Impact of zero‑output crisp range recentering on the performance of FPIDD² controllers for multi-area LFC-AVR systems

Modern interconnected power systems with high penetration of renewable energy sources (RES) and large‑scale use of electric vehicles (EVs) experience recurring frequency and voltage disturbances. Accordingly, the main objective in this work is to overcome this limitation in a power system under coordinated load frequency control (LFC) and automatic voltage regulation (AVR), which requires highly accurate control strategies. Fuzzy logic‑based controllers are among the most promising approaches for disturbance rejection, control precision, system stability, and robust performance. However, their performance is often limited because the selection of crisp ranges (i.e., the universes of discourse of the fuzzy variables) is usually set heuristically. In this paper, the crisp output range of a Fuzzy Proportional Integral Derivative Double Derivative (FPIDD²) controller, which is based on a previous study, is reconfigured while maintaining the original rule base and membership function structure unchanged. This reconfiguration is presented to change the controller's response by recentering (shifting) the zero output membership function rightward, thereby improving control sensitivity and dynamic performance. The effectiveness of the proposed approach is validated via MATLAB simulation on a multi‑area interconnected power system under realistic operating conditions, including stochastic input fluctuations due to renewable energy source penetration and electric vehicle participation, as well as nonlinear constraints such as generation ramp‑rate limits and governor dead zones. Several metaheuristic optimizers, including Particle Swarm Optimization (PSO), Gorilla Troops Optimizer (GTO), and Marine Predators Algorithm (MPA), are used to further evaluate the robustness of the proposed method. The results demonstrate that optimized FLC configuration with modified crisp ranges significantly improves controller sensitivity, damping characteristics, and robustness. Consequently, the Integral of Time- Absolute Error (ITAE) is reduced by up to 69% compared to the original controller configuration.