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Turbine-Governor Control01:17

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Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
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Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
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Decentralized Sampled-Data Control for Stochastic Disturbance in Interconnected Power Systems With PMSG-Based Wind

Lakshmanan Shanmugam, Kumarasamy Palanimuthu, Young Hoon Joo

    IEEE Transactions on Cybernetics
    |August 24, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study enhances the stability of interconnected power systems with permanent magnet synchronous generator (PMSG)-based wind turbines (WTs) using a decentralized control strategy. The research ensures reliable frequency response against disturbances for improved grid performance.

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    Area of Science:

    • Electrical Engineering
    • Control Systems
    • Renewable Energy Integration

    Background:

    • Interconnected power systems (IPSs) face challenges in maintaining stable frequency response due to the integration of renewable energy sources like permanent magnet synchronous generator (PMSG)-based wind turbines (WTs).
    • External and stochastic disturbances can significantly degrade the performance of these systems.
    • Existing models often do not fully capture the stochastic nature of disturbances affecting WTs.

    Purpose of the Study:

    • To investigate and improve the frequency response stability of IPSs with PMSG-based WTs under various disturbances.
    • To develop a decentralized control scheme that enhances system resilience.
    • To model the system incorporating stochastic disturbances for a more realistic analysis.

    Main Methods:

    • Derivation of a state-space model for IPSs with PMSG-based WTs.
    • Development of a stochastic state-space model to include external and stochastic disturbances.
    • Design of a decentralized sampled-data load frequency control strategy.
    • Application of Lyapunov stability theory and Itô's formula to derive sufficient stability conditions.

    Main Results:

    • Stochastic sufficient conditions were derived to guarantee asymptotic stability in the mean square with H∞ performance.
    • The proposed decentralized control scheme effectively regulates frequency response against both deterministic and stochastic noises.
    • Simulations on a three-area IPS demonstrated superior stability performance compared to existing methods.

    Conclusions:

    • The developed decentralized control strategy significantly enhances the frequency response stability of interconnected power systems with PMSG-based WTs.
    • The stochastic modeling approach provides a more accurate representation of system dynamics under disturbances.
    • The findings confirm the effectiveness of the proposed methods for reliable grid operation with high wind power penetration.