Discrete-mode automatic generation control of a two-area reheat thermal system with new area control error

1989 ◽  
Vol 4 (2) ◽  
pp. 730-738 ◽  
Author(s):  
M.L. Kothari ◽  
J. Nanda ◽  
D.P. Kothari ◽  
D. Das
Keyword(s):  
Automatic Generation ◽  
Automatic Generation Control ◽  
Thermal System ◽  
Control Error ◽  
Discrete Mode ◽  
Area Control Error ◽  
Generation Control

scholarly journals Meta-Heuristic Algorithm Optimized Fuzzy PID Controlled AGC of Three Area Power System

2019 ◽  
Vol 9 (2) ◽  
pp. 2493-2499
Keyword(s):  
Control Mechanism ◽  
Automatic Generation ◽  
Control Area ◽  
Automatic Generation Control ◽  
Primary Control ◽  
Fuzzy Pid ◽  
Control Error ◽  
Area Control Error ◽  
Generation Control ◽  
Tie Line

The problem of automatic generation control (AGC) is a major concern in power utilities; it plays a major role of the complicated structure and dimension of the multi-area systems. Automatic Generation Control's main intention in the multi-area system is to maintain the frequency of each control area and remain the tie-line power flows within the many defined tolerance limits by modifying the Automatic Generation Control generators’ actual power outputs to accommodate the changing load requirements. Frequency control is accomplished through the primary control mechanism or the governor control mechanism. But the Area Control Error (ACE) always present in the system. The secondary controllers are surmounting this ACE to zero. The design tunes the controllers to enhance the better dynamic performance and stability of these eccentric conditions. The goal of this work is to diminish area control error, settle time, under-shoots and over-shoots of frequency divergence and net interchange tie-line error. Generally the gain values of the PID Control parameters obtain by tribulation and error technique and it need additional computation time. To reduce this obscurity of tuning of PID gains Evolutionary algorithm approach can be habituated to optimize the PID gains. Fuzzy – PID have been employed with different objective to enhance the efficient optimal solutions to the three area system. In this proposed study, GWO technique used to maximize Fuzzy-based PID controller's Proportional, Integral and Derivative gains in Three Area System.

Research of Target-Controllable Optimal Dispatch for AGC Regulation Capacity

2013 ◽  
Vol 805-806 ◽  
pp. 472-476
Author(s):  
Hong Qian ◽  
Yi Ming Yao ◽  
Min Rui Fei ◽  
Liang Deng
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Control Error ◽  
Optimal Dispatch ◽  
Area Control Error ◽  
Control Factors ◽  
Optimal Technology ◽  
Generation Control

In order to implement the target-controllability and the optimal dispatch of automatic generation control (AGC), a new dispatch method of AGC regulation capacity based on the multi-target optimal technology and the genetic algorithm (GA) is proposed. In the algorithm, the control factors are introduced by applying multi-target mathematical model. So it can control every object importance artificially according to the region of the area control error (ACE) by operators. The genetic algorithm is used to get the optimal results. Finally an example is given to demonstrate the validity of the proposed method.

scholarly journals AGC of multi area power system based PSO under deregulated conditions

2018 ◽  
Vol 7 (3) ◽  
pp. 1446
Author(s):  
Ahmed Jasim Sultan ◽  
Falah Noori Saeed
Keyword(s):  
Power Flow ◽  
Optimization Technique ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
System Response ◽  
Area Control Error ◽  
Particle Swarm Optimization Technique ◽  
Power Flow Controller ◽  
Generation Control ◽  
Tie Line

In This research PIDF (Proportional Integral Derivative with Filter) is suggested to control the ACE (area control error) signal of automatic generation control circuit (AGC) for two-area multi units system under deregulated conditions, each area consist of two thermal reheat units with physical GRC (generating rate constrain). The parameters of the PIDF controller are tuned using PSO (particle swarm optimization) technique. To improve the system performance, Redox Flow Batteries (RFB) is presented in one area and one of FACTS components IPFC (Inter Line Power Flow Controller) is installed in tie line. The performance of the proposed controller is assessed under different working conditions of deregulated power market. Finally, a comparison will be made on the system response when testing with varying the load conditions and system parameter through MATLAB environment 2015Rb.  

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