考虑源荷随机性与相关性的直流配电网量测概率优化配置方法

大规模分布式能源以直流源荷形式接入直流配电网,其功率强随机与强相关特性深刻影响实时量测数据不足、依赖伪量测数据的直流配电网态势感知的准确性,急需研究实时量测点的优化配置保障系统状态估计精度。为此,本文首先考虑源荷功率的随机性与相关性影响,建立节点注入功率伪量测模型,提出基于三点估计的改进Nataf变换的直流配电网概率状态估计方法,计算节点电压状态量的估计偏差概率分布；在此基础上,建立以量测点配置成本最少为目标,考虑节点电压估计偏差机会约束的直流配电网量测概率优化配置模型,求解得到最优配置方案。采用改进的IEEE-33节点系统开展算例仿真,结果表明,所提方法能够有效兼顾量测配置的经济性与状态估计精度。

Stochastic optimal placement method of measurement for DC distribution network considering probability and correlation of source load

Large-scale distributed energy resources (DERs) in the form of DC source load access to the DC distribution network. The probability and correlation of DERs power are remarkable, which profoundly affects the accuracy of the DC distribution network situational awareness with insufficient real-time measurement data and pseudo-measurement data-dependent. It is an urgent need to study the optimal placement of real-time measurement points to ensure the accuracy of system state estimation (SE). Therefore, a pseudo-measurement model of node injected power considering the impact of probability and correlation of source-load power is firstly established in this paper. And a stochastic state estimation (SSE) method for DC distribution network based on the modified Nataf transformation with the three-point estimation is proposed, and the probability distribution of the node voltage estimation deviation can be calculated. On this basis, a stochastic optimal placement model of measurement for DC distribution network considering the chance constraint of the node voltage estimation deviation is built to minimize the measurement placement cost, and the optimal placement scheme can be figured out. The modified IEEE-33 node system is used to carry out case simulation, and the results show that the proposed method can effectively balance the economy of measurement placement and the SE accuracy.