A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

Information and communication technologies (ICT) represent a fundamental element in the growth and performance of smart grids. A sophisticated, reliable and fast communication infrastructure is, in fact, necessary for the connection among the huge amount of distributed elements, such as generators, substations, energy storage systems and users, enabling a real time exchange of data and information necessary for the management of the system and for ensuring improvements in terms of efficiency, reliability, flexibility and investment return for all those involved in a smart grid: producers, operators and customers. This paper overviews the issues related to the smart grid architecture from the perspective of potential applications and the communications requirements needed for ensuring performance, flexible operation, reliability and economics.

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A Survey on Smart Grid Potential Applications and Communication Requirements

Every organisation from the scale of whole countries down to small companies has a list of system developments which have ended in various forms of disaster. The nature of the failures varies but typical examples are: cost overruns; timescale overruns and sometimes, loss of life. The post-mortems to these systems reveal a wide range of reasons all the way from hardware failures, through software errors right to major system level mistakes. More importantly a large number of these systems share one attribute: complexity. This paper presents a fresh look at the nature of complexity in the building of computer based systems.

http://ieeexplore.ieee.org/iel3/4458/12639/00581896.pdf

Complex systems

The Council and the European Parliament

The fast-paced development of power systems necessitates smart grids to facilitate real-time control and monitoring with bidirectional communication and electricity flows. Future smart grids are expected to have reliable, efficient, secured, and cost-effective power management with the implementation of distributed architecture. To focus on these requirements, we provide a comprehensive survey on different cloud computing applications for the smart grid architecture, in three different areas— energy management , information management , and security . In these areas, the utility of cloud computing applications is discussed, while giving directions on future opportunities for the development of the smart grid. We also highlight different challenges existing in the conventional smart grid (without cloud application) that can be overcome using cloud. In this survey, we present a synthesized overview of the current state of research on smart grid development. We also identify the current research problems in the areas of cloud-based energy management, information management, and security in smart grid.

Cloud Computing Applications for Smart Grid: A Survey

The smart grid concept provides a solution to the growing recognition that current utility grids need an ICT deployment infrastructure based upgrade to allow millions of potential market players to operate and to cope with distributed generation, wide-area situational awareness, demand response, electric storage, and efficient electric transportation. Smart grid deployment is mainly about defining the necessary standards for ICT solutions. The design of the communication network associated with the smart grid involves detailed analysis of its communication requirements, a proposal of the appropriate protocol architecture, the choice of the most suitable technologies for each case study, and a scheme for the resultant heterogeneous network management system. Given the smart grid use cases, this article is focused on proposing a heterogeneous communication paradigm for smart grids based on power line communications and wireless networks. The proposal is related to the framework of the ITU ubiquitous sensor network architecture using the ITU next-generation network model. This architecture allows for better management of the QoS in the smart grid and should facilitate interoperability with other technologies.

Heterogeneous communication architecture for the smart grid

Interdisciplinary cross-cultural and cross-organizational research offers great opportunities for innovative breakthroughs in the field of smart cities, yet it also presents organizational and knowledge development hurdles. Smart cities must be large towns able to sustain the needs of their citizens while promoting environmental sustainability. Smart cities foment the widespread use of novel information and communication technologies (ICTs); however, experimenting with these technologies in such a large geographical area is unfeasible. Consequently, smart campuses (SCs), which are universities where technological devices and applications create new experiences or services and facilitate operational efficiency, allow experimentation on a smaller scale, the concept of SCs as a testbed for a smart city is gaining momentum in the research community. Nevertheless, while universities acknowledge the academic role of a smart and sustainable approach to higher education, campus life and other student activities remain a mystery, which have never been universally solved. This paper proposes a SC concept to investigate the integration of building information modeling tools with Internet of Things- (IoT)-based wireless sensor networks in the fields of environmental monitoring and emotion detection to provide insights into the level of comfort. Additionally, it explores the ability of universities to contribute to local sustainability projects by sharing knowledge and experience across a multi-disciplinary team. Preliminary results highlight the significance of monitoring workspaces because productivity has been proven to be directly influenced by environment parameters. The comfort-monitoring infrastructure could also be reused to monitor physical parameters from educational premises to increase energy efficiency.

A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring

Automatic meter reading (AMR) is an application implemented by power utilities which is becoming increasingly important in the utilities sector. It could be included in the more general environment of demand side management, which satisfies the need for more improved communications. AMR offers a better financial return due to the inclusion of other applications. Although there are several international standards which address AMR, most deployments are currently using proprietary systems. This fact may reflect that current standards do not fully cover this area. Since the power network reaches all energy meters, a convenient way to deploy AMR is to use the power lines as a transmission medium. The present-day situation is that there is mounting pressure to deploy AMR systems in a bid to provide better management of the energy demand in a bid to reduce global warming and create a more sustainable electrical system in our environmentally conscious society. This paper is focused on analyzing different standards and specifications related to AMR over powerline communications (PLC). Furthermore, two of them are chosen, implemented, and simulated using the OPNET modeler. The main goal of the implemented applications is to obtain comparative results of the two most known standard applications in AMR over PLC.

Survey and Performance Comparison of AMR Over PLC Standards

Data mining techniques are traditionally divided into two distinct disciplines depending on the task to be performed by the algorithm: supervised learning and unsupervised learning. While the former aims at making accurate predictions after deeming an underlying structure in data—which requires the presence of a teacher during the learning phase—the latter aims at discovering regular-occurring patterns beneath the data without making any a priori assumptions concerning their underlying structure. The pure supervised model can construct a very accurate predictive model from data streams. However, in many real-world problems this paradigm may be ill-suited due to (1) the dearth of training examples and (2) the costs of labeling the required information to train the system. A sound use case of this concern is found when defining data replication and partitioning policies to store data emerged in the Smart Grids domain in order to adapt electric networks to current application demands (e.g., real time consumption, network self adapting). As opposed to classic electrical architectures, Smart Grids encompass a fully distributed scheme with several diverse data generation sources. Current data storage and replication systems fail at both coping with such overwhelming amount of heterogeneous data and at satisfying the stringent requirements posed by this technology (i.e., dynamic nature of the physical resources, continuous flow of information and autonomous behavior demands). The purpose of this paper is to apply unsupervised learning techniques to enhance the performance of data storage in Smart Grids. More specifically we have improved the eXtended Classifier System for Clustering (XCSc) algorithm to present a hybrid system that mixes data replication and partitioning policies by means of an online clustering approach. Conducted experiments show that the proposed system outperforms previous proposals and truly fits with the Smart Grid premises.

Improving data partition schemes in Smart Grids via clustering data streams

This article presents a proposal for applying the ITU-T end-to-end QoS control architecture for next-generation networks to the distribution smart grid communication networks. We propose the use of a QoS broker device to enhance the QoS in the smart grid electrical distribution access domains by providing a centralization of QoS management. Our proposal takes decisions based on current network data traffic flows, existing QoS policies and customer service level agreements and facilitates interoperability with other technology domains in order to achieve seamless end-to-end QoS. The key feature of this end-toend QoS control is the mapping of QoS parameters mainly between broadband power line and wireless technologies that principally serve the distribution smart grid but it can be applied to other communication technologies as well.

Agustín Zaballos

Papers

Heterogeneous communication architecture for the smart grid

A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring

Survey and Performance Comparison of AMR Over PLC Standards

Improving data partition schemes in Smart Grids via clustering data streams

Next-generation QoS control architectures for distribution smart grid communication networks