ArticleScientific reports2025
Optimized cascaded regulation strategy for robust automatic generation control in renewable-integrated power networks.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A Novel Algebraic Saturation-Based PID Controller Optimized by Animated Oat Algorithm for Ultra-Fast Dynamic Response of Automatic Voltage Regulation.Biomimetics (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ensuring stability of both voltage and frequency in linked power networks (LPNs) is a critical challenge, primarily due to their nonlinear dynamics and load variability. Due to the high penetration of intermittent renewable energy sources, traditional Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) schemes often struggle to ensure fast, robust, and coordinated regulation in modern multi-area hybrid grids. To address these limitations, this research introduces a novel cascaded control architecture developed for Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) within a three-area hybrid LPN comprising thermal, wind, hydro, photovoltaic, and diesel generation sources. The proposed framework integrates three cascaded regulators: FOPI, TIDμ, and PIDA. Combining strengths of the three controllers provides better transient response, higher robustness against system uncertainties, and Improved steady-state accuracy. Also, for better performance, the parameters of the proposed controller are optimally selected using a recent developed optimization algorithm called Differential Creative Search (DCS). All simulations were carried out in MATLAB/Simulink environment. The obtained results are comprehensively compared to results obtained by utilizing other algorithms, Artificial Ecosystem-based Optimization (AEO), Dandelion Optimizer (DO), and the Runge-Kutta Optimization (RUN) algorithm. Results indicate that the DCS algorithm achieved the superior outcome, attaining the lowest objective function value of 0.0507, surpassing AEO, DO, and RUN with values of 0.0706, 0.0789, and 0.0649, respectively. Furthermore, the proposed controller was benchmarked against advanced control strategies such as FOPI-PI, TFOIDFF, and FOPI-PIDD2, yielding improvements in objective function values by 28.89%, 54.89%, and 26.42%, respectively. The simulation findings demonstrate that the FOPI-TIDμ-PIDA controller ensures significantly reduced overshoot by less than 0.12 Hz, faster settling times by less than 9.4 s, and enhanced voltage-frequency regulation even under ±25% variations in system parameters. Collectively, these results Proves the robustness, adaptability, and effectiveness of the proposed controller in advancing the stability and resilience of sustainable hybrid linked power networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.