Explore the vast range of titles available.

With the ongoing trends in the energy sector such as vehicular electrification and renewable energy, the Smart Grid (SG) is clearly playing a more and more important role in the electric power system industry. One essential feature of the SG is the information flow over high-speed, reliable, and secure data communication networks in order to manage the complex power systems effectively and intelligently. SGs utilize bidirectional communication to function whereas traditional power grids mainly only use one-way communication. The communication requirements and suitable techniques differ depending on the specific environment and scenario. In this paper, we provide a comprehensive and up-to-date survey on the communication technologies used in the SG, including the communication requirements, physical layer technologies, network architectures, and research challenges. This survey aims to help the readers identify the potential research problems in the continued research on the topic of SG communications.

Power generation, distribution, transmission, and consumption face ongoing challenges such as smart grid management, control, and operation, resulting from high energy demand, the diversity of energy sources, and environmental or regulatory issues. This paper provides a comprehensive overview of blockchain-based solutions for smart grid management, control, and operations. We systematically summarize existing work on the use and implementation of blockchain technology in various smart grid domains. The paper compares related reviews and highlights the challenges in the management, control, and operation for a blockchain-based smart grid as well as future research directions in the five categories: collaboration among stakeholders; data analysis and data management; control of grid imbalances; decentralization of grid management and operations; and security and privacy. All these aspects have not been covered in previous reviews.

Thanks to smart grids, more intelligent devices may now be integrated into the electric grid, which increases the robustness and resilience of the system. The integration of distributed energy resources is expected to require extensive use of communication systems as well as a variety of interconnected technologies for monitoring, protection, and control. The fault location and diagnosis are essential for the security and well-coordinated operation of these systems since there is also greater risk and different paths for a fault or contingency in the system. Considering smart distribution systems, microgrids, and smart automation substations, a full investigation of fault location in SGs over the distribution domain is still not enough, and this study proposes to analyze the fault location issues and common types of power failures in most of their physical components and communication infrastructure. In addition, we explore several fault location techniques in the smart grid’s distribution sector as well as fault location methods recommended to improve resilience, which will aid readers in choosing methods for their own research. Finally, conclusions are given after discussing the trends in fault location and detection techniques.

This book discusses relevant microgrid technologies in the context of integrating renewable energy and also addresses challenging issues. The authors summarize long term academic and research outcomes and contributions. In addition, this book is influenced by the authors' practical experiences on microgrids (MGs), electric network monitoring, and control and power electronic systems. A thorough discussion of the basic principles of the MG modeling and operating issues is provided. The MG structure, types, operating modes, modelling, dynamics, and control levels are covered. Recent advances in DC microgrids, virtual synchronousgenerators, MG planning and energy management are examined. The physical constraints and engineering aspects of the MGs are covered, and developed robust and intelligent control strategies are discussed using real time simulations and experimental studies.

<p><b>A PRACTICAL GUIDE TO MICROGRID SYSTEMS ARCHITECTURE, DESIGN TOPOLOGIES, CONTROL STRATEGIES AND INTEGRATION APPROACHES</b> <p><i>Microgrid Planning and Design</i> offers a detailed and authoritative guide to microgrid systems. The editors &#150; noted experts on the topic &#150; explore what is involved in the design of a microgrid, examine the process of mapping designs to accommodate available technologies and reveal how to determine the efficacy of the final outcome. This practical book is a compilation of collaborative research results drawn from a community of experts in 8 different universities over a 6-year period. <p><i>Microgrid Planning and Design</i> contains a review of microgrid benchmarks for the electric power system and covers the mathematical modeling that can be used during the microgrid design processes. The authors include real-world case studies, validated benchmark systems and the components needed to plan and design an effective microgrid system. This important guide: <ul> <li>Offers a practical and up-to-date book that examines leading edge technologies related to the smart grid</li> <li>Covers in detail all aspects of a microgrid from conception to completion</li> <li>Explores a modeling approach that combines power and communication systems</li> <li>Recommends modeling details that are appropriate for the type of study to be performed</li> <li>Defines typical system studies and requirements associated with the operation of the microgrid</li> </ul> <p>Written for graduate students and professionals in the electrical engineering industry, <i>Microgrid Planning and Design</i> is a guide to smart microgrids that can help with their strategic energy objectives such as increasing reliability, efficiency, autonomy and reducing greenhouse gases.

