R() imitation learning for automatic generation control of interconnected power grids

Automatica ◽  
2012 ◽  
Vol 48 (9) ◽  
pp. 2130-2136 ◽  
Author(s):  
T. Yu ◽  
B. Zhou ◽  
K.W. Chan ◽  
Y. Yuan ◽  
B. Yang ◽  
...  
Keyword(s):  
Automatic Generation ◽  
Power Grids ◽  
Imitation Learning ◽  
Automatic Generation Control ◽  
Interconnected Power Grids ◽  
Generation Control

A FO-PID Controlled Automatic Generation Control of Multi Area Power Systems Tuned by Harmony Search

2020 ◽  
Vol 13 (1) ◽  
pp. 101-109
Author(s):  
Aurobindo Behera ◽  
Tapas K. Panigrahi ◽  
Arun K. Sahoo
Keyword(s):  
Power Systems ◽  
Harmony Search ◽  
Automatic Generation ◽  
System Stability ◽  
Automatic Generation Control ◽  
Similar System ◽  
Thermal Plant ◽  
Clear Idea ◽  
Generation Control ◽  
Fractional Controller

Background: Power system stability demands minimum variation in frequency, so that loadgeneration balance is maintained throughout the operation period. An Automatic Generation Control (AGC) monitors the frequency and varies the generation to maintain the balance. A system with multiple energy sources and use of a fractional controller for efficient control of stability is presented in the paper. At the outset a 2-area thermal system with governor dead band, generation rate constraint and boiler dynamics have been applied. Methods: A variation of load is deliberated for the study of the considered system with Harmony Search (HS) algorithm, applied for providing optimization of controller parameters. Integral Square Time Square Error (ISTSE) is chosen as objective function for handling the process of tuning controller parameters. : A study of similar system with various lately available techniques such as TLBO, hFA-PS and BFOA applied to PID, IDD and PIDD being compared to HS tuned fractional controller is presented under step and dynamic load change. The effort extended to a single area system with reheat thermal plant, hydel plant and a unit of wind plant is tested with the fractional controller scheme. Results: The simulation results provide a clear idea of the superiority of the combination of HS algorithm and FO-PID controller, under dynamically changing load. The variation of load is taken from 1% to 5% of the connected load. Conclusion: Finally, system robustness is shown by modifying essential factors by ± 30%.

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