Enhanced reactive power control and stability analysis of hybrid power system using Lyapunov and snake algorithm-based SVC strategies

• This work focusses on Multi-SVC, Multi-HPS systematic and comparative analysis. • Lyapunov ensures stability via ISE, SOA tunes PI via ITAE for optimized control. • Robust simulation-based validation of the system is performed using MATLAB. • Enhanced reactive power control achieved using advanced SVC strategies. • SVC3 shows fastest response, best damping; SVC2 excels in voltage, exciter control. Static Var Compensator (SVC) is a key FACTS device for enhancing the stability of Wind–Diesel Hybrid Power System (HPS) by dynamically managing reactive power, regulating voltage, and reducing stress on Diesel Generator (DG). The study introduces an advanced control approach involving Lyapunov theory and the Snake Optimization Algorithm (SOA) to optimize SVC performance. The proposed framework is evaluated on three distinct HPS configurations comprising a wind-driven Induction Generator (IG) and a (DG)-driven Synchronous Generator (SG). SVC meets the IG’s reactive power demand and compensates for load fluctuations. Type 1 and Type 2 SVCs are tuned via Lyapunov-based Integral Square Error minimization. SVC Type 3 is tuned via SOA-based Integral Time Absolute Error minimization. The transient stability of HPS under step changes in reactive load is assessed with comprehensive simulations, supported by Eigenvalue (EGV) and Damping Ratio (DR) analyses. SVC Type 3 (SOA-tuned PI) consistently outperforms others, achieving the fastest settling times (0.015 sec in HPS3) and highest DR (0.211) for the dominant oscillatory mode. It ensures rapid oscillation damping and stability enhancement. SVC Type 2 delivers the best voltage and exciter control, recording minimal deviations in terminal and exciter voltage, making it suitable for voltage-sensitive applications. SVC Type 1 maintains stability but exhibits slower response and higher deviations, particularly in HPS1. The study demonstrates that metaheuristic-tuned SVCs significantly improve both dynamic and stability metrics in HPS. The methodology offers scalability to other renewable configurations, such as solar–micro hydro, paving the way for robust, efficient, and sustainable HPS operation.

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Publication Details

Journal
Results in Engineering
Published
2026-02-23
DOI
https://doi.org/10.1016/j.rineng.2026.109712
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
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article

Enhanced reactive power control and stability analysis of hybrid power system using Lyapunov and snake algorithm-based SVC strategies

Sheila Mahapatra, Niharika Agrawal, Bishwajit Dey
Results in Engineering
Power System Optimization and Stability
article

Enhanced reactive power control and stability analysis of hybrid power system using Lyapunov and snake algorithm-based SVC strategies

Sheila Mahapatra, Niharika Agrawal, Bishwajit Dey
article en

Abstract

• This work focusses on Multi-SVC, Multi-HPS systematic and comparative analysis. • Lyapunov ensures stability via ISE, SOA tunes PI via ITAE for optimized control. • Robust simulation-based validation of the system is performed using MATLAB. • Enhanced reactive power control achieved using advanced SVC strategies. • SVC3 shows fastest response, best damping; SVC2 excels in voltage, exciter control. Static Var Compensator (SVC) is a key FACTS device for enhancing the stability of Wind–Diesel Hybrid Power System (HPS) by dynamically managing reactive power, regulating voltage, and reducing stress on Diesel Generator (DG). The study introduces an advanced control approach involving Lyapunov theory and the Snake Optimization Algorithm (SOA) to optimize SVC performance. The proposed framework is evaluated on three distinct HPS configurations comprising a wind-driven Induction Generator (IG) and a (DG)-driven Synchronous Generator (SG). SVC meets the IG’s reactive power demand and compensates for load fluctuations. Type 1 and Type 2 SVCs are tuned via Lyapunov-based Integral Square Error minimization. SVC Type 3 is tuned via SOA-based Integral Time Absolute Error minimization. The transient stability of HPS under step changes in reactive load is assessed with comprehensive simulations, supported by Eigenvalue (EGV) and Damping Ratio (DR) analyses. SVC Type 3 (SOA-tuned PI) consistently outperforms others, achieving the fastest settling times (0.015 sec in HPS3) and highest DR (0.211) for the dominant oscillatory mode. It ensures rapid oscillation damping and stability enhancement. SVC Type 2 delivers the best voltage and exciter control, recording minimal deviations in terminal and exciter voltage, making it suitable for voltage-sensitive applications. SVC Type 1 maintains stability but exhibits slower response and higher deviations, particularly in HPS1. The study demonstrates that metaheuristic-tuned SVCs significantly improve both dynamic and stability metrics in HPS. The methodology offers scalability to other renewable configurations, such as solar–micro hydro, paving the way for robust, efficient, and sustainable HPS operation.

Results in EngineeringVol. 29
Alliance University (IN), University of Rajasthan (IN)
Affordable and clean energy
Openalex Percentile: Top 47%
Power System Optimization and Stability
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