PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 4, 2026Journal of Renewable and Sustainable Energy1 citations

Fractal-optimized adaptive control for robust frequency regulation in renewable-rich power systems

View Full Paper
MYMuhammad Zubair YameenZLZhigang LuKBKaneez Bano

Key Points

  • This research aims to improve frequency regulation in power systems with high penetration of variable renewable energy sources.
  • Introduced a Double-Layer Fractional-Order Cascaded Controller (DL-FOCC) for frequency regulation.
  • Developed a Fractal-Firefly-Whale Optimization (F-FWO) algorithm for parameter tuning.
  • Conducted MATLAB/Simulink simulations on a dual-area hybrid power system.
  • Compared performance against ten existing controllers to evaluate effectiveness.
  • Achieved significant improvements in Integral of Time-weighted Absolute Error and transient frequency deviations.
  • Demonstrated a 30% reduction in computing costs with the F-FWO method.
  • Confirmed the DL-FOCC's superior performance compared to state-of-the-art controllers.

Abstract

The incorporation of high-penetration Variable Renewable Energy (VRE) sources results in considerable intermittency and inertia reduction, hence undermining the effectiveness of traditional Load Frequency Control (LFC). This research offers a novel framework based on a Double-Layer Fractional-Order Cascaded Controller (DL-FOCC) to achieve strong, flexible, and computationally efficient frequency regulation. The DL-FOCC's hierarchical cascaded architecture separates setpoint governance from dynamic disturbance rejection. It also has a real-time adaptive mechanism that changes its fractional-orders based on the Area Control Error. A new algorithm called Fractal-Firefly-Whale Optimization (F-FWO) is also proposed to optimally tune the parameters of this complex controller. The suggested F-FWO-DL-FOCC architecture is thoroughly tested using detailed MATLAB/Simulink simulations on a genuine dual-area hybrid power system subjected to strong and simultaneous disturbances. Comparative analyses against ten state-of-the-art controllers confirm the framework's superiority, demonstrating substantial improvements in key performance metrics such as the Integral of Time-weighted Absolute Error and transient frequency deviations. Furthermore, the F-FWO method itself cuts computing costs by about 30%, highlighting the framework's practicality for real-time applications. This work successfully connects the need for good performance in VRE-rich contexts with the need for efficient computing for practical LFC implementation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Yameen et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd6ed48f933b5eed9c6dhttps://doi.org/10.1063/5.0321873
Ask AI
Helpful
Bookmark
Share
View Full Paper