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Figure from:Dingo optimization algorithm for designing power system stabilizer

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Figure 2. Block diagram of proposed PSS where Aw(t) is the deviation of the rotor speed following the disturbance. Ts is the time of simulation. RESULTS AND DISCUSSION MATLAB 2015 software is used to perform simulations. Ability to determine performance, the DOA method is compared with the WOA and GOA methods. The convergence curve for comparing the DOA method with the WAO and GOA methods can be seen in Figure 3. The curve uses a time value of 0 at 30 seconds. The single machine system used in this article is the Heffron-Philips model. Figure 2 includes the popular Heffron-Philips model variables, namely K, — Kg. w and 6 are the rotor speed and the rotor angle. The damping factor are D. K, and T, are DC gain and time constant of AVR. A single machine installed with DOA-based PSS can be seen in Figure 2. DOA optimizes PSS parameters which include gain, washout and lead lag. The number of optimized PSS parameters is 7. PSS parameters are optimized using the integral of time multiplied absolute error (ITAE) with the (4):

Figure 2 Block diagram of proposed PSS where Aw(t) is the deviation of the rotor speed following the disturbance. Ts is the time of simulation. RESULTS AND DISCUSSION MATLAB 2015 software is used to perform simulations. Ability to determine performance, the DOA method is compared with the WOA and GOA methods. The convergence curve for comparing the DOA method with the WAO and GOA methods can be seen in Figure 3. The curve uses a time value of 0 at 30 seconds. The single machine system used in this article is the Heffron-Philips model. Figure 2 includes the popular Heffron-Philips model variables, namely K, — Kg. w and 6 are the rotor speed and the rotor angle. The damping factor are D. K, and T, are DC gain and time constant of AVR. A single machine installed with DOA-based PSS can be seen in Figure 2. DOA optimizes PSS parameters which include gain, washout and lead lag. The number of optimized PSS parameters is 7. PSS parameters are optimized using the integral of time multiplied absolute error (ITAE) with the (4):

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Figure 3. The convergence curve same value as the GOA method, which is -0.0257. This value is the best speed undershoot value in the first test The undershoot speed value of the DOA method is 28.4% better than the lead-lag method and 5.83% than th WOA method. Figure 4 is the graphic result of the speed in test 1. Meanwhile, the best under shoot value fron the rotor angle in test 1 is the DOA method. Figure 5 is a comparison graph of the angle rotor in test 1.
Figure 3. The convergence curve same value as the GOA method, which is -0.0257. This value is the best speed undershoot value in the first test The undershoot speed value of the DOA method is 28.4% better than the lead-lag method and 5.83% than th WOA method. Figure 4 is the graphic result of the speed in test 1. Meanwhile, the best under shoot value fron the rotor angle in test 1 is the DOA method. Figure 5 is a comparison graph of the angle rotor in test 1.
Figure 5. Rotor angle in 20% load
Figure 5. Rotor angle in 20% load
Figure 6. Speed in 50% load Figure 7. Rotor angle in 50% load speed in test 3. Meanwhile, the best under shoot value of the rotor angle in test 3 is the GOA method. Figure ‘ is a comparison graph of the rotor angle in test 3. Table 3. Test 3: 100% of load
Figure 6. Speed in 50% load Figure 7. Rotor angle in 50% load speed in test 3. Meanwhile, the best under shoot value of the rotor angle in test 3 is the GOA method. Figure ‘ is a comparison graph of the rotor angle in test 3. Table 3. Test 3: 100% of load
Figure 9. Rotor angle in 100% load
Figure 9. Rotor angle in 100% load