<![CDATA[Micro-hydro Power Plant is a small-scale power plant. Micro-hydro plants are built with enough water potential to generate electrical energy. A common problem with micro-hydro generating systems is that the output of the generator is not constant. This is caused by changes in connected loads. Thus causing frequent fluctuations in the frequency and voltage of the system that can cause damage to electrical equipment. Because it is used Load Frequency Control (LFC) to control the frequency can be more stable. To obtain optimal control parameters on micro hydropower systems used by Artificial Intelligence (AI) is Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS data is retrieved from training data of PID controllers tuned using Ant Colony Optimization (ACO) and Bat Algorithm (BA). This study compared uncontrolled methods, PID-ZN control methods, PID-ACO method, PID-BA, PID-ACO-ANFIS, and PID-BA-ANFIS obtained the best control method. The result of this research is the control method of PID-ACO-ANFIS is the best control method with overshoot 0.00 and the fastest settling time is 0.00. The results showed that the smallest overshoot (0) in the PID-ACO-ANFIS model, the smallest undershoots (1,12x10-5) in PID-ACO-ANFIS and the fastest settling time (3.77 seconds) in the starting also at PID-ACO-ANFIS. The results of this study will be tried bengan other methods, which results may be better]]>
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