458 research outputs found

    Advanced Metering Infrastructure Based on Smart Meters in Smart Grid

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    Due to lack of situational awareness, automated analysis, poor visibility, and mechanical switches, today\u27s electric power grid has been aging and ill‐suited to the demand for electricity, which has gradually increased, in the twenty‐first century. Besides, the global climate change and the greenhouse gas emissions on the Earth caused by the electricity industries, the growing population, one‐way communication, equipment failures, energy storage problems, the capacity limitations of electricity generation, decrease in fossil fuels, and resilience problems put more stress on the existing power grid. Consequently, the smart grid (SG) has emerged to address these challenges. To realize the SG, an advanced metering infrastructure (AMI) based on smart meters is the most important key

    Cooperative Communications in Smart Grid Networks

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    The conventional grid system is facing great challenges due to the fast growing electricity demand throughout the world. The smart grid has emerged as the next generation of grid power systems, aimed at providing secure, reliable and low cost power generation, distribution and consumption intelligently. The smart grid communication system within the smart grid network is of fundamental importance to support data transfer and information exchange within the smart grid system. The National Institute of Standards and Technology has identified wireless communications as an important networking technology to be employed in power systems. The reliability of the data transmission is essential for the smart grid system to achieve high accuracy for the power generation, distribution and consumption. In this thesis, we investigate cooperative communications to improve transmission reliability in smart grid networks. Although many issues within cooperative communication have already been addressed, there is a lack of research efforts on cooperative communication for the wireless smart grid communication system which has its own network features and different transmission requirements. In our research, the smart grid communication networks were studied, and cooperative communications in smart grid networks were analysed. The research work mainly focuses on three problems: the application of cooperative relay communications to modern smart grid communication networks, the cooperative relay-based network development strategy, and the optimization of cooperative relay communication for smart grids. For the first problem, the application of cooperative relay communication to a home area network (HAN) of smart grid system is presented. The wireless transmission reliability is identified as the issue of most concern in wireless smart grid networks. We model the smart grid HAN as a wireless mesh network that deploys cooperative relay communication to enhance the transmission reliability. We apply cooperative relay communication to provide a user equipment selection scheme to effectively improve the transmission quality between the electricity equipment and the smart meter. For the second problem, we address the network design and planning problem in the smart grid HAN. The outage performance of direct transmission and cooperative transmission was analysed. Based on the reliability performance metric that we have defined, we propose a HAN deployment strategy to improve the reliability of the transmission links. The proposed HAN deployment strategy is tested in a home environment. The smart meter location optimization problem has also been identified and solved. The simulation results show that our proposed network deployment strategy can guarantee high reliability for smart grid communications in home area networks. For the third problem, the research focuses on the optimization of the cooperative relay transmission regarding the power allocation and relay selection in the neighbourhood area network (NAN) of the smart grid system. Owing to the complexity of the joint optimization problem, reduced-complexity algorithms have been proposed to minimize the transmission power, at the same time, guarantee the link reliability of the cooperative communications. The optimization problem of power allocation and relay selection is formulated and treated as a combinatorial optimization problem. Two sub-optimal solutions that simplify the optimization process are devised. Based on the solutions, two different algorithms are proposed to solve the optimization problem with reduced complexity. The simulation results demonstrate that both two algorithms have good performance on minimizing the total transmission power while guaranteeing the transmission reliability for the wireless smart grid communication system. In this thesis, we consider cooperative communications in a smart grid scenario. We minimize the outage probability and thus improve the reliability of the communications taking place in the smart grid by considering the optimization problem of power control, relay selection and the network deployment problem. Although similar problems might have been well investigated in conventional wireless networks, such as the cellular network, little research has been conducted in smart grid communications. We apply new optimization techniques and propose solutions for these optimization problems specifically tailored for smart grid communications. We demonstrate that, compared to naively applying the algorithms suitable for conventional communications to the smart gird scenario, our proposed algorithm significantly improves the performance of smart grid communications. Finally, we note that, in future work, it will be possible to consider more complex smart grid communications system models. For example, it is worthwhile considering hetregeneous smart communications by combining HAN and wide area networks (WAN). In addition, instead of assuming that all communications have the equal priority, as in this thesis, more comprehensive analysis of the priority of the smart grid communication can be applied to the research

