Sensor Networks In Smart Grid Research Articles

Coverage hole optimization with a mobile sensor in wireless sensor networks for smart grid

The Smart Grid (SG) enables electricity and energy exchange between two ends of the grid. Wireless Sensor Networks (WSNs) are considered as an enabling communication technology for effective SG management. How well the target region is covered by a WSN indicates the service quality of the relevant implementation. Since effective monitoring is key to exploiting the benefits of the SG, maintaining the desired coverage level is critical in WSN for SG applications. However, some uncovered regions (coverage holes) might emerge due to several reasons such as improper localization or sensor malfunctioning. In this paper, we propose using a mobile sensor to cover such blind regions in a timely and hence energy-efficient way. First, we present a novel 0–1 mixed integer programming model without restrictive assumptions about the mobility pattern to find the shortest trajectory for the mobile sensor. Then we show that the problem is NP-hard with a polynomial reduction to the Traveling Salesman Problem. Consequently, we present an optimization-based heuristic, two heuristic-based algorithms, and a hybrid algorithm. We show that our heuristics are efficient as they find high quality solutions in a few seconds. We also observe that assumptions about the starting point of the tour and the potential set of stops significantly affect the final tour’s length.

Analysis and Prospect of the Application of Wireless Sensor Networks in Ubiquitous Power Internet of Things.

With the rapid development of the economy and society, the low efficiency and high loss of the traditional power grid can no longer meet the growing social demand, and the power grid market is facing a reform. Smart grid, as a next-generation power system, it can effectively improve the performance of traditional power grids. The ubiquitous power Internet of Things (UPIOT) replaces the traditional grids with efficient, safe, reliable, and flexible new grids, improves the utilization efficiency of the grid, reduces the loss of the power grid in the transmission process, and can meet the needs of different types of markets and users. As an advanced information acquisition and processing technology, wireless sensor networks have been widely used in medical, industrial, agricultural, commercial, and public management fields. It is an important means to promote future economic development and build a harmonious society. In the power system, wireless sensor network technology can be widely used in many fields such as line fault location, real-time monitoring, smart meter reading, and relay protection. In this paper, the basic concepts and overall architecture of ubiquitous power Internet of Things are summarized. Then, we summarize the research status of the wireless sensor network in smart grid, including power equipment, line monitoring, smart grid wireless automatic meter reading, distribution network relay protection, power assets life-cycle management, power grid fault location, and power grid fault diagnosis. In view of the technical characteristics of wireless sensor networks, combined with the production links of power systems, the application framework of wireless sensor network technology in the power systems is constructed. The application of wireless sensor networks is prospected from the aspects of network development of relay protection, application research of smart substation, application research of power grid catastrophe, security protection of power system, and deep-seated ubiquitous power Internet of Things.

Proportional‐integral‐derivative controller‐based self‐healing of distribution system using wireless sensor networks in smart grid

SummaryThe grid is a platform of distributing the power to the consumers; if an automatic controlling and monitoring are connected with the grid, it referred to as smart grid (SG). Self‐healing is the approach of restoring the unaffected areas without affecting the system performance. The term restoration is if a fault occurs on a distribution system, it must be isolated; after that, it can be reconfigured to restore the unaffected areas. The distribution system cannot work as efficient without the self‐healing approach because it will affect the unaffected areas without any proper reason. This paper proposed a multiagent system with controlled voltage (MAS‐CV) along with self‐healing of wireless sensor network (WSN) with proportional integral derivative (PID) controller in smart grid. At initial, the magnetic flux sensors are placed in the pole transformer for detection of flux leakage. The sensed data are transferred to the distribution grid, where the multiagent system (MAS) is established to carrying out the load restoration process (i.e., self‐healing). Connection agents (CA), monitor agent (MA), main feeder agent (MFA), backup feeder agent (BFA), supporting feeder agent (SFA), and local agent (LA) are the agents presented in the paper. Each agent is communicating via agent communication language (ACL) for the restoration process; after all the loads are restored, the voltage drop of the system is controlled by the proportional integral derivative controller. The simulation results of the proposed method show that the restoration of loads is improved and number of switching is reduced with improved data transmission. Thus, the cost of the proposed method is reduced by the reduced switches. At last, the controlled power from the distribution grid is send to the consumer.

