File Name: opportunities and challenges of wireless sensor networks in smart grid .zip
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The Smart Grid SG is conceived as the evolution of the current electrical grid representing a big leap in terms of efficiency, reliability and flexibility compared to today's electrical network. However, the SG has posed significant challenges to utility operators—mainly very harsh radio propagation conditions and the lack of appropriate systems to empower WSN devices—making most of the commercial widespread solutions inadequate.
In this context, and as a main contribution, we have designed a comprehensive ad-hoc WSN-based solution for the Smart Grid SENSED-SG that focuses on specific implementations of the MAC, the network and the application layers to attain maximum performance and to successfully deal with any arising hurdles.
Our approach has been exhaustively evaluated by computer simulations and mathematical analysis, as well as validation within real test-beds deployed in controlled environments. The increase in the number of different energy sources the current power grid has to accommodate and regulate leads to an unavoidable increase in the complexity of grid; despite that, this power grid still lacks an effective sensing and control platform that could help provide more intelligence to the management process.
To alleviate this situation, cutting-edge sensing and control technologies are envisioned to be integrated into the current power grid. This integration will result in what is called the Smart Grid SG , a more configurable, dynamic, reliable, flexible and effective power network. The Smart Grid can be observed as the evolution of the primitive state of the current electrical grids which in most cases consist of power transmission lines more than 50—60 years old [ 2 ] and whose conceptual design has remained unchanged for more than years [ 3 ].
This out-of-date design, together with the lack of information collecting mechanisms, have been identified as the main triggers for serious power failures such as the European blackout on November 4, that affected more than 15 million European household [ 4 ] and the North American black out in , with an estimated cost of four to 10 billion dollars to the U. In light of this situation, it should be one of the priorities of every country's economy to provide their power grids with the required tools to enable intelligent asset management and successful health management.
In this regard, successfully managing key power assets substations, transformers and transmission towers among others is considered to be as important as being able to predict their remaining useful life RUL or the time to the next failure.
For such purposes, relevant data must flow in both directions: from power assets to central processing centers sending acquired physical data such as temperature, voltage, vibrations, etc. Wireless Sensor Networks WSNs are considered to play an important role in this two-way communication process, which is in charge of bringing intelligence to the electrical network.
This enabling technology has proven to have the ability to promote the use of automation, control and sensing techniques at a low cost and with very low-power consumption. Although other alternatives like wired communication systems could be considered as a more robust solution, they would require much more investment very high deployment costs , an increase in maintenance costs and less network scalability, therefore leading to an inflexible communication solution for the new grid [ 8 ]—the network would not be able to accommodate to new requirements.
The inherent decentralized nature of wireless systems, the decreasing evolution of prices, their easy and fast plug-and-play philosophy and a long-term durability have made WSN technology a clear winner in the field of power engineering [ 9 ]. The substantial benefit of a WSN lies in its capacity to deploy small battery-powered sensor nodes directly into critical power assets with practically no installation and maintenance work.
These devices wirelessly send their processed sensed data to central nodes also known as sink nodes where data is converted into decisions and sent back to nodes. However, the concern behind this approach is that designing the required WSN-based monitoring systems implies a profound knowledge of telecommunications and electronics involved, especially when dealing with an integral ad - hoc solution. Furthermore, because of the particular nature of the power grid mainly very harsh propagation conditions and the lack of appropriate inexhaustible power sources , systems intended to manage and control power assets have to fulfill specific requirements and be engineered with those requirements in mind.
Therefore, the communication protocol stack and technologies used in WSNs for the Smart Grid must be revised and improved when not specifically designed from scratch to achieve the best results.
Unfortunately, to the best of our knowledge, no integral ad - hoc WSN solution has been proposed in the Smart Grid research field so far and only few approaches have intended to adapt well-known WSN technologies originally thought to operate in different fields [ 10 — 13 ]. To address this shortcoming, and as the main contribution to this work, we propose a fully integral ad - hoc control and sensing solution based on wireless sensing technologies denoted as SENSED-SG satisfying the major requirements of a Smart Grid monitoring application.
