Abstract
The Load Frequency Control problem has been a major subject in electrical power system design/operation and is becoming more significant recently with increasing size, changing structure and complexity in interconnected power systems. In practice LFC systems use simple proportional-integral controllers. However, since the PI control parameters are usually tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamic performance for a wide range of operation conditions and various load changes scenarios in multi-area power system. For this problem, in this paper quantitative feedback theory method is used for LFC control in multi-area power system with system parametric uncertainties. The system parametric uncertainties are obtained by changing parameters by 40% simultaneously from their typical values. A two-area power system example with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of proposed method, a classical I type controller optimized by genetic algorithm is designed for LFC for comparison with QFT. The validity of the proposed method was confirmed by comparing it results with those of traditional methods (I controller optimized by genetic algorithm) has been confirmed.
Highlights
For large-scale power systems, which normally consist of interconnected control area, Load Frequency Control (LFC) is important to keep the system frequency and the inter-area tie power as close as possible the scheduled values
Several strategies for Load Frequency Control of power systems have been proposed by researchers over the past decades[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17]
To compare and show effectiveness of proposed method, a classical I type controller optimized by genetic algorithm (GA) is designed for LFC
Summary
For large-scale power systems, which normally consist of interconnected control area, Load Frequency Control (LFC) is important to keep the system frequency and the inter-area tie power as close as possible the scheduled values. Several strategies for Load Frequency Control of power systems have been proposed by researchers over the past decades[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17] This extensive research is due to fact that LFC constitutes an important function on power system operation where the main objective is to regulate the output power of each generator at prescribed levels while keeping the frequency fluctuations within pre-defined limits. The applications of artificial neural networks, genetic algorithms, fuzzy logic and optimal control to LFC have been reported in[15,16,17]
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