scholarly journals THE DIGITALIZATION OF SUBSTATIONS BY CREATING A 6-35 kV SWITCHING DEVICESCONTROL SYSTEM FROM THE AUTOMATED WORKPLACE

Author(s):  
Georgi M. Mikheev ◽  
Ayrat G. Ziganshin

The control system of high-voltage switches at one of the substations of the branch of JSC «Grid Company» Buinskie Power Networks is presented in the work. The block control circuit of switching devices from the automated workplace is described. Its specific blocks with the help of which the whole process of switching of high-voltage switches in the switchgear – 10, 35 kV is performed are provided. An explanation of the collection and transfer of information from intelligent electronic devices to the switchgear drive, transmission of control commands, protocol conversion and data exchange with higher levels of automated systems is given. Advantages of the remote control system for 6-35 kV electrical apparatus are shown on the example of the 110/35/10 kV «Verkhny Uslon» substation of the Tatenergo system. The system of remote control of switchgear during its repair and in case of other emergency situations is opened on the example of one of the substations 110/35/10 kV of the Republic of Tatarstan. There are schemes KRUN-10, KRUN-35 kV with an illustration of the positions of electrical apparatus, combined with video surveillance of the state of the switch of a certain cell and the position of the earthing switch of a separate switching device.

Author(s):  
Sajad Shahsavari ◽  
Mohammed Rabah ◽  
Eero Immonen ◽  
Mohammad-Hashem Haghbayan ◽  
Juha Plosila

We propose an adaptive run-time failure recovery control system for quadcopter drones, based on remote real-time processing of measurement data streams. Particularly, the measured RPM values of the quadcopter motors are transmitted to a remote machine which hosts failure detection algorithms and performs recovery procedure. The proposed control system consists of three distinct parts: (1) A set of computationally simple PID controllers locally onboard the drone, (2) a set of computationally more demanding remotely hosted algorithms for real-time drone state detection, and (3) a digital twin co-execution software platform — the ModelConductor-eXtended — for two-way signal data exchange between the former two. The local on-board control system is responsible for maneuvering the drone in all conditions: path tracking under normal operation and safe landing in a failure state. The remote control system, on the other hand, is responsible for detecting the state of the drone and communicating the corresponding control commands and controller parameters to the drone in real time. The proposed control system concept is demonstrated via simulations in which a drone is represented by the widely studied Quad-Sim six degrees-of-freedom Simulink model. Results show that the trained failure detection binary classifier achieves a high level of performance with F1-score of 96.03%. Additionally, time analysis shows that the proposed remote control system, with average execution time of 0.49 milliseconds and total latency of 6.92 milliseconds in two-way data communication link, meets the real-time constraints of the problem. The potential practical applications for the presented approach are in drone operation in complex environments such as factories (indoor) or forests (outdoor).


Author(s):  
Liu Shi-nian ◽  
Hu Shan ◽  
Ma Cun-ren ◽  
Xu He-zhang ◽  
Su Wei ◽  
...  

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