Special section on smart grids: A hub of interdisciplinary research : IEEE ACCESS Special section editorial smart grids: A hub of interdisciplinary research

International audienceThe smart grid is an important hub of interdisciplinary research where researchers from different areas of science and technology combine their efforts to enhance the traditional electrical power grid. Due to these efforts, the traditional electrical grid is now evolving. The envisioned smart grid will bring social, environmental, ethical, legal and economic benefits. Smart grid systems increasingly involve machine-to-machine communication as well as human-to-human, or simple information retrieval. Thus, the dimensionality of the system is massive. The smart grid is the combination of different technologies, including control system theory, communication networks, pervasive computing , embedded sensing devices, electric vehicles, smart cities, renewable energy sources, Internet of Things, wireless sensor networks, cyber physical systems, and green communication. Due to these diverse activities and significant attention from researchers, education activities in the smart grid area are also growing. The smart grid is designed to replace the traditional electrical power grid. The envisioned smart grid typically consists of three networks: Home Area Networks (HANs), Neighborhood Area Networks (NANs), and Wide Area Networks (WANs). HANs connect the devices within the premises of the consumer and connect smart meters, Plug-in Electric Vehicles (PEVs), and distributed renewable energy sources. NANs connect multiple HANs and communicate the collected information to a network gateway. WANs serve as the communication backbone. Communication technologies play a vital role in the successful operation of smart grid. These communication technologies can be adopted based upon the specific features required by HANs, NANs, and WANs. Both wired and the wireless communication technologies can be used in the smart grid [1]. However, wireless communication technologies are suitable for many smart grid applications due to the continuous development in the wireless research domain. One drawback of wireless communication technologies is the limited availability of radio spectrum. The use of cognitive radio in smart grid communication will be helpful to break the spectrum gridlock through advanced radio design and operating in multiple settings, such as underlay, overlay, and interweave [2]. The smart grid is the combination of diverse sets of facilities and technologies. Thus, the monitoring and control of transmission lines, distribution facilities, energy generation plants, and as well as video monitoring of consumer premises can be conducted through the use of wireless sensor networks [3]–[6]. In remote sites and places where human intervention is not possible, wireless sensor and actuator networks can be useful for the successful smart grid operation [7], [8]. Since wireless sensor networks operate on the Industrial, Scientific, and Medical (ISM) band, the spectrum might get congested due to overlaid deployment of wireless sensor networks in the same premises. Thus, to deal with this spectrum congestion challenge, cognitive radio sensor networks can be used in smart grid environments [9], [10]. The objective of this Special Section in IEEE ACCESS is to showcase the most recent advances in the interdisciplinary research areas encompassing the smart grid. This Special Section brings together researchers from diverse fields and specializations, such as communications engineering, computer science, electrical and electronics engineering, educators, mathematicians and specialists in areas related to smart grids. In this Special Section, we invited researchers from academia, industry, and government to discuss challenging ideas, novel research contributions, demonstration results, and standardization efforts on the smart grid and related areas. This Special Section is a collection of eleven articles. These articles are grouped into the following four areas: (a) Reliability, security, and privacy for smart grid, (b), Demand response management, understanding customer behavior, and social networking applications for smart grid, (c) Smart cities, renewable energy, and green smart grid, and (d) Communication technologies, control and management for the smart grid

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

An Approximately Optimal Algorithm for Scheduling Phasor Data Transmissions in Smart Grid Networks

In this paper, we devise a scheduling algorithm for ordering transmission of synchrophasor data from the substation to the control center in as short a time frame as possible, within the realtime hierarchical communications infrastructure in the electric grid. The problem is cast in the framework of the classic job scheduling with precedence constraints. The optimization setup comprises the number of phasor measurement units (PMUs) to be installed on the grid, a weight associated with each PMU, processing time at the control center for the PMUs, and precedence constraints between the PMUs. The solution to the PMU placement problem yields the optimum number of PMUs to be installed on the grid, while the processing times are picked uniformly at random from a predefined set. The weight associated with each PMU and the precedence constraints are both assumed known. The scheduling problem is provably NP-hard, so we resort to approximation algorithms which provide solutions that are suboptimal yet possessing polynomial time complexity. A lower bound on the optimal schedule is derived using branch and bound techniques, and its performance evaluated using standard IEEE test bus systems. The scheduling policy is power grid-centric, since it takes into account the electrical properties of the network under consideration.Comment: 8 pages, published in IEEE Transactions on Smart Grid, October 201

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

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

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