A new emergency control method and a preventive mechanism against cascaded events to avoid large-scale blackouts

Cascaded events may cause a major blackout which will lead to a massive economic loss and even fatalities. Significant research efforts have been made to address the issue systematically: preventive mechanisms are designed to mitigate the impact of initiating events on power systems; emergency control methods are proposed to prevent power systems from entering an unstable state; restorative control methods are developed to stop the propagation of power system instability and to prevent widespread blackouts. This work contributes to the development of new emergency control methods and preventive mechanisms. First, a new emergency control scheme is proposed for preventing power systems from a loss of synchronism. Traditional out-of-step relays may fail to predict losses of synchronism as the dynamics of power systems become more and more complex. In recent years, the installation of the Phasor Measurement Units (PMUs) on power grids has increased significantly and, therefore, a large amount of real-time data is available for on-line monitoring of power system dynamics. This research proposes a PMU-based application for on-line monitoring of rotor angle stability. The Lyapunov Exponents are used to predict a loss of synchronism within large power systems. The relationship between rotor angle stability and the Maximal Lyapunov Exponent (MLE) is established. A computational algorithm is developed for the calculation of MLE in an operational environment. The effectiveness of the monitoring scheme is illustrated with a 3-machine system and a 200-bus system model. Then, a preventive mechanism against cyber attacks is developed. Cyber threats are serious concerns for power systems. For example, hackers may attack power control systems via the interconnected enterprise networks. This research proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The Duality Element Relative Fuzzy Evaluation Method (DERFEM) is employed to evaluate identified security vulnerabilities within cyber systems of power systems quantitatively; The Attack Graph is used to identify possible intrusion scenarios that exploit multiple vulnerabilities; an Intrusion Response system (IRS) is developed to monitor the impact of intrusion scenarios on power system dynamics in real time. IRS calculates the Conditional Lyapunov Exponents (CLEs) on line based on PMU data. Power system stability is predicted through values of CLEs. Control actions based on CLEs will be suggested if power system instability is likely to happen. A generic wind farm control system is used for case study. The effectiveness of IRS is illustrated with the IEEE 39 bus system model

In-situ health monitoring for wind turbine blade using acoustic wireless sensor networks at low sampling rates

PhD ThesisThe development of in-situ structural health monitoring (SHM) techniques represents a challenge for offshore wind turbines (OWTs) in order to reduce the cost of the operation and maintenance (O&M) of safety-critical components and systems. This thesis propos- es an in-situ wireless SHM system based on acoustic emission (AE) techniques. The proposed wireless system of AE sensor networks is not without its own challenges amongst which are requirements of high sampling rates, limitations in the communication bandwidth, memory space, and power resources. This work is part of the HEMOW- FP7 Project, ‘The Health Monitoring of Offshore Wind Farms’. The present study investigates solutions relevant to the abovementioned challenges. Two related topics have been considered: to implement a novel in-situ wireless SHM technique for wind turbine blades (WTBs); and to develop an appropriate signal pro- cessing algorithm to detect, localise, and classify different AE events. The major contri- butions of this study can be summarised as follows: 1) investigating the possibility of employing low sampling rates lower than the Nyquist rate in the data acquisition opera- tion and content-based feature (envelope and time-frequency data analysis) for data analysis; 2) proposing techniques to overcome drawbacks associated with lowering sampling rates, such as information loss and low spatial resolution; 3) showing that the time-frequency domain is an effective domain for analysing the aliased signals, and an envelope-based wavelet transform cross-correlation algorithm, developed in the course of this study, can enhance the estimation accuracy of wireless acoustic source localisa- tion; 4) investigating the implementation of a novel in-situ wireless SHM technique with field deployment on the WTB structure, and developing a constraint model and approaches for localisation of AE sources and environmental monitoring respectively. Finally, the system has been experimentally evaluated with the consideration of the lo- calisation and classification of different AE events as well as changes of environmental conditions. The study concludes that the in-situ wireless SHM platform developed in the course of this research represents a promising technique for reliable SHM for OWTBs in which solutions for major challenges, e.g., employing low sampling rates lower than the Nyquist rate in the acquisition operation and resource constraints of WSNs in terms of communication bandwidth and memory space are presente

