基于多重故障和混合仿真算法的风电系统概率短路分析

Probabilistic short-circuit analysis of wind power systems with multiple contingencies and hybrid sampling

多重故障、风电并网增加了概率短路计算难度。引入双馈风电机组潮流算法,计及风速不确定性,得到概率短路前初始运行方式。引入多重短路算法,计算节点电压和支路电流的期望、方差以及概率分布。对枚举故障线路进行概率加权,抽样确定其他故障参数,建立混合仿真算法。综合考虑解析枚举和概率抽样特点,提出混合概率仿真方差计算公式。算例分析对比了风电出力波动、双重短路对概率短路计算结果的影响,比较了三序电压和电流的收敛性。研究结果为电气设备选择和电网安全分析提供了参考数据。

Multiple-contingency and wind power integration add difficulty for probabilistic short-circuit analysis （PSCA）. The power flow model with doubly-fed induction generators （DFIGs） is introduced, which together with wind uncertainty yields initial state before contingency. The multiple-contingency algorithm is introduced to find expectation, variance, and distribution of the bus voltages and the branch currents. A hybrid probabilistic sampling technique is proposed with the fault branch enumerated and probabilistically weighted, and other fault parameters sampled. The variance for the hybrid simulation is proposed by combined analytical enumeration and probabilistic sampling. Numerical analysis quantifies impact of wind fluctuation and double contingencies on the PSCA results, and compares convergence of sequential voltages and currents. The proposed models provide reference to select electrical equipment and analyze power system security.