@article{Ali_Siswanto_Baehaqi_2024, title={Flower Polination Algorithm Sebagai Optimalisasi LFC Pada Hybrid Pembangkit Wind-Diesel}, volume={5}, url={http://journal.fortei7.org/index.php/fortech/article/view/608}, DOI={10.56795/fortech.v5i1.5106}, abstractNote={<p><em>As input power, the amount of wind and wind speed greatly influences the wind power generation system. A combination of a wind-diesel power generation system is needed to obtain optimal power quality. A hybrid system is a controlled network of multiple renewable energy generators such as wind turbines, solar cells, micro-hydro, and so on. Gain settings that are not optimal and the time constant is small in Load Frequency Control (LFC), causing its ability to be weak (weak line). In practice, the wind-diesel system is controlled with a PID controller. Setting the gain value of the PID is still in the conventional method, so it is difficult to get the optimal value. In this research, a control design was implemented using the Smart Method to find the optimum value of the Proportional Integral Derivative (PID) based on the FPA (Flower Pollination Algorithm). For comparison, methods were used without control methods, conventional PID methods, PID Auto tuning methods, and FPA (Flower Pollination Algorithm) methods. Wind-diesel modeling uses transfer function diagrams of wind and diesel turbines. This study compares several uncontrolled methods and conventional PID, PID-Auto tuning, and PID-FPA. The results of the research that has been carried out show that the smallest undershoot is -1.187.10<sup>-04</sup> for PID-FPA, the smallest overshot is 0 for PID-FPA, and the fastest settling time is 9.827 s for PID-FPA. So it can be concluded that PID-FPA is the best controller in this research. This research can later be continued using other artificial intelligence methods.</em></p>}, number={1}, journal={Jurnal FORTECH}, author={Ali, Machrus and Siswanto, Agus and Baehaqi, Mudofar}, year={2024}, month={May}, pages={41–47} }