This control and sensing solution is achieved by means of a novel protocol stack designed from scratch to appropriately exploit the benefits the SG and circumvent potential challenges. Special attention has been paid to the MAC and Network layer where the core of the communication system lies and its main settings tuned to attain good performance.
As an additional contribution, our solution is compared to ZigBee, one of the most popular standards in WSNs in a Smart Grid environment.
As far as we know, this is the first test-bed including multi-hop and cluster-tree topologies performed in a Smart Grid environment. The results reveal that our ad - hoc solution, specifically designed for the Smart Grid area, is better suited than other solutions like ZigBee adapted to operate in this research field. The rest of this paper is structured as follows.
Section 2 presents an up-to-date review of the particular requirements of a Smart Grid and the challenges the enabling technologies have to face. Section 3 introduces the related work found in the literature, summarizing their advantages and limitations. Section 4 describes our proposal as well as the mathematical analysis supporting the decisions made. The set of complex simulations conducted is reported in Section 5.
The test-beds accomplished are explained in Section 6. Finally, Section 7 concludes and outlines future works. The first step in the design of a sensing and control system based on a WSN solution must be the definition of the requirements that the system must satisfy. Generally speaking, the main goal of the Smart Grid is to improve the efficiency, reliability and safety of the current power grid while easing the process of integrating new sources of energy e.
This is accomplished by the inclusion of control, monitoring and processing tools into the current power grid. These three tools can be effectively implemented with the deployment of a ubiquitous WSN underpinned by a real-time processing support system.
WSNs, like any other technology, have to face diverse challenges to achieve their full effectiveness, especially when dealing with noisy and unsteady environments. It is a common practice in the scientific literature to describe the requirements that an ideal Smart Grid must fulfill without taking into account the limitations of the enabling technologies [ 14 , 15 ]. This leads to a deficient understanding of the underlying mechanisms that make a Smart Grid possible and may cause an incorrect vision of the whole picture.
To this aim, the following sub-sections summarize the primary requirements of the Smart Grid and connect them with the potential challenges that WSN need to tackle satisfactorily. The sensing and control system must work in optimal conditions even when the Smart Grid grows significantly. A typical utility of 25, km of high voltage power lines and thousands of capacitors and transformers could require the monitoring of over , distinct elements and distributed sensors or sources of data that may be spread over a 20—80, sq.
From the technologies' perspective, there are a couple of challenges to be faced in order to provide high scalability to a Smart Grid. First of all, the information network must be able to grow inexpensively and on demand, to enable this, monitoring systems composed of WSN devices must be of very low cost and be available to designers and end users.
Secondly, when the network increases in terms of WSN devices it does also in size. It is therefore of paramount importance the implementation of multi-hop algorithms allowing the network to operate for long distances and providing communication from any arbitrary element of the Smart Grid to the central node [ 17 , 18 ].
Power assets must be designed and engineered to ensure a proper operation during a considerable amount of time—most of the current American power grid is about 50—60 years old [ 16 ]—therefore, in a Smart Grid, any monitoring and actuating system must be ready to work with minimum maintenance for extremely long periods of time.
WSNs are composed of a large number of hardware-constrained sensing nodes whose operation periods must be adjusted to mitigate the lack of available, inexhaustible, power supplies and guarantee an appropriate lifespan. In this regard, it is worth remarking that there is no segment of the power grid where voltages are suitable for supplying energy to sensor nodes working at 5 V , and, as a solution, voluminous and expensive voltage transformers should be deployed for every single node in order to connect them directly to the power grid.
On the other hand, energy-harvesting techniques solar, vibrations, electromagnetic field, wind, etc. The goodness of this approach is heightened by the high electromagnetic fields found in power grid environments and many works have already corroborated the efficacy of it in a Smart Grid context [ 19 , 20 ].
However, solar energy is not a feasible approach for indoor environments and not reliable in many countries where the solar energy harvested may be simply insufficient during certain seasons.
On the other hand, and to the best of our knowledge, there is no current off-the-shelf sensing device fitted with the other aforementioned energy harvesting mechanisms electromagnetic fields, vibrations, wind, etc.