RVFL-LQP: RVFL-Based Link Quality Prediction of Wireless Sensor Networks in Smart Grid

In the application of wireless sensor networks (WSNs) to smart grid, real-time and accurate wireless link quality prediction (LQP) is important to determine which link is reliable enough to undertake the communication task. However, the existing LQP methods are neither suitable to describe the dynamic stochastic features of link quality nor to ensure the validity of prediction results. In this paper, a random-vector-functional-link-based LQP (RVFL-LQP) algorithm is proposed. The algorithm selects the signal-to-noise ratio (SNR) as the link quality metric and decomposes the raw SNR sequence into the time-varying sequence and the stochastic sequence according to the analysis of wireless link characteristics. Then, the RVFL network is used to establish the prediction model of the time-varying sequence and the variance of the stochastic sequence. Lastly, the probability-guaranteed interval boundary of SNR is predicted, and the validity and practicability of prediction results are evaluated by comparative experiments and real-world application, respectively.

Distributed Dynamic Power Allocation Strategy Based on Energy Balance in Wireless Sensor Networks for Smart Grid

The characteristics of wireless sensor networks can solve many problems in smart grid construction. The power allocation strategy can effectively improve the energy efficiency of wireless sensor networks, but the static strategy will lead to unbalanced network energy consumption. So we construct a function of the energy condition of the reaction node. The transmission power of nodes is changed dynamically through the exchanging of information between neighbor nodes. And a distributed dynamic power allocation strategy based on energy balance is proposed. Simulation results show that it can effectively prolong the overall survival time of the network. This method can be used in a power system private network.

Secrecy analysis of wireless sensor network in smart grid with destination assisted jamming

In this study, the authors investigate the physical layer security performance over Rayleigh fading channels in the presence of impulsive noise, as encountered, for instance in smart grid environments. For this scheme, secrecy performance metrics are considered with and without destination assisted jamming at the eavesdropper's side. Specifically, they derive analytical expressions for the secrecy outage probability (SOP), at the legitimate receiver. Finally, numerical results are provided to verify the accuracy of the authors' derivations. From the obtained results, it is verified that the SOP, without destination assisted jamming, is flooring at high signal-to-noise-ratio values and that it can be significantly improved with the use of jamming.

Trust aware fault tolerant prediction model for wireless sensor network based measurements in Smart Grid environment

Reliable and accurate prediction models for power generation, transmission and distribution can radically transform the Smart Grid (SG) environment. The application of wireless sensor networks in SG is among the latest areas of research. In this paper, a resilient Time Series Trust Model (TSTM) has been implemented in wireless sensor nodes that are modeled as smart meters in power generation and consumption. The performance of the proposed trust model has been compared with four other models. Non-linear auto regressive trust based prediction models for power generation and power consumption has also been proposed based on five different algorithms namely treepartition, wavenet, sigmoidal, feed forward net and cascade forward net. The prediction accuracy of these models are evaluated based on suitable metrics. The resilience of the proposed trust model is validated in the presence of offset fault and data loss fault in smart meters. The proposed TSTM emerges as the most robust and fault tolerant model.

A new efficient error control algorithm for wireless sensor networks in smart grid

