Evidence map›Paper›PMID 40394105›Full record

ArticleScientific reports2025

Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems.

Muhammad Zubair Yameen, Abdul Khalique Junejo, Zhigang Lu, Rizwan Aziz Siddiqui, Fayez F M El-Sousy, Ibtisam Naveed

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Muhammad Zubair YameenKey Laboratory of Power Electronics for Energy Conservation and Drive Control of Hebei Province, Yanshan University, Qinhuangdao, 066004, China.
Abdul Khalique JunejoState Key Laboratory of Advanced Electromagnetic Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, China. ak_junejo@hust.edu.cn.
Zhigang LuKey Laboratory of Power Electronics for Energy Conservation and Drive Control of Hebei Province, Yanshan University, Qinhuangdao, 066004, China.
Rizwan Aziz SiddiquiDepartment of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, 67450, Pakistan.
Fayez F M El-SousyDepartment of Electrical Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj, 16273, Saudi Arabia.
Ibtisam NaveedSchool of Electrical Engineering, Southeast University, Nanjing, 210096, China.

Funding

Fayez F.M. El- Sousy PSAU/2025/R/1446
6 · The paper itself

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

Dual-area power networkElectric vehicleGOAITAELFCPID controllerPSO

Identifiers

PMID40394105
PMCPMC12092779

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Registered trials

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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.