Therefore, the inclusion of these mechanisms is not covered in this work—although it is considered as a future potential improvement. Electronic devices may become inoperative or fail because of the presence of very high electromagnetic disturbances nearby as explored in [ 21 ].
As a result, a malfunctioning power asset can be not identified as such, provoking partial isolated outage or overall system failures which can affect larger regions and a higher number of consumers due to the cascading effect [ 22 ]—as it happened in the aforementioned European blackout. Therefore, the endurance of the WSN devices and a prompt detection of the failing ones is a must to prevent malfunctioning power assets from impoverishing the capacity of the power network. From a technological point of view, it is a common denominator of any power network the presence of high electromagnetic disturbances which strongly deteriorate the performance of any wireless network and, in particular, of a WSN deployment.
These high electromagnetic disturbances along with the absence of unlimited power sources are two of the most important concerns for a WSN operating in a power grid environment [ 21 , 23 ]. Our SENSED-SG is engineered having taken these effects into account, thus offering better network performance in comparison with other wireless technologies e.
The harsh propagation conditions found in power grid environments are mainly caused by:. Multiple metallic structures that may reflect and distort waves and cause noise-cancellation phenomena. Other communication systems working in the same frequency such as Wi-Fi, Bluetooth, Cordless Phones, etc.
SENSED-SG makes use of many of the well-known techniques noise-tolerant modulation techniques, timed-out retransmissions, use of the least-utilized frequency channel, etc. Another aspect to consider is the failure of a particular WSN node.
Under these circumstances, the network topology may change causing neighboring nodes of the faulty node to seek alternative routes to the central station. Consequently, the routing protocol must provide explicit mechanisms to refresh and discard any possible corrupted route. The growing importance of the Smart Grid make it a sensitive target for cyber terrorists, which implies a critical concern for system designers as remarked in the EPRI report [ 24 ].
Therefore, it is mandatory that the information collected and the decisions made are sent encrypted to prevent malicious users from eavesdropping or tampering with sensitive information as many works have already outlined [ 25 , 26 ]. For small embedded devices like WSN nodes, implementing state-of-the-art encryption techniques represents an important challenge due to their hardware constraints, both in terms of computing capabilities and memory.
Besides, the required extra computation leads to a non-trivial increase in the power consumption. Therefore, a thorough study of the current available encryption algorithms to select the best solution is needed. The network must acquire, process and analyze data from the power assets in a suitable period of time to allow decision-making and control algorithms running in the central node to react against these changes appropriately.
In this regard the differences between the asset management and the power system protection should be noted. While the former does not impose hard constraints in terms of real-time processing and generates large amount of data, the latter inherently requires a strict real-time decision-making system and dispatches fewer packets [ 21 , 27 ]. It is accepted by the research community that measured data in wireless asset-managing systems, like the one proposed here, should reach sink nodes in less than 15 s [ 15 ].
It is important to highlight, that such constraint only applies to wireless asset-managing system and other systems wired or those intended to be used in power system protection may have to meet other requirements such as those suggested in the IEC standard.
From a technological point of view, to ensure an appropriate asset managing solution in terms of timing constraints, diverse aspects must be taken into account. Firstly, despite the WSN nodes of the Smart Grid are able to collect large amounts of data, this information has to be pre-processed in every node before being sent to the wireless network. This is carried out to prevent large volumes of data from simultaneously reaching the central node, negatively affecting its ability to furnish a real-time decision making system.
It has been proven as a non-trivial issue in widespread WSN sensing systems such as the London Traffic Management system [ 28 ]. Secondly, WSN nodes are extremely hardware limited devices incapable of computing complex mathematical operations, therefore there must exist a study of the trade-off between pre-processing in the node and the number of packets dispatched to the network.
Moreover, to guarantee adequate data collection times, data latency must rank within a tolerable range. To achieve this goal, specific protocols settings must be tweaked as will be explored later in Section 5. Finally, extensive tests must be carried out to validate the deployed solution in terms of end-to-end delay and to ensure the proper functioning of the network.