    Application of cognitive radio based sensor network in smart grids for efficient, holistic monitoring and control.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.This thesis is directed towards the application of cognitive radio based sensor network (CRSN) in smart grid (SG) for efficient, holistic monitoring and control. The work involves enabling of sensor network and wireless communication devices for spectra utilization via the capability of Dynamic Spectrum Access (DSA) of a cognitive radio (CR) as well as end to end communication access technology for unified monitoring and control in smart grids. Smart Grid (SG) is a new power grid paradigm that can provide predictive information and recommendations to utilities, including their suppliers, and their customers on how best to manage power delivery and consumption. SG can greatly reduce air pollution from our surrounding by renewable power sources such as wind energy, solar plants and huge hydro stations. SG also reduces electricity blackouts and surges. Communication network is the foundation for modern SG. Implementing an improved communication solution will help in addressing the problems of the existing SG. Hence, this study proposed and implemented improved CRSN model which will help to ultimately evade the inherent problems of communication network in the SG such as: energy inefficiency, interference, spectrum inefficiencies, poor quality of service (QoS), latency and throughput. To overcome these problems, the existing approach which is more predominant is the use of wireless sensor network (WSNs) for communication needs in SG. However, WSNs have low battery power, low computational complexity, low bandwidth support, and high latency or delay due to multihop transmission in existing WSN topology. Consequently, solving these problems by addressing energy efficiency, bandwidth or throughput, and latency have not been fully realized due to the limitations in the WSN and the existing network topology. Therefore, existing approach has not fully addressed the communication needs in SG. SG can be fully realized by integrating communication network technologies infrastructures into the power grid. Cognitive Radio-based Sensor Network (CRSN) is considered a feasible solution to enhance various aspects of the electric power grid such as communication with end and remote devices in real-time manner for efficient monitoring and to realize maximum benefits of a smart grid system. CRSN in SG is aimed at addressing the problem of spectrum inefficiency and interference which wireless sensor network (WSN) could not. However, numerous challenges for CRSNs are due to the harsh environmental wireless condition in a smart grid system. As a result, latency, throughput and reliability become critical issues. To overcome these challenges, lots of approaches can be adopted ranging from integration of CRSNs into SGs; proper implementation design model for SG; reliable communication access devices for SG; key immunity requirements for communication infrastructure in SG; up to communication network protocol optimization and so on. To this end, this study utilized the National Institute of Standard (NIST) framework for SG interoperability in the design of unified communication network architecture including implementation model for guaranteed quality of service (QoS) of smart grid applications. This involves virtualized network in form of multi-homing comprising low power wide area network (LPWAN) devices such as LTE CAT1/LTE-M, and TV white space band device (TVBD). Simulation and analysis show that the performance of the developed modules architecture outperforms the legacy wireless systems in terms of latency, blocking probability, and throughput in SG harsh environmental condition. In addition, the problem of multi correlation fading channels due to multi antenna channels of the sensor nodes in CRSN based SG has been addressed by the performance analysis of a moment generating function (MGF) based M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique which includes derivation and novel algorithmic approach. The results of the MATLAB simulation are provided as a guide for sensor node deployment in order to avoid the problem of multi correlation in CRSN based SGs. SGs application requires reliable and efficient communication with low latency in timely manner as well as adequate topology of sensor nodes deployment for guaranteed QoS. Another important requirement is the need for an optimized protocol/algorithms for energy efficiency and cross layer spectrum aware made possible for opportunistic spectrum access in the CRSN nodes. Consequently, an optimized cross layer interaction of the physical and MAC layer protocols using various novel algorithms and techniques was developed. This includes a novel energy efficient distributed heterogeneous clustered spectrum aware (EDHC- SA) multichannel sensing signal model with novel algorithm called Equilateral triangulation algorithm for guaranteed network connectivity in CRSN based SG. The simulation results further obtained confirm that EDHC-SA CRSN model outperforms conventional ZigBee WSN in terms of bit error rate (BER), end-to-end delay (latency) and energy consumption. This no doubt validates the suitability of the developed model in SG

    A Framework for the Performance Analysis and Simulation of RF-Mesh Advanced Metering Infrastructures for Smart Grid Applications

