Frequency stabilization for interconnected renewable based power system using cascaded model predictive controller with fractional order PID controller

Abstract

In today's electrical grid, frequency cannot be ignored. The proliferation of renewable energy sources into a power system degrades its frequency; hence, the need for frequency regulation has been increased as a result. The second major factor is the perturbation in the load that originates the frequency fluctuation which needs to be suppressed in minimum time to avoid any system collapse. The designing of an optimal controller is indispensable because of increasing power system complexity. In order to maintain the stability of the power system, this paper presents the cascaded design of the model predictive controller with fractional order PID controller (MPC‐FOPIDN) to mitigate the frequency oscillations due to disruption in load. The combination of the predictive capabilities of model predictive control (MPC) and fractional order control enhances control abilities, making it an optimal control strategy for load frequency control (LFC). The grasshopper optimization algorithm (GOA) is applied to obtain optimal gains values for the FOPID controller. The efficacy of the controller has effectively mitigated frequency fluctuations caused by a change in demand or any uncertainty in the power system.

Automatic Generation Control of a Hybrid PV-Reheat Thermal Power System Using RIME Algorithm

“…Various optimization algorithms have been explored in these studies, each with their unique inspiration. For instance, the grasshopper optimization algorithm (GOA) [12] imitates the swarming behavior of grasshoppers, while the dragonfly search algorithm (DSA) [13]- [15] replicates the foraging behavior of dragonflies. Additionally, the jellyfish search optimizer (JSO) [10] simulates the pulsating motion of jellyfish.…”