Error detection and correction is an important issue in the design and maintenance of a smart grid communication network to provide reliable communication between sender and receiver. Various error-control coding techniques are employed to reduce bit error rates (BER) in wireless sensor networks (WSNs). The performance of these techniques is also compared and evaluated to find the most suitable technique for WSNs. This is the first study to compare the most efficient coding techniques in the smart grid environment, and it suggests a new error correction algorithm based on this comparison result. Therefore, this article first examines and compares two forward error control (FEC) coding techniques such as Bose-Chaudhuri-Hochquenghem code (BCH) and Reed Solomon code (RS) with various modulation methods including frequency shift keying (FSK), offset quadrature phase-shift keying (OQPSK), and differential phase shift keying (DPSK) in a 500 kV line-of-sight (LoS) substation smart grid environment. Second, as a result of this comparison, a new adaptive error control (AEC) algorithm is proposed. Adaptive error control adaptively changes error correction code (ECC) based on the channel behavior that is observed through the packet error rate (PER) in the recent previous transmissions. The link-quality-aware capacitated minimum hop spanning tree (LQ-CMST) algorithm and the multi-channel scheduling algorithm are used for data transmission over the log-normal channel. Therefore, the performance of compared coding techniques and AEC are also evaluated when multiple channels are used during transmission. Further, AEC is compared with static RS and without-FEC methods based on performance metrics such as the throughput, BER, and delay in different smart grid environments, e.g., 500 kV Substation (LoS), underground network transformer vaults (UTV) (LoS), and main power control room (MPR) (LoS). Our simulation results indicate that the proposed AEC algorithm achieves better performances than all those techniques.

Cognitive Radio Based Sensor Network in Smart Grid: Architectures, Applications and Communication Technologies

The cognitive radio-based sensor network (CRSN) is envisioned as a strong driver in the development of modern power system smart grids (SGs). This can address the spectrum limitation in the sensor nodes due to interference cause by other wireless devices operating on the same unlicensed frequency in the Industrial, Scientific and Medical band. These sensor nodes are used for monitoring and control purposes in various components of a SG, ranging from generation, transmission, and distribution, and down to the consumer, including monitoring of utility network assets. A reliable SG communication network architecture is required for transferring information which needed by the SG applications, alongside the monitoring and control by CRSN. Hence, this paper investigates and explores the CRSN conceptual framework, and SG communication architecture with its applications; vis-a-vis the communication access technologies, including implementation design with quality of service support. Consequently, this paper highlights various research gaps, such as implementation design model, utilization of LPWAN for CRSN based SG deployment, and so on. This includes discussion on the future direction for various aspects of the CRSN in SG. To address these research gaps, we introduced a smart unified communication solution to improve the efficiency of the SG and mitigate various associated challenges.

SACRB-MAC: A High-Capacity MAC Protocol for Cognitive Radio Sensor Networks in Smart Grid.

The Cognitive Radio Sensor Network (CRSN) is considered as a viable solution to enhance various aspects of the electric power grid and to realize a smart grid. However, several challenges for CRSNs are generated due to the harsh wireless environment in a smart grid. As a result, throughput and reliability become critical issues. On the other hand, the spectrum aggregation technique is expected to play an important role in CRSNs in a smart grid. By using spectrum aggregation, the throughput of CRSNs can be improved efficiently, so as to address the unique challenges of CRSNs in a smart grid. In this regard, we proposed Spectrum Aggregation Cognitive Receiver-Based MAC (SACRB-MAC), which employs the spectrum aggregation technique to improve the throughput performance of CRSNs in a smart grid. Moreover, SACRB-MAC is a receiver-based MAC protocol, which can provide a good reliability performance. Analytical and simulation results demonstrate that SACRB-MAC is a promising solution for CRSNs in a smart grid.

Research on the Influence of Sensor Network Communication in the Electromagnetic Environment of Smart Grid

Smart grid adopts wildly various sensors for lots of applications to sense work environment, monitor production process and realize the automation control, and so forth. However, due to the wireless and open communication, the electromagnetic phenomena in the communication and the electric network of the sensor network usually produce the mutual interference. Meanwhile, electrical equipment and sensors are usually in high pressure electromagnetic environment. Therefore, it is very necessary and important to ensure the reliability and stability in smart grid applications. And the sensing and communication device must be after equal parameter simulation environment under strict evaluation and verification can be put to use in actual production operation system. In this paper, we analyze the application of wireless sensor network in smart grid and propose the test method of the interaction between WSN and smart grid.

