Optimal AGC of a multi-area power system with parallel AC/DC tie lines using output vector feedback control strategy

2016 ◽  
Vol 81 ◽  
pp. 22-31 ◽  
Author(s):  
Gulshan Sharma ◽  
Ibraheem Nasiruddin ◽  
K.R. Niazi ◽  
R.C. Bansal
Keyword(s):  
Feedback Control ◽  
Power System ◽  
Control Strategy ◽  
Output Vector ◽  
Tie Lines ◽  
Feedback Control Strategy

scholarly journals Optimal Output Vector Feedback Control Strategy for Wind Power Systems

2015 ◽  
Vol 43 (8-10) ◽  
pp. 1122-1132
Author(s):  
Shahida Khatoon ◽  
Ibraheem Nasiruddin ◽  
Reshma Ehtesham ◽  
Ramesh C. Bansal
Keyword(s):  
Feedback Control ◽  
Power Systems ◽  
Wind Power ◽  
Control Strategy ◽  
Output Vector ◽  
Optimal Output ◽  
Wind Power Systems ◽  
Feedback Control Strategy

scholarly journals An Optimal Feedback Control Strategy for Nonlinear, Distributed-Parameter Processes

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 758 ◽  
Author(s):  
Debaprasad Dutta ◽  
Simant Ranjan Upreti
Keyword(s):  
Feedback Control ◽  
Oil Recovery ◽  
Control Strategy ◽  
Moving Boundary ◽  
State Feedback Control ◽  
Optimal Feedback Control ◽  
Distributed Parameter ◽  
Optimal State ◽  
Non Linear ◽  
Feedback Control Strategy

In this work, an optimal state feedback control strategy is proposed for non-linear, distributed-parameter processes. For different values of a given parameter susceptible to upsets, the strategy involves off-line computation of a repository of optimal open-loop states and gains needed for the feedback adjustment of control. A gain is determined by minimizing the perturbation of the objective functional about the new optimal state and control corresponding to a process upset. When an upset is encountered in a running process, the repository is utilized to obtain the control adjustment required to steer the process to the new optimal state. The strategy is successfully applied to a highly non-linear, gas-based heavy oil recovery process controlled by the gas temperature with the state depending non-linearly on time and two spatial directions inside a moving boundary, and subject to pressure upsets. The results demonstrate that when the process has a pressure upset, the proposed strategy is able to determine control adjustments with negligible time delays and to navigate the process to the new optimal state.

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