电压暂降随机预估的自适应信赖域方法

Adaptive Trust Region Method for Stochastic Estimation of Voltage Sags

当前的电压暂降随机预估方法已不能满足电力系统中含有分布式电源和功率型负荷的情形。提出基于自适应信赖域算法的电压暂降随机预估方法,考虑了分布式电源类型和负荷模型对电压暂降评估指标的影响,解决了故障时的病态潮流计算问题。根据敏感负荷的电压容忍曲线,运用二次插值计算4种故障类型下公共连接点(point of common coupling,PCC)的故障相暂降域及评估指标。文中对IEEE标准试验系统进行分析和测试,结果表明,所提方法能够得到更符合实际的期望暂降频次(expected sag frequency,ESF)指标,且自适应信赖域方法具有良好的全局寻优能力和计算效率。

The conventional stochastic estimation methods on voltage sags are difficult to satisfy the requirement of the power systems with distributed generation and power-typed loads. The paper proposes a stochastic approach estimating voltage sags based on adaptive trust region algorithm for ill-conditioned power＇flow calculation under faulty conditions, in which distributed generation resources and load model are taken into account. From the voltage tolerance curve of sensitive loads, quadratic interpolation is adopted to calculate the voltage sag domain and evaluation indices of point of common coupling （PCC） under four fault types, respectively. The IEEE test systems are adopted to test the proposed method, the results show that the proposed method is good at computing expected sag frequency （ESF） indices more accurately, and the adopted adaptive trust region algorithm has better capability in global optimization and computational efficiency.