In the framework of a Smart Grid, interoperability means the ability of diverse systems to work together, exchange information or equipment from each other and operate cooperatively to perform several tasks [ 15 ]. To provide a suitable level of interoperability and a seamless data flow among WSN devices, the use of standards is a key issue [ 29 , 30 ]. Furthermore, the communication protocols and message exchange patterns must be fully documented to facilitate interoperability with other potential systems.
Many papers have looked into the requirements of a Smart Grid as the main way to understand the big picture [ 14 , 15 , 27 ], on the other hand many others have kept the focus on the challenges diverse technologies have to face in order to implement a Smart Grid [ 16 , 31 ].
However, as far as we know, there is no single work that unifies these two aspects—requirements of a Smart Grid and what challenges the enabling technologies have to tackle to achieve them—with the aim of setting the starting point for a Smart Grid suitable control and sensing solution. Nevertheless, we believe that individual technologies that are interconnected to form a bigger system cannot be analyzed independently since doing so will overlook the non-trivial interaction between them.
For instance, in [ 34 ] a new secure routing protocol including quality of service support for Smart Grids is presented and analyzed. Although several simulations are shown and their outcomes discussed, the authors omit the effect of an underlying MAC Medium Access Control layer that may severely deteriorate the results e. In this regard, our analyses and test-beds are aimed at providing results of different performance metrics considering every possible interaction between protocols—as will be reflected in Sections 6 and 7.
In short, a complex system cannot be analyzed as the sum of its composing elements. In [ 35 ], a performance evaluation of a ZigBee-based approach for different Smart Grid environments is carried out by means of ns-2 simulations.
We present some of the ongoing standardisation work in M2M communications followed by the application of machine-to-machine M2M communications to smart grid. We analyse and discuss the enabling technologies in M2M and present an overview of the communications challenges and research opportunities with a focus on wireless sensor networks and their applications in a smart grid environment. Smart grid SG networks will be characterised by the tight integration of a flexible and secure communications network with novel energy management techniques requiring a very large number of sensor and actuator nodes. The communications network will not only facilitate advanced control and monitoring, but also support extension of participation of generation, transmission, marketing, and service provision to new interested parties. In order to realise the intelligent electricity network, machine-to-machine M2M communication is considered as a building block for SG as a means to deploy a wide-scale monitoring and control infrastructure, thus bringing big opportunities for the information and communication technology ICT industry.
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4-compliant sensor network platforms and guide design decisions and tradeoffs for WSN-based smart-grid applications. Index Terms—CC, diagnostics, IEEE.
Metrics details. The smart city model is used by many organizations for large cities around the world to significantly enhance and improve the quality of life of the inhabitants, improve the utilization of city resources, and reduce operational costs.
Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Opportunities and Challenges of Wireless Sensor Networks in Smart Grid Abstract: The collaborative and low-cost nature of wireless sensor networks WSNs brings significant advantages over traditional communication technologies used in today's electric power systems. Recently, WSNs have been widely recognized as a promising technology that can enhance various aspects of today's electric power systems, including generation, delivery, and utilization, making them a vital component of the next-generation electric power system, the smart grid. However, harsh and complex electric-power-system environments pose great challenges in the reliability of WSN communications in smart-grid applications.
Но за три дня до голосования в конгрессе, который наверняка бы дал добро новому стандарту. молодой программист из лаборатории Белл по имени Грег Хейл потряс мир, заявив, что нашел черный ход, глубоко запрятанный в этом алгоритме. Черный ход представлял собой несколько строк хитроумной программы, которые вставил в алгоритм коммандер Стратмор. Они были вмонтированы так хитро, что никто, кроме Грега Хейла, их не заметил, и практически означали, что любой код, созданный с помощью Попрыгунчика, может быть взломан секретным паролем, известным только АНБ. Стратмору едва не удалось сделать предлагаемый стандарт шифрования величайшим достижением АНБ: если бы он был принят, у агентства появился бы ключ для взлома любого шифра в Америке.
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