A GPS-free power grid monitoring system over mobile platforms

Author(s):  
Haoyang Lu ◽  
Lingwei Zhan ◽  
Yilu Liu ◽  
Wei Gao
2014 ◽  
Vol 23 (03n04) ◽  
pp. 1450024
Author(s):  
Michael Gouzman ◽  
Serge Luryi

A shortcoming of the contemporary power grid monitoring is that the system does not know its own state. Instead of taking automatic note of energy-flow disruptions, one deals with haphazard telephone reports of “no light in our house”. We propose a novel monitoring system that requires no restructuring of the power distribution network and can be applied both to the existing grids and the future “smart grids”. The proposed system is based on a network of inexpensive sensors, installed on every connecting line and communicating measured data to a central processing unit. Our approach is topological in nature, based on the connectivity aspects of the power grid embodied in Kirchhoff's current law that must be valid at every node of the network. We argue that the state of the network can be adequately characterized by specifying the RMS currents and the direction of energy flow in all connecting lines. It is essential that in this description one does not have to know the magnitude of the energy flow, only its direction. This eliminates the need to measure voltage, which would be prohibitively costly on the massive scale. In contrast, the relative phase between the current and voltage can be measured easily. Another essential point is that the instantaneous RMS currents are impractical to record and communicate, hence local averaging is required. Since Kirchhoff's law should remain valid upon averaging, the latter must be carried out at each sensor synchronously over the entire network with global synchronization provided by the GPS.


2020 ◽  
Vol 7 (8) ◽  
pp. 7773-7782
Author(s):  
Joe-Air Jiang ◽  
Jen-Cheng Wang ◽  
Hung-Shuo Wu ◽  
Chien-Hsing Lee ◽  
Cheng-Ying Chou ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hongyang He ◽  
Yue Gao ◽  
Yong Zheng ◽  
Yining Liu

Companies that produce energy transmit it to any or all households via a power grid, which is a regulated power transmission hub that acts as a middleman. When a power grid fails, the whole area it serves is blacked out. To ensure smooth and effective functioning, a power grid monitoring system is required. Computer vision is among the most commonly utilized and active research applications in the world of video surveillance. Though a lot has been accomplished in the field of power grid surveillance, a more effective compression method is still required for large quantities of grid surveillance video data to be archived compactly and sent efficiently. Video compression has become increasingly essential with the advent of contemporary video processing algorithms. An algorithm’s efficacy in a power grid monitoring system depends on the rate at which video data is sent. A novel compression technique for video inputs from power grid monitoring equipment is described in this study. Due to a lack of redundancy in visual input, traditional techniques are unable to fulfill the current demand standards for modern technology. As a result, the volume of data that needs to be saved and handled in live time grows. Encoding frames and decreasing duplication in surveillance video using texture information similarity, the proposed technique overcomes the aforementioned problems by Robust Particle Swarm Optimization (RPSO) based run-length coding approach. Our solution surpasses other current and relevant existing algorithms based on experimental findings and assessments of different surveillance video sequences utilizing varied parameters. A massive collection of surveillance films was compressed at a 50% higher rate using the suggested approach than with existing methods.


2016 ◽  
pp. 1-10 ◽  
Author(s):  
Haoyang Lu ◽  
Lingwei Zhan ◽  
Yilu Liu ◽  
Wei Gao

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