Abstract

The perception of automatic generation control (AGC) has a massive part in delivering eminence power in an interrelated structure. To acquire eminence power by monitoring the fluctuations of frequency and tie-link power, an appropriate controller strategy is essential. This work explores AGC learning under the traditional situation. In this study, we employ a cascade controller with proportional amalgamation with a tilt-integral-derivative with a filter (TIDN) and fractional order integral-derivative (FOID), named TIDN-FOID. In order to acquire the controller’s attributes, a meta-heuristic optimization algorithm spotted hyena optimizer (SHO) is employed. Several investigations express the excellency of the TIDN-FOID controller over other controllers from outlook regarding the lessened level of peak_overshoot, peak_undershoot, and settling_time for the considered structure. The structure comprises thermal, biodiesel units in area 1, thermal, and geothermal units in area-2, and hydrothermal units in area-3. Both biodiesel and GPP have a better effect on system dynamics even in the presence of time delay. Action in the redox flow battery is also examined, providing a noteworthy outcome. Eigenvalue assessment is carried out to comment on the stability of the system. TIDN-FOID parameter values at nominal conditions are appropriate for a higher disturbance value without the need for optimization.

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