Dynamic load frequency control in Power systems using a hybrid simulated annealing based Quadratic Interpolation Optimizer

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Oct. 29, 2024

Ensuring the stability and reliability of modern power systems is increasingly challenging due to growing integration renewable energy sources dynamic nature load demands. Traditional proportional-integral-derivative (PID) controllers, while widely used, often fall short in effectively managing these complexities. This paper introduces a novel approach frequency control (LFC) by proposing filtered PID (PID-F) controller optimized through hybrid simulated annealing based quadratic interpolation optimizer (hSA-QIO). The hSA-QIO uniquely combines local search capabilities (SA) with global optimization strengths (QIO), providing robust efficient solution for LFC challenges. key contributions this study include development application hSA-QIO, which significantly enhances performance PID-F controller. proposed was evaluated on unimodal, multimodal, low-dimensional benchmark functions, demonstrate its robustness effectiveness across diverse scenarios. results showed significant improvements quality compared original QIO, lower objective function values faster convergence. Applied two-area interconnected system photovoltaic-thermal generation, hSA-QIO-tuned achieved substantial reduction integral time-weighted absolute error 23.4%, from 1.1396 0.87412. Additionally, reduced settling time deviations Area 1 9.9%, 1.0574 s 0.96191 s, decreased overshoot 8.8%. In 2, improved 0.89209 4.8%. also demonstrated superior tie-line regulation, achieving immediate response minimal overshoot.

Language: Английский

Multi-strategy enhanced artificial rabbit optimization algorithm for solving engineering optimization problems

Evolutionary Intelligence, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 9, 2025

Language: Английский

HIL co-simulation of an optimal hybrid fractional-order type-2 fuzzy PID regulator based on dSPACE for quadruple tank system

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 4, 2025

Accurate regulation of the liquid level in a quadruple tank system (QTS) is not easy and imposes higher requirements on control strategies, so design controllers these systems challenging due to difficulty dynamic analysis its nonlinear characteristics parametric uncertainties. To overcome problems increase robustness pump coefficients, this article proposes investigates use an optimal hybrid fractional-order type-2 fuzzy-PID (OH-FO-T2F-PID) regulator using combination two bio-inspired evolutionary optimizers, namely augmented grey wolf optimizer cuckoo search optimizer, which gives rise new A-GWOCS algorithm. This mechanism was chosen facilitate convergence water liquids tanks as quickly possible corresponding required values. In addition, collaborative optimization technique with several objectives used adjust parameters. The capability efficiency suggested first investigated through computer simulation results then confirmed by real-time experimental QTS based dSPACE 1104 computation engine. findings showed that OH-FO-T2F-PID significantly outperformed both optimized ADRC OH-FO-T1F-PID regulators. Specifically, it reduced rising time 17.02% 95.21%, respectively, settling 25.13% 74.28%. Additionally, designed successfully eliminated steady-state error overshoot, enabling precise QTS, maintenance at desired set point under wide range working situations. recommended also studied considering - 50% disturbance parameters, less susceptible variations

Language: Английский