基于XGBOOST-PSO提高受端电网电压暂态稳定的发电机无功优化方法

考虑发电机稳态输出无功对其支撑暂态电压恢复稳定能力的影响，基于机器学习研究优化发电机稳态输出无功提高电压对故障扰动保持暂态稳定能力的预防控制方法。该方法采用加权多二元表暂态稳定裕度指标量化母线暂态电压对不同预想故障扰动的综合稳定裕度，并基于指标排序确定稳定裕度薄弱母线。同时基于发电机无功调节对预想故障下各薄弱母线电压暂态稳定裕度综合作用灵敏度排序，选择作用灵敏发电机。在利用XGBoost建立根据系统稳态特征向量预测薄弱母线暂态电压稳定的分类模型基础上，以系统对预想故障扰动保持暂态电压稳定为约束、以减小发电机稳态无功调节对网损产生影响为目标，基于潮流计算寻优灵敏发电机稳态输出无功，以提高薄弱母线的暂态电压稳定性。最后采用雅湖直流接入江西电网的PSASP计算模型验证了所提方法的有效性。

A generator reactive power optimization method based on XGBOOST-PSO to improve the voltage transient stability of a receiving terminal network

Considering the effect of generator steady-state output reactive power on the ability to support transient voltage recovery stability, preventive control through optimizing that power to improve the ability of grid maintaining transient voltage stability under severe fault disturbance is studied based on machine learning. The method uses a weighted multi-binary table transient stability margin index to quantify the comprehensive stability margin of bus transient voltages to different expected fault disturbances. Then it determines the bus with weak stability margin based on the index ranking. At the same time, based on the comprehensive action sensitivity ranking of generator reactive power regulation on the voltage transient stability margin of each weak bus under the expected fault, the action sensitive generator can be determined. Then an XGBoost classification model for predicting transient voltage stability based on the system steady-state characteristics vector is developed. This considers the constraint of grid voltage maintaining transient stability under expected severe fault. It has the objective of reducing the impact on grid active power loss caused by generator reactive power. A regulation method of using power flow calculation to optimize the steady-state reactive power output of the sensitive generator is proposed. Finally, the validity of the proposed method is verified based on the PSASP calculation model for Yahu DC transmission fed-in Jiangxi power grid.