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<p>Offshore wind energy conversion systems have an inherent control challenge due to the long transmission cables necessary to deliver the generated power to an energy station. Grid-tied power system with a transmission cable has dynamics that threaten system stability. In this sense, controlling this kind of system subject to exogenous disturbances is not trivial, requiring sophisticated control algorithms whose parameter tuning is not intuitive. Therefore, this work presents a robust adaptive current control approach optimized with a new improved chaotic stochastic fractal search algorithm with fitness-distance balance (SFS-FDB). This novel optimizer uses a stochastic selective strategy of ten chaotic maps to improve the SFS-FDB performance. The modification consists in replacing the random variables in the SFS-FDB algorithm with values generated by chaotic maps, independently, at each iteration, enhancing the diversity in the solution, which avoids premature convergence, stagnation, and biased solutions. Four scenarios are considered to evaluate the resulting optimized controller: current reference changes, two grid inductance variations (including up to ten times the nominal value of grid-side inductance), and grid frequency oscillations. Simulation results demonstrate the effectiveness of the developed intelligent control solution, making the tracking errors converge to residual values in steady state when the renewable energy system operates under weak grid conditions.</p>

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A new improved chaotic stochastic fractal search with fitness-distance balance-based advanced controller for offshore wind energy transmission systems with long cables connected in weak grids

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月25日

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  • Paulo Jefferson Dias de Oliveira Evald,
  • Matheus Schramm Dall’asta,
  • Lenon Schmitz,
  • Jéssika Melo de Andrade,
  • Telles Brunelli Lazzarin

摘要

Offshore wind energy conversion systems have an inherent control challenge due to the long transmission cables necessary to deliver the generated power to an energy station. Grid-tied power system with a transmission cable has dynamics that threaten system stability. In this sense, controlling this kind of system subject to exogenous disturbances is not trivial, requiring sophisticated control algorithms whose parameter tuning is not intuitive. Therefore, this work presents a robust adaptive current control approach optimized with a new improved chaotic stochastic fractal search algorithm with fitness-distance balance (SFS-FDB). This novel optimizer uses a stochastic selective strategy of ten chaotic maps to improve the SFS-FDB performance. The modification consists in replacing the random variables in the SFS-FDB algorithm with values generated by chaotic maps, independently, at each iteration, enhancing the diversity in the solution, which avoids premature convergence, stagnation, and biased solutions. Four scenarios are considered to evaluate the resulting optimized controller: current reference changes, two grid inductance variations (including up to ten times the nominal value of grid-side inductance), and grid frequency oscillations. Simulation results demonstrate the effectiveness of the developed intelligent control solution, making the tracking errors converge to residual values in steady state when the renewable energy system operates under weak grid conditions.