Integrating Low Voltage Distribution Systems to Distribution Automation

The aim of this thesis is to define and study the key elements and the main characteris-tics of the integration of the low voltage (LV) distribution systems to distribution auto-mation (DA). The key elements are defined by studying the development of essential systems in LV distribution networks as well as by studying the development of the net-works by way of evolution phases. The key elements and the main characteristics of the integration to DA are illustrated by a certain model of a LV distribution network under its development. For a start DA is reviewed by generally used functions and by technologies. The review includes the data and the information systems and in addition the communication net-works are studied generally. Thereafter the main elements of LV distribution networks are presented and their evolution visions are introduced. The main elements comprises of the distribution network, distributed generation, smart energy metering, electric vehicles and energy storages. The approach to the integration is the evolution of LV distribution networks, so four main evolution phases are introduced; traditional, boom of distributed generation, mi-crogrid and intelligent microgrid. The evolution phases bases on general research publi-cations and visions of Smart Grids. Management architectures for the networks are pre-sented. Also requirements for communication are evaluated by studying the number of nodes, capacity requirements for transferred data types and fault and event frequencies. In order to define a proposal for integrating LV distribution networks to DA, the man-agement architectures and the studied requirements are compared to produce functions for DA. As a result, the proposal is presented based on the studied architectures and re-quirements. In addition considerable issues are introduced relating to the functions in devices or sub-systems, which are needed for DA applications. This thesis indicates the need for further studies, such as: Which are the desired DA functions to be extended to LV distribution networks? Which device or system should offer the desired functions? How well the potential protocols using some media type serves the functions?fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together

Novel Methods for Loss of Mains Protection

Small-scale generation connected to distribution networks has increased significantly in recent years. This trend is driven by developments in distributed generation (DG) technologies, environmental concerns and economic reasons. The diffusion of generation into the distribution network level has many potential benefits, but it also raises challenges, such as unintentional islanding, which is hazardous to the safety of both personnel and equipment. Due to the safety risks, all DG units need to be equipped with a loss of mains (LOM) protection scheme capable of rapidly detecting and stopping islanding. LOM protection methods can be divided into passive, active and communication-based methods. Passive methods rely on detecting islanding by monitoring chosen system quantities. These methods are affordable and applicable to all types of DG units, but their performance is highly dependent on the local power imbalances between the production and consumption in the islanded zone. Most, if not all, passive methods, fail to detect islanding if the local production closely matches the local consumption. The set of power imbalance combinations that lead to non-detected islanding is referred to as the non-detection zone (NDZ). Active methods are based on deliberately injecting small perturbations to the grid and monitoring the response of the system. These methods generally have smaller NDZ than passive methods. However, this comes at the cost of degraded power quality. Communication-based methods rely on other means than the local monitoring of system quantities, which makes them immune to the NDZ problem. However, these methods tend to be costly.The performance of passive and active methods can be improved by applying more sensitive LOM protection settings. However, if the LOM protection settings are too sensitive, voltage dips caused by faults in the transmission grid may result in a cascading disconnection of DG. In order to avoid such risks, which threaten the system’s stability, many grid codes include fault-ridethrough (FRT) requirements, which specify the depth and duration of voltage dips which DG units need to be able to withstand. FRT requirements often also require the DG units to feed reactive current to the grid during the voltage dip in order to support the system voltages. The work conducted for this thesis indicates that FRT requirements significantly degrade the performance of LOM protection. This thesis also studies how the type of the protected DG unit affects LOM protection. The frequency of an islanded circuit sustained by a directly-coupled synchronous generator is determined by the local active power imbalance, whereas the frequency of an islanded circuit sustained by a converter-coupled DG unit is determined by the local reactive power imbalance. However, when there are both directly-coupled synchronous generators and convertercoupled DG units in an islanded circuit, the synchronous generator seems to dominate these relationships. This has significant implications on the performance of active LOM protection schemes.One of the main issues distribution system operators face when they are evaluating the adequacy of LOM protection for DG installations is the lack of suitable analysis tools. This thesis proposes a novel LOM risk management procedure which utilizes the existing analysis tools embedded in a modern network information system (NIS). This NIS-based procedure analyzes what kind of power imbalance combinations are possible in the studied network sections. Based on the possible combinations of power imbalances and predefined NDZ mappings of optional LOM protection schemes, the procedure tells protection engineers if there are any risks of non-detected islanding in the analyzed network sections and proposes which LOM protection schemes would be most suitable for each DG installation. Although the proposed LOM risk management tool is presented at the concept level only here, it is clearly a promising area for future research.Two active LOM protection methods and one communication-based protection automation concept were also developed during this thesis work. The first of the active LOM protection methods is based on forcing the frequency of an islanded circuit out of the utilized frequency thresholds by constant injection of reactive power pulses and a dedicated reactive power versus frequency droop. The knowledge gained during the development of this method resulted in a second, significantly more advanced, active LOM protection scheme. This is based on forcing the rate-ofchange-of-frequency of an islanded circuit to a desired value by applying a dedicated reactive power versus frequency droop. This method is able to detect islanding rapidly and reliably even if the local power imbalances are negligible. Moreover, this can be achieved with a very modest injection of reactive power. The communication-based protection automation concept is designed to solve typical DG related protection challenges and to automatically change the feeding path of the protected DG unit in case if the original feeding route becomes faulted. However, the successfulness of the automatic feeding path changing depends on many factors such as DG unit type, network parameters and the momentary input power provided by the primary energy source.The methods developed in this thesis have slightly different purposes. The proposed NIS-based LOM risk assessment procedure is useful for evaluating the adequacy of existing LOM protection as well as for choosing optimal LOM protection schemes for new DG installations. If the LOM risk assessment procedure indicates that the local power imbalances will always be very large, then passive LOM protection schemes are a sensible choice. However, should the LOM risk assessment procedure reveal that the local power imbalances could be so small that reliable LOM protection cannot be ensured with passive LOM protection schemes, then active or communication-based LOM protection schemes are preferable. Active LOM protection schemes are suitable if the ratio of converter-coupled to directly-coupled generator capacity in the analyzed zone is large. This is because certain active LOM schemes, such as the one proposed in this thesis, are able to detect islanding reliably and rapidly even if the local active- and reactive power imbalances would be negligible, provided that the ratio between converter coupled to directly coupled synchronous generator capacity is large. However, if a significant proportion of the generation capacity in the analyzed network section is synchronous generator based, then sensitive and rapid LOM protection cannot always be guaranteed. In such cases, it is advisable to utilize advanced communication-based LOM protection schemes which are immune to the NDZ problem