Loss allocation based on active power flow tracing

2016 ◽  
Author(s):  
Adhip ◽  
D Thukaram ◽  
Gurunath Gurrala
Keyword(s):  
Power Flow ◽  
Active Power ◽  
Loss Allocation ◽  
Active Power Flow ◽  
Power Flow Tracing

Active Power Flow Control in Inverter using Sliding Mode Controller

2021 ◽  
Author(s):  
Arpit Sharma ◽  
Adarsh Kashyap ◽  
Ayushi Saxena ◽  
Arunprasad Govindharaj ◽  
A Ambikapathy
Keyword(s):  
Flow Control ◽  
Power Flow ◽  
Sliding Mode ◽  
Active Power ◽  
Sliding Mode Controller ◽  
Power Flow Control ◽  
Active Power Flow

Determination of Marginal Power Flows Based on an Adaptive Gradual Load Increase Trajectory

Vestnik MEI ◽  
2021 ◽  
pp. 20-30
Author(s):  
Natalya L. Batseva ◽  
◽  
Vasiliy A. Sukhorukov ◽  
Keyword(s):  
Power Flow ◽  
Active Power ◽  
Power Grids ◽  
Small Signal ◽  
Mode Change ◽  
Operation Speed ◽  
Load Increase ◽  
Active Power Flow ◽  
Change Vector ◽  
The Difference

The aim of the study is to develop a technique for searching an adaptive gradual load increase trajectory for power grids with a chain structure and to test this technique on the monitored 500 kV backbone grid sections. The technique for searching an adaptive gradual load increase trajectory was developed proceeding from the theoretical data about the chain structures of power grids and about the specific features of their operation modes. The voltage levels at the 500 kV backbone grid nodes and normalized phase angles across the ties included in the studied section and in the adjacent monitored sections are adopted as criteria for monitoring loss of small-signal aperiodic stability in the section under study. Special attention is paid to active power flows through the monitored adjacent sections with respect to the section under study. The proposed technique was tested on two monitored sections of the backbone 500 kV grid. The numerical analysis results have shown that under certain grid configuration and mode conditions, the marginal active power flow determined according to the proposed technique is either higher than the marginal active power flow determined using the mode change vector with the difference between the values from 54 MW to 319 MW, or lower than the marginal flow, with the difference between the values from 121 MW to 228 MW. It has been established that the difference between the values is caused by higher or lower loading of the monitored adjacent sections with respect to the section under study. Grid configuration and mode conditions has also been found in which the marginal active power flows determined according to the proposed technique and the mode change vector are almost identical with one another with the difference making about 15 MW. The subsequent algorithmic implementation of the procedure and development of the relevant software will make it possible to apply it to a larger number of monitored sections and to study various grid configuration and mode conditions for accumulating statistical data. If the software operation speed requirements in a close-to-real-time mode are satisfied, the software will be adapted to the Stability Margin Monitoring System software package. On the whole, the testing of the proposed technique for chain-shaped grids allowed us to conclude that the procedure can be used for searching an adaptive gradual loading trajectory and determining marginal active power flows in regard of small-signal aperiodic stability using the power system analysis model corresponding to the current grid configuration and mode conditions.

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