ArticleScientific reports2025
Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems.
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 5 papers.
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
5 citing papers in PubMed.
- ELLS-NSBA three-stage framework for optimal DG/SC placement and EV integration in distribution networks.Scientific reports · 2026Article
- A hybrid knowledge-based and evolutionary framework for fault diagnosis and optimization in power systems.Scientific reports · 2026Article
- Resilient frequency stabilization of renewable-penetrated microgrids via deep learning and machine learning.Scientific reports · 2026Article
- Comparison of metaheuristic algorithms set-point tracking-based weight optimization for model predictive control.Scientific reports · 2025Article
- Robust load frequency control in renewable integrated Multi Area grids using hybrid SA and QIO tuned PIDF controller.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The integration of unconventional power sources, such as solar, wind, and electric vehicles (EVs), into electrical power grids poses significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can compromise the reliability and quality of power delivered to end-users. To address these challenges, this paper proposes a novel Proportional-Integral-Derivative (PID) controller optimized using a hybrid Grasshopper Optimization Algorithm-Particle Swarm Optimization (GOA-PSO) approach. Unlike conventional tuning methods, the proposed GOA-PSO hybridization leverages the exploratory strengths of GOA and the exploitative capabilities of PSO, resulting in an optimized control strategy that significantly enhances load frequency control (LFC) performance. This study is among the first to integrate a fuzzy-based MPPT PV system, a P&O MPPT-controlled PMSG-based wind energy system, and EVs within a single-area multi-source energy network while simultaneously addressing a dual-area interconnected power system (IPS). The GOA-PSO-PID controller is fine-tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control efficiency. The controller's effectiveness is evaluated across two distinct cases: (1) a single-area system integrating thermal, solar, wind, and EV resources, and (2) a two-area thermal tie-line interconnected power system. Comparative studies across various operational scenarios, including extensive parameter variations (± 40%) and load fluctuations, demonstrate the superior performance of the GOA-PSO-PID controller over the conventional PSO-PID approach. The GOA-PSO-PID achieves a 79.95% reduction in overshoot, a 92.78% reduction in undershoot, and a 98.91% improvement in settling time in the single-area system. Similarly, in the dual-area IPS, it provides a 76.73% reduction in overshoot, an 87.62% reduction in undershoot, and a 75.68% improvement in rise time. These findings highlight the robustness and adaptability of the GOA-PSO-PID controller in handling highly fluctuating renewable-dominated power networks, making it a reliable solution for future smart grids.
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.