ArticleScientific reports2024
Enhancing load frequency control and automatic voltage regulation in Interconnected power systems using the Walrus optimization algorithm.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- A CrOA-tuned cascaded (2DOF-PDf)-(LTI) controller for coordinated LFC-AVR regulation in interconnected power systems.Scientific reports · 2026Article
- Adaptive long short term memory-PI based control for load frequency regulation in electric vehicle integrated two area power systems.Scientific reports · 2026Article
- Neural network aided fractional-order second-order sliding mode controller for frequency stabilization of wind integrated nonlinear power system.Scientific reports · 2026Article
- Multi-stage sliding mode control design with optimal state estimator for load frequency regulation in hybrid-source power systems.Scientific reports · 2025Article
- A quasi-oppositional FBI algorithm driven fuzzy cascaded fractional-order controller for enhancing transient stability in hybrid power systems.Scientific reports · 2025Article
- State and disturbance estimation with supertwisting sliding mode control for frequency regulation in hydrogen based microgrids.Scientific reports · 2025Article
- Enhanced hybrid microgrid stability with electric vehicle integration using PDA-FOPIID control optimized by tianji's horse racing algorithm.Scientific reports · 2025Article
- Multi-stage ESO-ADRC for frequency stabilization in off-grid systems with high renewable energy and EV penetration.Scientific reports · 2025Article
- Automatic generation control optimization for power system resilience under real world load variations using genetic algorithm.Scientific reports · 2025Article
- Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation.Scientific reports · 2025Article
- Novel application of sinh cosh optimizer for robust controller design in hybrid photovoltaic-thermal power systems.Scientific reports · 2025Article
- Advanced microgrid optimization using price-elastic demand response and greedy rat swarm optimization for economic and environmental efficiency.Scientific reports · 2025Article
- An approach for load frequency control enhancement in two-area hydro-wind power systems using LSTM + GA-PID controller with augmented lagrangian methods.Scientific reports · 2025Article
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7 authors.
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Abstract
This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations.
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