Identified improvements of wireless sensor networks in smart grid: issues, requirements and challenges

Communications infrastructure is a basic part for the success of smart grid. Optimisation of energy consumption in the future intelligent energy networks (smart grids) will be based on the integrated near real-time between the different elements of grid network communications. Through a communication infrastructure, a smart grid can improve the reliability of power, eliminate power outages, and optimise energy consumption. The network gets smarter by improving detection, so the most important element that makes the smart grid is wireless sensor networks. Among them, one of the most important applications is a sensor data collection. This paper discusses some of communications research challenges and opportunities in the areas of smart grid and smart meters. In particular, we focus on some of the main communications challenges to achieve interoperability and future proof, smart grid/metering networks. We describe the basic taxonomy and propose to break the network data collection of wireless sensors.

A survey on wireless sensor networks for smart grid

The traditional power grid in many countries suffers from high maintenance costs and scalability issues along with the huge expense of building new power stations, and lack of efficient system monitoring that could increase the overall performance by acting proactively in preventing potential failures. To address these problems, a next-generation electric power system, called the smart grid (SG), has been proposed as an evolutionary system for power generation, transmission, and distribution. To this end, the SGs utilize renewable energy generation, smart meters and modern sensing and communication technologies for effective power system management, and hence, succeeding in addressing many of the requirements of a modern power grid system while significantly increase its performance. Recently, wireless sensor networks (WSNs) have been recognized as a promising technology to achieve seamless, energy efficient, reliable, and low-cost remote monitoring and control in SG applications. In these systems, the required information can be provided to electric utilities by wireless sensor systems to enable them to achieve high system efficiency. The real-time information gathered from these sensors can be analyzed to diagnose problems early and serve as a basis for taking remedial action. In this paper, first WSN-based SG applications have been explored along with their technical challenges. Then, design challenges and protocol objectives have been discussed for WSN-based SG applications. After exploring applications and design challenges, communication protocols for WSN-based SG applications have been explained in detail. Here, our goal is to elaborate on the role of WSNs for smart grid applications and to provide an overview of the most recent advances in MAC and routing protocols for WSNs in this timely and exciting field.

Secure and reliable surveillance over cognitive radio sensor networks in smart grid

In view of recent attacks on smart grid surveillance is of vital importance to enforce surveillance based disaster recovery management operations to ensure seamless energy generation and distribution. The reliability of disaster recovery management depends on availability and privacy preservation of surveillance data. In this paper we propose a reliable privacy preserving smart grid surveillance architecture over cognitive radio sensor networks. Cognitive radio sensor networks are capable of facilitating reliable communications through opportunistic spectrum sensing capabilities as opposed to fixed radio terminal networks based surveillance architectures. The main privacy preserving feature is a novel energy aware physical unclonable function (PUF) based cryptographic key generation method. The proposed solution determines the encryption key length depending on the remaining energy reserve to facilitate data transmission over an expected period of time with minimum channel interferences. Based on the experimental evaluation, the PUF pattern matching based key generation is viable for 32 bits pattern length over a cognitive radio sensor with optimum power utilization and with a probability of reproducibility of a bit pattern (i−p)=0. We have also performed experiments to validate the reliability model using real-world data. In conclusion, our proposed cognitive radio sensor based solution provide more pragmatic insights in reliability assurances for surveillance in smart grid.

Secure smart grid communications and information integration based on digital watermarking in wireless sensor networks

As more and more wireless sensor nodes and networks are employed to acquire and transmit the state information of power equipment in smart grid, we are in urgent need of some viable security solutions to ensure secure smart grid communications. Conventional information security solutions, such as encryption/decryption, digital signature and so forth, are not applicable to wireless sensor networks in smart grid any longer, where bulk messages need to be exchanged continuously. The reason is that these cryptographic solutions will account for a large portion of the extremely limited resources on sensor nodes. In this article, a security solution based on digital watermarking is adopted to achieve the secure communications for wireless sensor networks in smart grid by data and entity authentications at a low cost of operation. Our solution consists of a secure framework of digital watermarking, and two digital watermarking algorithms based on alternating electric current and time window, respectively. Both watermarking algorithms are composed of watermark generation, embedding and detection. The simulation experiments are provided to verify the correctness and practicability of our watermarking algorithms. Additionally, a new cloud-based architecture for the information integration of smart grid is proposed on the basis of our security solutions.