A Literature Review on the Application of Acoustic Emission to Machine Condition Monitoring

Acoustic emission (AE) is a common physical phenomenon, in which the strain energy is released in the form of elastic wave when a material is deformed or cracked during the stress process. The condition monitoring based on AE is a relatively new method that aims to use noise/vibration anomalies to detect machine failures. However, some challenges lie ahead of its application. This thesis aims to analyze the literature in the field of AE applications to machine condition monitoring. The principles of AE technology, relevant instruments, machine monitoring and AE signal analysis, and practical examples of AE monitoring applications will be presented. More specifically, challenges, solutions and future direction in solving signal noise and attenuation challenges will be discussed. Through the example of rotating machinery, the characteristics of AE will be explained in detail. This thesis lays the foundation for the actual use of AE to monitor and analyze the state of machinery and provides guideline for future data collection and analysis of AE signals

IoT for measurements and measurements for IoT

The thesis is framed in the broad strand of the Internet of Things, providing two parallel paths. On one hand, it deals with the identification of operational scenarios in which the IoT paradigm could be innovative and preferable to pre-existing solutions, discussing in detail a couple of applications. On the other hand, the thesis presents methodologies to assess the performance of technologies and related enabling protocols for IoT systems, focusing mainly on metrics and parameters related to the functioning of the physical layer of the systems

Wireless Channel Path-Loss Modelling for Agricultural and Vegetation Environments: A Survey

This work undertakes an extensive survey of the channel modelling methods and path-loss characterization carried out in agricultural fields and vegetation environments in an attempt to study the state-of-the-art in this field, which, though vastly explored, still presents extremely diverse opportunities and challenges. The interface for communication between nodes in a typical agricultural field is the wireless channel or air interface, making it imperative to address the impairments that are exclusive to such a communication scenario by studying the characteristics of the medium. The performance of the channel is a direct indicator of the quality of communication. It is required to have a lucid understanding of the channel to ensure quality in transmission of the required information, while simultaneously ensuring maximum capacity by employing limited resources. The impairments that are the very nature of a typical wireless channel are treated in an explicit manner covering the theoretical and mathematical models, analytical aspects and empirical models. Although there are several propagation models characterized for generic indoor and outdoor environments, these cannot be applied to agricultural, vegetation, forest and foliage scenarios due to the various additional factors that are specific to these environments. Owing to the wide variety, size, properties and span of the foliage, it also becomes extremely challenging to develop a generic predictive model for all kinds of crops or vegetation. The survey is categorized into fields containing specific crops, greenhouse environment and forest/foliage scenarios and the key findings are presented

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Current Advances in Internet of Underground Things

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

A Measurement-based Multipath Channel Model for Signal Propagation in Presence of Wind Farms in the UHF Band

[EN] Scattering signals on wind turbines may lead to degradation problems on the communication systems provided in the UHF band, such as terrestrial television broadcasting, broadband wireless systems or public safety services. To date, despite the continuous requests from the International Telecommunication Union for studies on this field, no channel model has been developed to characterize signal propagation under these particular conditions. In response to this necessity, this paper presents a complete Tapped Delay Line (TDL) channel model to characterize multipath propagation in presence of a wind farm, including novel scattering modeling and Doppler spectra characterization. As proved later, this channel model, which is based on both theoretical development and empirical data obtained in the surroundings of a real wind farm, is adaptable to the particular features of any case under study: wind turbine dimensions, working frequency, and relative location of the wind farm, transmitter and receivers.This work was supported in part by the European Union FP7 (grant agreement n 296164), by the Spanish Ministry of Economy and Competitiveness (project TEC2012-32370), and by the Basque Government (SAIOTEK program)