考虑风电场无功功率潜力的风电集群接入电网双层无功功率优化OA
Bi-Level Reactive Power Optimization for Wind Cluster Integrating the Power Grid Considering the Reactive Power Potential of Wind Farm
随着大规模风电集群接入电力系统,风电场更多地参与电网无功功率调节,基于此首先建立了以电力系统有功功率网损和电压偏差最小为目标函数的上层优化模型.继而对该模型进行求解,以减少系统网损,实现电网的安全、节能运行.其次,建立下层模型对风电集群进行精细化分析,估算出风电集群的无功功率潜力,以风电场的无功功率潜力为目标函数,各风电机组单元的无功功率出力为待优化量,协调风电集群内部的无功功率输出,采用一种改进鲸鱼算法求解此双层优化模型.最后,通过算例验证了所提的优化策略和算法能在风电无功功率潜力利用最大化时能有效减小电力系统的网损和电压偏差.
With the integration of large-scale wind power clusters into the power system,wind farms are increasingly involved in reac-tive power regulation of the power grid.Based on this,an upper level optimization model is first established to minimize the active power loss and voltage deviation in the power system.Subsequently,the model is solved to reduce system network loss and achieve safe and energy-saving operation of the power grid.Additionally,a detailed analysis of the wind power cluster is conducted at a lower level,estimating its reactive power potential.Taking the reactive power potential of the wind farm as the objective function and the reactive power output of each wind turbine unit as the optimization variable,this study coordinates the reactive power output within the wind farm cluster and employs an improved whale optimization algorithm to solve this bi-level optimization model.Finally,the proposed optimization strategy and algorithm are verified through case studies to effectively reduce network losses and voltage devia-tion in the power system while maximizing utilization of wind power's reactive power potential.
马喜平;甄文喜;梁琛;董晓阳;李亚昕
国网甘肃省电力公司电力科学研究院,兰州 730070国网甘肃省电力公司电力科学研究院,兰州 730070国网甘肃省电力公司电力科学研究院,兰州 730070国网甘肃省电力公司电力科学研究院,兰州 730070国网甘肃省电力公司电力科学研究院,兰州 730070
信息技术与安全科学
多目标无功功率优化双层优化无功功率潜力分析改进鲸鱼算法
multi-objective reactive power optimizationbi-level optimizationreactive power potential analysisimproved whale algorithm
《南方电网技术》 2026 (7)
101-110,10
国家自然科学基金资助项目(62063015)国家电网甘肃电力公司科技项目(52272223004A). Supported by the National Natural Science Foundation of China(62063015)the Science and Technology Project of State Grid Gansu Electric Power Company(52272223004A).
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