Data analytics are now playing a more important role in the modern industrial systems. Driven by the development of information and communication technology, an information layer is now added to the conventional electricity transmission and distribution network for data collection, storage and analysis with the help of wide installation of smart meters and sensors. This paper introduces the big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as huge amount of data collection are firstly discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of the typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this paper. By dealing with huge amount of data from electricity network, meteorological information system, geographical information system etc., many benefits can be brought to the existing power system and improve the customer service as well as the social welfare in the era of big data. However, to advance the applications of the big data analytics in real smart grids, many issues such as techniques, awareness, synergies, etc., have to be overcome.

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

Although the impact of integrating solar and wind sources into the power system has been studied in the past, the chaos caused by wind and solar energy generation has not yet had broader mitigation solutions notwithstanding their rapid deployment. Many research efforts in using prediction models have developed real-time monitoring of variability and machine learning predictive algorithms in contrast to the conventional methods of studying variability. This study focused on the causes and types of variability, challenges, and mitigation strategies used to minimize variability in grids worldwide. A summary of the top ten cases of countries that have successfully managed variability in their electrical power grids has been presented. Review shows that most of the success cases embraced advanced energy storage, grid upgrading, and flexible energy mix as key technological and economic strategies. A seven-point conceptual framework involving all energy stakeholders for managing variability in power system networks and increasing variable renewable energy (VRE)-grid integration has been proposed. Long-duration energy storage, virtual power plants (VPPs), smart grid infrastructure, cross-border interconnection, power-to-X, and grid flexibility are the key takeaways in achieving a reliable, resilient, and stable grid. This review provides a useful summary of up-to-date research information for researchers and industries investing in a renewable energy-intensive grid.

Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applications, wireless sensor networks, cloud environment, enterprise network, web applications, and smart grid technologies. These wide emerging applications in variety of domains raise many security issues such as protecting devices and network, attacks in IoT networks, and managing resource-constrained IoT networks. To address the scalability and resource-constrained security issues, many security solutions have been proposed for IoT such as web application firewalls and intrusion detection systems. In this paper, a comprehensive survey on Intrusion Detection System (IDS) for IoT is presented for years 2015–2019. We have discussed various IDS placement strategies and IDS analysis strategies in IoT architecture. The paper discusses various intrusions in IoT, along with Machine Learning (ML) and Deep Learning (DL) techniques for detecting attacks in IoT networks. The paper also discusses security issues and challenges in IoT.

This paper provides a comprehensive review of the applications of smart meters in the control and optimisation of power grids to support a smooth energy transition towards the renewable energy future. The smart grids become more complicated due to the presence of small-scale low inertia generators and the implementation of electric vehicles (EVs), which are mainly based on intermittent and variable renewable energy resources. Optimal and reliable operation of this environment using conventional model-based approaches is very difficult. Advancements in measurement and communication technologies have brought the opportunity of collecting temporal or real-time data from prosumers through Advanced Metering Infrastructure (AMI). Smart metering brings the potential of applying data-driven algorithms for different power system operations and planning services, such as infrastructure sizing and upgrade and generation forecasting. It can also be used for demand-side management, especially in the presence of new technologies such as EVs, 5G/6G networks and cloud computing. These algorithms face privacy-preserving and cybersecurity challenges that need to be well addressed. This article surveys the state-of-the-art of each of these topics, reviewing applications, challenges and opportunities of using smart meters to address them. It also stipulates the challenges that smart grids present to smart meters and the benefits that smart meters can bring to smart grids. Furthermore, the paper is concluded with some expected future directions and potential research questions for smart meters, smart grids and their interplay.