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    RÉSUMÉ L’Infrastructure de Mesurage AvancĂ©e (IMA), conçue Ă  l’origine pour lire Ă  distance des compteurs intelligents, est actuellement considĂ©rĂ©e comme une composante essentielle dans le domaine des Smart Grid. Le but principal des IMAs est de connecter le grand nombre de compteurs intelligents installĂ©s chez les clients au le centre de contrĂŽle de donnĂ©es de l’entreprise d’électricitĂ© et viceversa. Cette communication bidirectionnelle est une caractĂ©ristique recherchĂ©e par un grand nombre d’applications, qui visent Ă  utiliser ces infrastructures comme support Ă  la transmission de leurs donnĂ©es dans le rĂ©seau Ă©lectrique, comme par exemple la gestion de la charge et la demande-rĂ©ponse. Un grand nombre de technologies et de protocoles de communication sont actuellement utilisĂ©s dans les IMAs : parmi les solutions disponibles, le RF-Mesh est une des plus populaires, surtout grĂące au bas coĂ»t pour l’installation et les Ă©quipements. Toutefois, le dĂ©bit nominal des communications RF-Mesh est trĂšs bas, de l’ordre des dizaines de kbps, et la littĂ©rature qui traite leur performance est trĂšs limitĂ©e. Ceci pourrait en limiter l’utilisation pour des applications autres que la lecture Ă  distance des compteurs intelligents. Ce travail de thĂšse vise Ă  dĂ©velopper un systĂšme de modĂšles et outils pour Ă©valuer la performance des rĂ©seaux RF-Mesh et encourager leur utilisation pour un grand nombre d’applications dans le domaine des Smart Grid. Le systĂšme d’évaluation de performance proposĂ© est constituĂ© (i) de modĂšles analytiques, pour calculer la probabilitĂ© de collision entre les paquets transmis, (ii) d’un simulateur de rĂ©seau, pour recrĂ©er le fonctionnement des rĂ©seaux RF-Mesh dans un environnement virtuel, (iii) d’un gĂ©nĂ©rateur de topologie, pour crĂ©er des cas rĂ©alistes en se basant sur des donnĂ©es gĂ©ographiques et (iv) des mĂ©thodes pour l’analyse de la performance. Trois diffĂ©rents modĂšles analytiques ont Ă©tĂ© implĂ©mentĂ©s. Dans les deux premiers, une nouvelle formule analytique a Ă©tĂ© utilisĂ©e pour calculer la probabilitĂ© de collision entre paquets. La probabilitĂ© de collision est ensuite utilisĂ©e pour estimer le dĂ©lai moyen de/vers chaque compteur intelligent dans l’IMA analysĂ©e. Par la suite, des indices de performance, basĂ©s sur le dĂ©lai moyen, sont utilisĂ©s pour faire des analyses de performance : Ă©tudes de faisabilitĂ© pour les applications de Smart Grid, l’identification de noeuds critiques et d’éventuels goulots d’étranglement. Dans le troisiĂšme modĂšle analytique, la thĂ©orie de Markov-Modulated System est utilisĂ©e pour prendre en considĂ©ration d’importants dĂ©tails d’implĂ©mentation, comme la probabilitĂ© de retransmission et la taille des mĂ©moires tampons des noeuds, qui n’avaient pas Ă©tĂ© inclus dans la modĂ©lisations prĂ©cĂ©dente.----------ABSTRACT Advanced Metering Infrastructure (AMI), originally conceived to replace the old Automated Meter Reading (AMR) infrastructures, have now become a key element in the Smart Grid context and might be used for applications other than remote meter reading. The main driver to their widespread installation is that they provide power utilities with a bidirectional connectivity with the smart meters. A wide variety of communication networks are currently proposed to support the implementation of AMIs, and, among them, the RF-Mesh technology seems to be very popular. The main reasons for its adoption are the proprietary infrastructure and the modest cost for the installation and the equipment. However, RF-Mesh systems are characterized by poor achievable data-rates in the order of 10 kbps, and their performance is not well studied in the literature. The lack of tools and methods for the performance evaluation might be a roadblock to their widespread adoption. This thesis aims at filling this gap and increase the knowledge of large-scale RF-Mesh systems to foster their use for a wide variety of applications. We propose a comprehensive framework for the performance evaluation of large-scale AMIs adopting the RF-Mesh technology. The framework includes (i) a geo-based topology generator that uses geographic data to produce realistic AMI cases, (ii) analytic models for the computation of packet collision probability and delay, (iii) a network simulator to recreate the behavior of large-scale RF-Mesh systems, and (iv) methods to evaluate the performance. Three different analytic models are included in the framework. The first two provide a novel analytic formulation of the packet collision probability in a mesh network with timeslotted ALOHA and the Frequency Hopping Spread Spectrum (FHSS) protocol : the collision probability is then used to estimate the average delay in the network, and to define and evaluate performance indexes (e.g., critical nodes and survival function). In the third model, a complex Markov-Modulated System (MMS) is used to take into consideration important implementation details, such as the retransmission probability and the buffer size, that were not considered in the two previous models. This model also provides a more accurate computation of the packet collision probability. A Poisson distribution is used to represent the traffic coming from potential Smart Grid applications. The framework also includes an RFMesh network simulator, written in Java and Python. The tool provides additional enhanced features with respect to the analytic models, such as a dynamic routing protocol or different traffic distributions
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