AI-enhanced load frequency control in multi-area power systems via a self-tuning PIDF with ANN-based NMPC and hybrid cat-pikas optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10258682" target="_blank" >RIV/61989100:27240/25:10258682 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/25:10258682
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590123025035170" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123025035170</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rineng.2025.107462" target="_blank" >10.1016/j.rineng.2025.107462</a>
Alternative languages
Result language
angličtina
Original language name
AI-enhanced load frequency control in multi-area power systems via a self-tuning PIDF with ANN-based NMPC and hybrid cat-pikas optimization
Original language description
Ensuring frequency stability in multi-area power systems under diverse disturbances remains a major challenge. This paper proposes an AI-enhanced self-tuning nonlinear-proportional-integrator-derivative denoising filter (NL-PIDF) controller designed within an artificial neural network (ANN)-based nonlinear model predictive control (NMPC) framework and optimized using a novel Hybrid Cat-Pikas Optimization (HCPO) algorithm. The ANN predictor identifies the nonlinear system dynamics, while an error compensator mitigates steady-state offsets caused by prediction errors. To further enhance dynamic stability, a superconducting magnetic energy storage (SMES) unit is integrated in Area 1, and high-voltage direct current (HVDC) tie-lines are employed between selected areas. The approach is evaluated on a nonlinear three-area power system including steam, gas, and combined-cycle turbines, considering key nonlinearities such as the reheater, generation rate constraint (GRC), governor deadband (GDB), and boiler dynamics (BD). Simulation results, supported by time-domain and eigenvalue analyses, demonstrate significant improvements in damping frequency oscillations and inter-area power exchanges compared with conventional controllers. The proposed strategy achieves faster settling, reduced overshoot/undershoot, and enhanced robustness under random step, sinusoidal load disturbances, and wide parameter variations. In such a way that the proposed strategy reduces frequency overshoot by approximate to 45%, improves settling time by approximate to 38%, and lowers ITSE by approximate to 52% compared with conventional tuned PID and recent metaheuristic-based controllers, confirming its robustness against load disturbances and system nonlinearities.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/EH23_021%2F0008759" target="_blank" >EH23_021/0008759: Increasing the resilience of power grids in the context of decarbonisation, decentralisation and sustainable socio-economic development</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Results in Engineering
ISSN
2590-1230
e-ISSN
2590-1230
Volume of the periodical
28
Issue of the periodical within the volume
December 2025
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
41
Pages from-to
1-41
UT code for WoS article
001598167400011
EID of the result in the Scopus database
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