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<p>A wind-diesel hybrid system integrates wind turbines and diesel generators for providing power that is reliable and efficient, specifically for remote or off-grid locations. The random nature of wind energy may lead to voltage swings and reactive power imbalances, which jeopardise system stability and power quality. Proper reactive power compensation is essential to ensure voltage stability along with power factor improvement and transmission line loss reduction. Here the static synchronous compensator is employed in a model for a wind-diesel hybrid system for compensation of reactive power to enable smooth operation of power. Transients have the most crucial role in monitoring the stability problems. A static synchronous compensator (STATCOM)-aided controller is also considered for the analysis of the behaviour of the proposed system. A Posicast Controller is a type of feed-forward controller utilised to reduce or suppress oscillations in system response. It does so by providing a control signal that zeroes out the oscillatory parts of system dynamics. With a STATCOM, the Posicast controller tries to enhance reactive power compensation transient response, leading to quicker voltage regulation, reduced overshoot and smaller settling time during disturbances. The Symbiotic Organism Search is one of the bio-inspired metaheuristic algorithms employed in the optimisation study of the hybrid system for transient analysis and others. The effectiveness of the Posicast controller in transient analysis to minimise settling time and reduce damping in oscillations is emphasised in the current study. The suggested algorithm is studied with established optimisation methods such as Ant Lion Optimisation (ALO), Gravitational Search Algorithm (GSA), Seeker Optimisation Algorithm (SOA) and Symbiotic Organism Search Optimisation (SOS) on the MATLAB platform. The suggested system attains a low steady-state error (Ess) of 0.0129, a rapid rise time (tr) of 7.8240, a rapid settling time (ts) of 8.0685&#xa0;s and a very low peak overshoot (Mp) of 0.0321%, which guarantees better stability and optimal performance under dynamic operating conditions. The above results show that the suggested system achieves better accuracy than other methods under different operating conditions.</p>

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SOS algorithm-based optimization techniques for efficient wind-diesel hybrid systems featuring STATCOM-POSICAST control

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月10日

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  • Mainak Mukherjee,
  • Abhik Banerjee

摘要

A wind-diesel hybrid system integrates wind turbines and diesel generators for providing power that is reliable and efficient, specifically for remote or off-grid locations. The random nature of wind energy may lead to voltage swings and reactive power imbalances, which jeopardise system stability and power quality. Proper reactive power compensation is essential to ensure voltage stability along with power factor improvement and transmission line loss reduction. Here the static synchronous compensator is employed in a model for a wind-diesel hybrid system for compensation of reactive power to enable smooth operation of power. Transients have the most crucial role in monitoring the stability problems. A static synchronous compensator (STATCOM)-aided controller is also considered for the analysis of the behaviour of the proposed system. A Posicast Controller is a type of feed-forward controller utilised to reduce or suppress oscillations in system response. It does so by providing a control signal that zeroes out the oscillatory parts of system dynamics. With a STATCOM, the Posicast controller tries to enhance reactive power compensation transient response, leading to quicker voltage regulation, reduced overshoot and smaller settling time during disturbances. The Symbiotic Organism Search is one of the bio-inspired metaheuristic algorithms employed in the optimisation study of the hybrid system for transient analysis and others. The effectiveness of the Posicast controller in transient analysis to minimise settling time and reduce damping in oscillations is emphasised in the current study. The suggested algorithm is studied with established optimisation methods such as Ant Lion Optimisation (ALO), Gravitational Search Algorithm (GSA), Seeker Optimisation Algorithm (SOA) and Symbiotic Organism Search Optimisation (SOS) on the MATLAB platform. The suggested system attains a low steady-state error (Ess) of 0.0129, a rapid rise time (tr) of 7.8240, a rapid settling time (ts) of 8.0685 s and a very low peak overshoot (Mp) of 0.0321%, which guarantees better stability and optimal performance under dynamic operating conditions. The above results show that the suggested system achieves better accuracy than other methods under different operating conditions.