Survey on Application of Wireless Sensor Network in Smart grid

The Wireless Sensor Network (WSN) is a promoted technology applied in the communication system of smart grid, which enjoys low cost, low power dissipation, self-organization, and strong flexibility. This paper presents the applications of WSN in condition-based maintenance, smart metering, smart-home, fault location, distributed bus protection of power networks, as well as some other application in disaster prevention with the main technical characteristics of WSN. It not only proposes the basic design philosophy of WSN's applications in areas, but also summarizes the superiority of the communication systems using WSN in smart grid.

Heterogeneous Cognitive Radio Sensor Networks for Smart Grid: Markov Analysis and Applications

Cognitive radio sensor networks (CRSN) have the potential to vastly improve spectrum utilization among heterogeneous applications for smart grid. To date, there has been little queueing theoretic modeling conducted of such systems that provide a quantitative estimate of the benefits from CRSN. We propose a novel queuing model which incorporates service rate and functional heterogeneity on the servers and implement preemptive priority among the varying service classes. Initially, we present a continuous-time Markov chain for performance analysis of CRSN for two colocated cognitive systems with various priority classes and bandwidth requirements. Closed form results for spectrum utilization, blocking probability, and optimal traffic intensities are then derived for the scenario of two heterogeneous secondary systems. A channel packing scheme is then proposed to pack smaller bandwidth users into clusters of adjacent channels to alleviate blockage of users requiring larger bandwidth requirements. Based on the numerical results of benefits of our scheme, we propose a feasible application for smart grid.

CRB-MAC: A Receiver-Based MAC Protocol for Cognitive Radio Equipped Smart Grid Sensor Networks

Wireless sensor networks (WSNs) have been widely recognized as a promising solution for enhancing various aspects of electric power grid and realizing the vision of smart grid. However, the challenging wireless environment in smart grid creates a number of challenges for WSNs, as a result of which energy efficiency and reliability become critically important. On the other hand, cognitive radio (CR) technology is expected to play a vital role in smart grid networks. The CR equipped sensor networks [or cognitive sensor networks (CSNs)] can effectively address the unique challenges of WSNs in smart grid. In this paper, we aim to design an energy efficient and reliable medium access control (MAC) protocol for CSNs. In this regard, we propose CRB-MAC which is a receiver-based MAC protocol for CSNs. The CRB-MAC uses preamble sampling and opportunistic forwarding techniques for providing high energy efficiency and reliability. In addition, CRB-MAC explicitly accounts for the peculiarities of a CR environment. Analytical and simulation results demonstrate the effectiveness of CRB-MAC as a viable solution for CSNs.

Top-k query framework in wireless sensor networks for smart grid

The smart grid has caught great attentions in recent years, which is poised to transform a centralized, producer-controlled network to a decentralized, consumer-interactive network that's supported by fine-grained monitoring. Large-scale WSNs (Wireless Sensor Networks) have been considered one of the very promising technologies to support the implementation of smart grid. WSNs are applied in almost every aspect of smart grid, including power generation, power transmission, power distribution, power utilization and power dispatch, and the data query processing of `WSNs in power grid? become an hotspot issue due to the amount of data of power grid is very large and the requirement of response time is very high. To meet the demands, top-k query processing is a good choice, which performs the cooperative query by aggregating the database objects' degree of match for each different query predicate and returning the best k matching objects. In this paper, a framework that can effectively apply top-k query to wireless sensor network in smart grid is proposed, which is based on the cluster-topology sensor network. In the new method, local indices are used to optimize the necessary query routing and process intermediate results inside the cluster to cut down the data traffic, and the hierarchical join query is executed based on the local results. Besides, top-k query results are verified by the clean-up process, and two schemes are taken to deal with the problem of node's dynamicity, which further reduce communication cost. Case studies and experimental results show that our algorithm has outperformed the current existing one with higher quality results and better efficiently.

Self-similarity of Traffic in Wireless Sensor Networks for Smart Grid

Self-similarity of Traffic in Wireless Sensor Networks for Smart Grid