JEE_V10_N1_RP5
Comparative Performance Analysis of PID, Fuzzy-Mamdani, Fuzzy-Sugeno and ANFIS for Automatic Generation Control of Multi-Area Power System
Umesh Kumar Singh
L.B. Prasad
Journal on Electrical Engineering
2230 – 7176
10
1
26
34
Automatic Generation Control (AGC), Adaptive Neuro Fuzzy Inference System (ANFIS), Generation Rate Constraint (GRC), Fuzzy Logic Controller (FLC)
Automatic Generation Control (AGC) insures a sufficient, reliable and good quality of power to the consumer. It insures that the amount of power available should be sufficient and the frequency deviation is within the rated limit. Any mismatch between generation and demand causes deviation in the system frequency from its nominal value. If load is continuously changing in nature, the frequency deviation goes on increasing, which may lead to system collapse. So in order to maintain the stability in power generation, a very fast and accurate controller is needed to maintain the nominal system frequency. In this paper, Proportional- Integral-Derivative controller and artificial intelligent controllers such as Fuzzy-Mamdani, Fuzzy-Sugeno and Adaptive Neuro Fuzzy Inference System (ANFIS) has been presented for AGC of fourarea (Thermal-Nuclear-Thermal-Hydro) interconnected power system including Generation Rate Constraint (GRC).
July - September 2016
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