In multi area electric power systems if a large load is suddenly connected (or disconnected) to the system, or if a generating unit is suddenly disconnected by the protection equipment, there will be a long-term distortion in the power balance between that delivered by the turbines and that consumed by the loads. This imbalance is initially covered from the kinetic energy of rotating rotors of turbines, generators and motors and, as a result, the frequency in the system will change. Therefore The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, numerous techniques have been proposed in literatures. In this paper a PI type controller is considered for LFC problem. The parameters of the proposed PI controller are tuned using Simulated Annealing (SA) optimization method. A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of the proposed method, a PI type controller optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PI controller. The simulation results visibly show the validity of SA-PI controller in comparison with the GA-PI controller.
[1]
Allen J. Wood,et al.
Power Generation, Operation, and Control
,
1984
.
[2]
Ertuğrul Çam,et al.
Fuzzy logic controller in interconnected electrical power systems for load-frequency control
,
2005
.
[3]
Randy L. Haupt,et al.
Practical Genetic Algorithms
,
1998
.
[4]
Wen Tan,et al.
Unified Tuning of PID Load Frequency Controller for Power Systems via IMC
,
2010,
IEEE Transactions on Power Systems.
[5]
Shengwei Mei,et al.
Optimal load-frequency control in restructured power systems
,
2003
.
[6]
Mohamed Zribi,et al.
Adaptive decentralized load frequency control of multi-area power systems
,
2005
.
[7]
Seyed Abbas Taher,et al.
Robust Decentralized Load Frequency Control Using Multi Variable QFT Method in Deregulated Power Systems
,
2008
.
[8]
P. Sangameswara Raju,et al.
DEREGULATED POWER SYSTEM
,
2011
.
[9]
Ali Feliachi,et al.
Robust load frequency control using genetic algorithms and linear matrix inequalities
,
2003
.
[10]
Om P. Malik,et al.
Robust decentralized neural networks based LFC in a deregulated power system
,
2007
.
[11]
Nedjeljko Perić,et al.
Sliding mode based load-frequency control in power systems
,
2010
.