Application of Energy Storage-PID For Load Frequency Control In Micro-hydro Using Flower Pollination Algorithm

To get optimal SMES and CES performance, optimal parameter tuning is needed. This research uses an artificial intelligence method based on the Flower Pollination Algorithm (FPA) for the optimization of SMEs and CES parameters. The FPA algorithm performs computations based on objective functions, namely optimizing Integral Time Absolute Error (ITAE). To test the reliability of micro-hydro, a disturbance is given in the form of load changes, then analyzed the governor response and micro-hydro frequency. In addition, in this study, a combination of SMES and CES control system scenarios with conventional PID controllers was used. From the results of the correct tuning of the SMES and CES parameters, the optimal micro-hydro performance was obtained. This is shown by the overshoot governor response and the minimum frequency and faster settling time using the methods proposed by SMEs and CES.