Aiming at the transformer DC demagnetization problem triggered by the complexity of AC/DC grid scale operation and the geomagnetic burst activity generated by the solar motion, this paper proposes the installation strategy of DC demagnetization measures for the control of transformer based on the whale optimization algorithm, in which the DC demagnetization inhibiting device combines with the characteristics of passive filters for the combination of the installation to reduce the high and even harmonics more efficiently. A three-phase transformer dual winding model is established in PSCAD to carry out transformer DC demagnetization simulation study, and A simulation model based on the IEEE33 node grid is developed to identify and manage DC demagnetization sites. The whale optimization algorithm is employed to minimize both the neutral point current and investment costs across various operating conditions, aiming to find the optimal configuration of demagnetization management equipment. Simulation results demonstrate that the total bias current is effectively controlled after applying the intelligent algorithm for site identification and management.

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A Whale Optimization Algorithm Based Strategy to Govern DC Bias

  • Lulu Liu,
  • Chenxuan Zhu,
  • Yang Liu

摘要

Aiming at the transformer DC demagnetization problem triggered by the complexity of AC/DC grid scale operation and the geomagnetic burst activity generated by the solar motion, this paper proposes the installation strategy of DC demagnetization measures for the control of transformer based on the whale optimization algorithm, in which the DC demagnetization inhibiting device combines with the characteristics of passive filters for the combination of the installation to reduce the high and even harmonics more efficiently. A three-phase transformer dual winding model is established in PSCAD to carry out transformer DC demagnetization simulation study, and A simulation model based on the IEEE33 node grid is developed to identify and manage DC demagnetization sites. The whale optimization algorithm is employed to minimize both the neutral point current and investment costs across various operating conditions, aiming to find the optimal configuration of demagnetization management equipment. Simulation results demonstrate that the total bias current is effectively controlled after applying the intelligent algorithm for site identification and management.