# Performance analysis of FL, PI and PID controller for AGC and AVR of a Two-Area Power System

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2 International Journal of Scientific and Research Publications, Volume 5, Issue 1, January changing a load reference set point input. A case study is presented by considering a two area power system [4]. (iii) Defuzzification module (Defuzzifier) 2.1. Area control error Area Control Error is defined by, ACE i = CP ij + B i *C f (1) Where, i -control area for which ACE is being measured CP ij -power interchange in areas i and j B i - control area frequency bias coefficient C f - deviation in frequency The ACE is an error signal consisting of two factors. 1 st factor represents the error in the scheduled tie flows. The 2 nd factor is inter-area assistance in generation from control area to prevent large deviation of interconnection frequency. ACE represents the generation versus load mismatch for the control area. The ACE indicates instant at which the total generation must be lowered or raised in a control area. A general criterion can be given about which AGC is considered good. Since ACE is directly influenced by random load variations, this criterion can be treated statically by specifying that the standard deviation of ACE should be small and ACE should not be allowed to drift. This means that the integral of ACE over appropriate time should be small. A drift in ACE has the cumulative effect of creating system time errors or inadvertent interchange errors [5]. Fig.1: Two area interconnected power system III. FUZZY LOGIC CONTROLLER Conventional control methods cannot provide desired results because power system dynamic characteristics are complex and variable. Advanced controller can be replaced with conventional controller to get fast and good dynamic response in load frequency problems. Fuzzy Logic Controller (FLC) as shown in Fig.(2) can be more useful in solving large scale of controlling problems with respect to conventional controller which are slower. Fuzzy logic controller is designed to minimize fluctuation on system outputs. There are many studies on power system with fuzzy logic controller. There are three principal elements to a fuzzy logic controller: (i) Fuzzification module (Fuzzifer) (ii) Rule base and Inference engine Fig.2: Fuzzy logic controller Fuzzy control is based on a logical system called fuzzy logic. It is much close in spirit to human thinking than conventional logical systems. Complexity and Multi-variable nature of power system limits the conventional control method, to provide satisfactory solutions. The FLC is to handle the reliability, robustness and nonlinearities associated with power system controls. Due to this fuzzy logic controller becomes adaptive and nonlinear in nature having a robust performance under parameter variations with the ability to get desired control actions for complex uncertainty, and nonlinear systems without their mathematical models and parameter estimation [3,5,10]. The error e and change in error ( e) are inputs to the fuzzy logic controller. These two inputs signals are converted to fuzzy numbers first in fuzzifier using seven membership functions. The fuzzy rules are interpreted as if ACE is NB and d(ace)/dt is NS then the output is PM. The Triangular membership functions are used for both the inputs and output signals. The rule table for fuzzy with AGC and AVR is as shown in Table 1 and Table Membership functions for AGC for the fuzzy variable of the proposed FLC Fuzzy control rules are constructed by using the control experience of operator having experiences about automatic generation control of the interconnected power system. There are two controllers, fuzzy ACE1 and fuzzy ACE2 as shown in Fig.3 and Fig.4. Each of the controllers has the Negative Big NB, Negative Medium NM, Negative Small NS, Zero ZE, Positive Big PB, Positive Medium PM, Positive Small PS for both the change in area control error d(ace)/dt and area control error ACE [5]. The rules are interpreted as follows, if ACE is NB and d(ace)/dt is NS then the output is PB. The triangular membership functions are used for both the inputs and output. The Defuzzification method employed is the center of area method [8]. The membership functions for input and output are shown in Fig.3, 4 and Fig 5. Rule viewer and Surface viewer of AGC block in FLC is shown in Fig.6 and Fig.7.

3 International Journal of Scientific and Research Publications, Volume 5, Issue 1, January Fig 3: Membership function editor for input1 of FLC Fig 5: Membership function editor for output of FLC Fig 6: Rule viewer of AGC block in FLC Fig 4: Membership function editor for input2 of FLC Fig 7: Surface viewer of AGC block in FLC

4 International Journal of Scientific and Research Publications, Volume 5, Issue 1, January TABLE 1: FUZZY RULE TABLE FOR AGC TABLE 2: FUZZY RULE TABLE FOR AVR Fig.8: AGC and AVR interconnection for single area using fuzzy logic controller IV. SIMULATION AND RESULTS Testing was done on each of the individual blocks of the AGC system and AVR system. The design and simulation of problem is done in MATLAB Simulink environment. The following simulations were performed in order to investigate the performance of the proposed fuzzy logic controller over the conventional integral controller. The simulation block diagram for AGC and AVR interconnection for single area using fuzzy logic controller is shown Fig.8 and the AGC and AVR for two areas interconnected using fuzzy logic controller is shown Fig.9. The change in frequency v/s time and change in voltage v/s time for single area is shown in Fig.10 and 11 respectively. Frequency deviation of AGC_AVR in area-1 using FLC, PI and PID in two area interconnected system is shown in Fig.12. The Voltage response of AVR for two area using FLC and PID are shown in Fig.13 and 14. Comparison of dynamic responses of FLC, PI and PID are shown in Table 3. The various assumptions used for AGC, AVR, PI and PID simulation are shown in Table 4, 5 and 6 respectively. Fig.9: AGC and AVR for two areas interconnected using fuzzy logic controller.

5 International Journal of Scientific and Research Publications, Volume 5, Issue 1, January Fig.10: Frequency deviation of AGC using FLC in single area. Fig.12: Frequency deviation of AGC_AVR in area-1 using FLC, PI and PID in two area interconnected system. Fig.11: Voltage response of AVR using FLC in single area. TABLE 3: COMPARISON OF DYNAMIC RESPONSES OF Fig.13: Voltage response of AVR using FLC in two area interconnected system. CONTROLL ER FREQUENCY DEVIATION SETTLING TIME (SEC) MAXIMUM OVERSHOOT AGC AVR AGC AVR FLC * PID * Fig.14: Voltage response of AVR using PID in two area interconnected system. PI * PI, PID AND FLC The assumptions used for AGC, AVR and PID simulations are shown in Table 4,5 and 6 respectively.

7 International Journal of Scientific and Research Publications, Volume 5, Issue 1, January

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