Future Wireless Sensor Networks for the Smart Grid

2015 ◽  
pp. 65-106
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Wireless Sensor

Deploying wireless sensor networks-based smart grid for smart meters monitoring and control

2018 ◽  
Vol 31 (10) ◽  
pp. e3557 ◽  
Author(s):  
Renato William R. de Souza ◽  
Leonardo R. Moreira ◽  
Joel J. P. C. Rodrigues ◽  
Rafael R. Moreira ◽  
Victor Hugo C. de Albuquerque
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Wireless Sensor ◽  
Monitoring And Control ◽  
Smart Meters ◽  
And Control

scholarly journals A Fiber-Wireless Sensor Networks QoS Mechanism for Smart Grid Applications

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 37601-37610 ◽  
Author(s):  
Michael Akerele ◽  
Irfan Al-Anbagi ◽  
Melike Erol-Kantarci
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Wireless Sensor ◽  
Grid Applications

scholarly journals Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 567 ◽  
Author(s):  
Chatura Seneviratne ◽  
Patikiri Arachchige Don Shehan Nilmantha Wijesekara ◽  
Henry Leung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Communication Networks ◽  
Smart Grids ◽  
Measurement Errors ◽  
Power Grid ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Grid Infrastructures

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.

An Efficient Sleeping Scheduling for Save Energy Consumption in Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 2288-2293
Author(s):  
Shu Guang Jia ◽  
Li Peng Lu ◽  
Ling Dong Su ◽  
Gui Lan Xing ◽  
Ming Yue Zhai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Round Robin ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Active Sensors ◽  
Save Energy ◽  
Battery Energy

Smart grid has become one hot topic at home and abroad in recent years. Wireless Sensor Networks (WSNs) has applied to lots of fields of smart grid, such as monitoring and controlling. We should ensure that there are enough active sensors to satisfy the service request. But, the sensor nodes have limited battery energy, so, how to reduce energy consumption in WSNs is a key challenging. Based on this problem, we propose a sleeping scheduling model. In this model, firstly, the sensor nodes round robin is used to let as little as possible active nodes while all the targets in the power grid are monitored; Secondly, for removing the redundant active nodes, the sensor nodes round robin is further optimized. Simulation result indicates that this sleep mechanism can save the energy consumption of every sensor node.

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