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Fig.3 Simulink model for fuzzy controller

Figure 3 Simulink model for fuzzy controller

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Consider a single generating unit supplying load. A small load change will produce change in the frequency. When the load shifts from its pre defined value, a supplementary control retrieves frequency to specified value by reset (integral) controller as shown in the Fig.1. The integral control will make the frequency error zero by adjusting speed reference set point.
Consider a single generating unit supplying load. A small load change will produce change in the frequency. When the load shifts from its pre defined value, a supplementary control retrieves frequency to specified value by reset (integral) controller as shown in the Fig.1. The integral control will make the frequency error zero by adjusting speed reference set point.
Fig.2 Simulink model for PI controller In the proposed work, control of three thermal units are carried out using PI and Fuzzy controller. Each unit is taken for 2000MW .Load perturbation of 0.01 p.u MW is applied on the system. Various parameters used in the making of model are as in Table 1 and fuzzy inference table in Table 2.Model designed using SIMULINK are as shown in Fig.2 and 3.Type of FLC used is Mamdani-type which has IF-THEN Rules. Inputs are ACE and dACE.The Triangle membership functions are taken into account where NB,NS,ZZ,PS and PB imply negative big,negative small,zero,positive small and positive big respectively. S,M,B,VB,VVB denote smal ,medium ,big,very big and very very big respectively © International J ournal of Engineering Sciences & Research Technology [334]
Fig.2 Simulink model for PI controller In the proposed work, control of three thermal units are carried out using PI and Fuzzy controller. Each unit is taken for 2000MW .Load perturbation of 0.01 p.u MW is applied on the system. Various parameters used in the making of model are as in Table 1 and fuzzy inference table in Table 2.Model designed using SIMULINK are as shown in Fig.2 and 3.Type of FLC used is Mamdani-type which has IF-THEN Rules. Inputs are ACE and dACE.The Triangle membership functions are taken into account where NB,NS,ZZ,PS and PB imply negative big,negative small,zero,positive small and positive big respectively. S,M,B,VB,VVB denote smal ,medium ,big,very big and very very big respectively © International J ournal of Engineering Sciences & Research Technology [334]
© International J ournal of Engineering Sciences & Research Technology [335]
© International J ournal of Engineering Sciences & Research Technology [335]
Fuzzy control has emerged as as one of the most effective and fruitful of research mainly in industrial application because of increased reliability over conventional controllers.
Fuzzy control has emerged as as one of the most effective and fruitful of research mainly in industrial application because of increased reliability over conventional controllers.
Fig. 5: Frequency deviation for area 1(PI) Simulations run for PI and FLC for frequency and tie line power deviations are as in the graphs obtained
Fig. 5: Frequency deviation for area 1(PI) Simulations run for PI and FLC for frequency and tie line power deviations are as in the graphs obtained
Fig.10: Power deviation of area 2(PI) Fig.11: Frequency deviation of area 1 (Fuzzy)
Fig.10: Power deviation of area 2(PI) Fig.11: Frequency deviation of area 1 (Fuzzy)
© International J ournal of Engineering Sciences & Research Technology [339]
© International J ournal of Engineering Sciences & Research Technology [339]
Fig. 12: Frequency deviation of area 2 (Fuzzy)
Fig. 12: Frequency deviation of area 2 (Fuzzy)
Fig.13:.Frequency deviation of area 3(F uzzy)
Fig.13:.Frequency deviation of area 3(F uzzy)
Fig.15: Power deviation of area2 (Fuzzy)
Fig.15: Power deviation of area2 (Fuzzy)
CONCLUSION Fuzzy logic controller can be applied to multi area power system connected through tie lines.FLC can be use for non linear loads as well. MATLAB simulation results show that FLC produces better regulation than PI controller. Fuzzy logic controller minimised the deviations in frequency and tie line power. REFERENCES
CONCLUSION Fuzzy logic controller can be applied to multi area power system connected through tie lines.FLC can be use for non linear loads as well. MATLAB simulation results show that FLC produces better regulation than PI controller. Fuzzy logic controller minimised the deviations in frequency and tie line power. REFERENCES
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