveness of the proposed approach, real PMU measurements from the Swiss power system are used as input

Online coherency identification and stability condition for large interconnected power systems using an unsupervised data mining technique

Identification of coherent generators and the determination of the stability system condition in large interconnected power system is one of the key steps to carry out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends, the larger amount data available and the non-linear dynamic behaviour of the frequency measurements often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. This paper presents a novel online unsupervised data mining technique to identify coherent groups, to detect the power system disturbance event and determine status stability condition of the system. The innovative part of the proposed approach resides on combining traditional plain algorithms such as singular value decomposition (SVD) and K -means for clustering together with new concept based on clustering slopes. The proposed combination provides an added value to other applications relying on similar algorithms available in the literature. To validate the effectiveness of the proposed method, two case studies are presented, where data is extracted from the large and comprehensive initial dynamic model of ENTSO-E and the results compared to other alternative methods available in the literature

A Criterion for Designing Emergency Control Schemes to Counteract Communication Failures in Wide-Area Damping Control

© The Authors 2023. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/Communication failures and transmission delays are two major issues associated with Wide-Area Damping Controllers (WADCs). While transmission delays have been extensively studied and various solutions have been proposed, little research has been done on communication failures and most of the proposed methods are based on preventive controls. However, in today’s liberalized electricity markets, preventive controls are no longer acceptable and the trend is to use emergency controls instead. This paper proposes a novel emergency control scheme to counteract the loss of remote signals related to the input and to the output of the WADC (i.e. sensor and actuator failures). The proposed scheme is based on a simple criterion, which overcomes the complexity of the previous methods. Modal analysis and time domain simulations are performed to verify the performance of the proposed method. The simulation results show that the proposed method performs well in handling communication failures and can maintain good damping performance. This research work is particularly important in view of the trend towards the wide-scale adoption of wide-area measurement technologies, while the vulnerability to cyber-attacks is increasing.Peer reviewe

Optimization free of algorithm-specific control parameters for power system stabilizer tuning

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A settings-free and derivative-free optimization technique, called Jaya Optimization Algorithm, is investigated in this paper for the design of simple fuzzy PSSs (FPSSs) in a multimachine power system. Performance of this technique during the optimization process is compared to the one exhibited by a Bat Optimization Algorithm based approach. Considering a set of test cases for illustrative purposes, FPSSs tuned with both of these algorithms are applied to the study system and their performance in damping inter-area and local oscillations is analyzed against some commonly used lead-lag structures, including multi-band PSSs

Power system inertia estimation using a residual neural network based approach

The increasing penetration of non-synchronous generation into power grids is reducing the equivalent system inertia and leading to different frequency regulation and control challenges. Consequently, the monitoring and quantification of this inertia to implement actions that can keep it above critical levels have become a key issue for the stability of power systems. In this regard, a residual neural network (ResNet) based alternative is proposed and investigated in this paper to estimate the equivalent inertia of a sample system when synchronous generating units are displaced by converter-interfaced generators. The proposed ResNet model is trained according to the frequency of the center of inertia and the corresponding computed rates of change of frequency for a predefined time interval, where sudden generation outages and load step changes are considered under variations of total load demand and equivalent inertia reductions. The accuracy of the proposed approach is compared against the one achieved with the application of two traditional machine learning techniques, such as Support Vector Machine and Random Forest

Convolutional neural nets with hyperparameter optimization and feature importance for power system static security assessment

Static security assessment (SSA) is fundamental in electrical network analysis. However, the growing complexity and variability of grid’s operating conditions can make it tedious, slow, computationally intensive, and limited or impractical for on-line applications when traditional approaches are considered. Since this may hinder the emerging analytical duties of system operators, data-driven alternatives are required for faster and sophisticated decision-making. Although different machine learning algorithms (MLAs) could be applied, Convolutional Neural Networks (CNNs) are one of the most powerful models used in many advanced technological developments due to their remarkable capability to identify meaningful patterns in challenging and complex data sets. According to this, a CNN based approach for fast SSA of power systems with N-1 contingency is presented in this paper. To contribute to the automation of model building and tuning, a settings-free strategy to optimize a set of hyperparameters is adopted. Besides, permutation feature importance is considered to identify only a subset of key features and reduce the initial input space. To illustrate the application of the proposed approach, the simulation model of a practical grid in Mexico is used. The superior performance of the CNN alternative is demonstrated by comparing it with two popular MLAs

Stability effects after massive integration of renewable energy sources on extra-large power systems

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this work, a security metric to quantify the stability effects after integration of different levels of renewable energy sources (RES) in extra-large power systems is presented. The comparison is carried out through extensive number of Root Mean Square (RMS) simulations, using as a test system the initial dynamic model of continental Europe under different scenarios representing the implementation of combined energy strategies across Europe. The RMS simulations were performed using the commercial power system software DIgSILENT PowerFactory. The stability effects in the entire system are analysed, as result of massive integration of RES in 13 of the most significant countries e.g. those who have been modelled in more detail. The result of three study cases are presented, corresponding to the increase of different levels of renewable penetration: 10%, 20% and 30%, respectively. The results are compared in terms of the frequency response but also on the evolution of the proposed stability metric. The results suggest that countries located in the Eastern part of Europe are more sensitive to massive integration of RES than the rest of the network, from a gobal stability perspective

Analysis of grid events influenced by different levels of renewable integration on extra-large power systems

In this work, the impact of implementing a large amount of decentralized renewable energysources (RES) of different scales on an extra-large power grid is investigated. Three scenariosare created, substituting 10%, 20%, and 30% of the conventional energy production by RES.For this purpose, the initial dynamic model of Continental Europe in combination with theindustrial power system application DIgSILENT PowerFactory was used. In order to comparethe behavior of different applied scenarios, a performance index was developed to evaluate andrank the effects of network disturbances by means of time-domain simulations. The performanceindex was designed based on three different criteria that analyze the oscillatory content andthus, the severity of a given event. The initial power flow of the dynamic model was identifiedas a limiting factor for the integration of RES, therefore two additional power flows weredeveloped following an innovative procedure. Through the methodologies mentioned above, itwas found that Turkey is the most sensitive to such changes, which are amplified by increasingimplementation of RES and often lead to inter-area oscillation