Design of cascade P-P-FOPID controller based on marine predators algorithm for load frequency control of electric power systems

• Published in: Electrical engineering Vol. 107; no. 1; pp. 809 - 827
• Main Authors: Hussain, Jahanzeab, Zou, Runmin, Akhtar, Samina, Abouda, Khalid A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025; Springer Nature B.V
• Subjects: Algorithms; Business metrics; Comparative analysis; Control systems design; Controllers; Design; Economics and Management; Electric power; Electric power systems; Electrical Engineering; Electrical loads; Electrical Machines and Networks; Energy Policy; Engineering; Fractals; Frequency control; Frequency deviation; Investigations; Optimization algorithms; Optimization techniques; Original Paper; Parameters; Power Electronics; Predators; Robust control; Turbines; Fractional-order PID controller; Load frequency control; Marine predators algorithm; Cascade controller; Interconnected power systems
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-024-02551-0

As power network complexity increases, efficient control of frequency deviations and tie-line power fluctuations becomes crucial. Load frequency control (LFC) addresses these issues by managing generation-consumption mismatches. This paper introduces a unique P-P-FOPID cascade controller for LFC, combining a proportional controller with a fractional-order PID. The marine predators algorithm (MPA), known for its benefits like being parameter-less, derivative-free, user-friendly, flexible, and simple, is employed to optimize the controller’s parameters using the integral time absolute error criterion. Tested on three power systems, the proposed controller outperforms single-structure FOPID controller based on MPA and recent approaches in reducing ITAE, settling time, and frequency and tie-line power deviations. In comparative analysis, the proposed MPA-tuned P-P-FOPID controller achieves a 60% and 11% decrease in ITAE compared to the second-best DSA-optimized FOPI-FOPD controller for Systems 1 and 2, respectively, and a 25% decrease compared to the second-best MPA-tuned FOPID controller for System 3. Furthermore, the controller’s robustness against parametric uncertainties is confirmed through variations in fundamental parameters.