Evidence map›Paper›PMID 41326502›Full record

ArticleScientific reports2025

Multi-stage sliding mode control design with optimal state estimator for load frequency regulation in hybrid-source power systems.

Anh-Tuan Tran, Van Van Huynh, Bang Le-Huy Nguyen, Jae Woong Shim, Ton Duc Do

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Anh-Tuan TranModeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Van Van HuynhAdvanced Intelligent Technology Research Group, Faculty of Electrical and ElectronicsEngineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Bang Le-Huy NguyenModeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Jae Woong ShimDepartment of Electrical Engineering, Sangmyung University, Seoul, 03016, South Korea. jaewshim@smu.ac.kr.
Ton Duc DoDepartment of Robotics and Mechatronics, School of Engineering and Digital Sciences (SEDS), Nazarbayev University, 010000, Astana, Kazakhstan.

Funding

Korea Institute of Energy Technology Evaluation and Planning RS-2025-02311040
6 · The paper itself

Abstract

The rapid growth of renewable energy sources (RES) and the increasing complexity of modern power systems (PSs) have introduced significant challenges for automatic load frequency control (LFC), including large uncertainties, disturbances, and reduced system inertia. These issues limit the effectiveness of conventional control strategies and may threaten system stability and reliability. To address these problems, this paper proposes a novel multi-stage sliding mode control (SMC) scheme integrated with an optimal state estimator (OSE) for LFC in multi-area hybrid PSs (HPSs) consisting of conventional thermal, hydro, and gas units together with battery and flywheel energy storage and renewable sources such as photovoltaic and wind power. The OSE is first designed to provide accurate state feedback under uncertain operating conditions, thereby improving control robustness. Based on these estimates, a new multi-term sliding surface is formulated to ensure fast dynamic response and strong resilience against system uncertainties. The stability of the proposed approach is mathematically validated, and extensive simulations are performed under various load changes, uncertainty scenarios, and communication delay in both isolated and interconnected HPSs. The results demonstrate that the proposed controller outperforms recently developed SMC-based approaches by reducing overshoot and undershoot by up to 46.4%, undershoot by up to 48.1%, and shortening settling time by up to 23.8%, while also eliminating chattering. These improvements highlight the robustness, reliability, and practical applicability of the proposed scheme for future complex PSs with high RES penetration.

Indexed as

Load frequency controlMulti-area power systemsSliding mode controlState estimator

Identifiers

PMID41326502
PMCPMC12705771

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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.