摘要
引入分位数概念来改善评估稳定性,并采用序贯最小优化策略来提高计算速度。首先,采用新能源和系统特征构建表征电力系统暂态稳定性的原始特征集,有效表征新能源接入对暂态稳定性的影响;然后,引入分位数来改变稳定类与不稳定类的最近点位置,降低由于新能源的波动性和不确定性对评估稳定性的影响,进而引入序贯最小优化策略,将弹球损失支持向量机的高维优化问题转化为多个低维优化问题,有效提高计算速度。最后,以修改后的IEEE-39测试算例进行仿真分析,验证所提方法的有效性和准确性。
The concept of quantile is introduced to improve the stability of transient stability assessment.Sequential minimum optimization(SMO)strategy is used to reduce computing time.Firstly,a group of renewable energy classification and system-level features are first extracted from the power system operation parameters to build the original feature set.These feature can reflect the influence of renewable energy access on the transient stability of power systems.Then,the definition of the nearest point between the two classes is changed by the concept of quantile.It can effectively reduce the impact of critically stable interference samples due to increased uncertainty in renewable energy.Furthermore,the SMO strategy is introduced to transform the high-dimensional binomial optimization problem of support vector machine with pinball loss into multiple low-dimensional binomial optimization problems,which can effectively improve the calculation speed.Finally,the simulated results of modified IEEE 39-bus system demonstrate the feasibility and validity of the proposed method.
作者
刘信彤
辛业春
王长江
张嵩
Liu Xintong;Xin Yechun;Wang Changjiang;Zhang Song(Department of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2021年第5期98-104,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51607032)。
关键词
暂态稳定
新能源
特征选择
支持向量机
transient stability
renewable energy resources
feature selection
support vector machines
