基于随机响应面法的主动配电网无功优化

考虑分布式电源(DG)的无功主动调控能力,计及状态变量的机会约束,建立主动配电网随机无功优化模型。通过非参数核密度估计对随机因素进行建模,进一步借助随机响应面法,研究适应于多种概率模型的概率潮流计算方法,用以判断状态变量是否满足机会约束,并利用Nataf变换处理随机变量的相关性。结合基于粒子群的无功优化方法,对所建立模型进行求解。最后,基于修改过的IEEE 33节点和美国PGE 69节点配电系统测试所提方法的正确性和有效性。算例表明所提概率潮流计算方法所得累积分布函数具有较高的精度,同时设计不同的场景,进一步表明所提模型和算法适应不同DG无功控制策略、可发现确定性优化方案的概率越界风险并调整解决。

Optimal Reactive Power Flow in Active Distribution Network Based on Stochastic Response Surface Method

Considering the reactive power regulation and control ability of the distributed generator(DG), the stochastic optimal reactive power flow(SORPF)model is proposed, in which the state variables are constrained by chance constraints. Nonparametric kernel density estimation is used to obtain the probability density function of random factors. The probabilistic power flow(PPF)calculation based on the stochastic response surface method is analyzed, which can be suitable for a variety of probabilistic models. The variables'' correlation processing method based on Nataf transformation of PPF is also proposed. The SORPF model can be solved by referring to particle swarm optimization. Finally, the modified IEEE 33-bus distribution system and American PG&E 69-bus distribution system are utilized to test the correctness and effectiveness of SORPF. It follows from the test results that the proposed PPF method has higher accuracy when computing the cumulative distribution function. The test of different scenarios further verifies the model and algorithm proposed in this paper can adapt to different DG control strategies, find the probabilistic cross-border risk and have the ability to fix it.