论文标题
电力分配网络弹性的随机资源分配
Stochastic Resource Allocation for Electricity Distribution Network Resilience
论文作者
论文摘要
近年来，这对于提高电力分销网络（DNS）对暴风雨引起的故障的弹性至关重要。通过分布式能源资源（DER）启用的微电网可以大大帮助加快载荷的重新加快，尤其是在完全没有批量电源的情况下。我们描述了一种综合方法，该方法在故障场景的不确定性下考虑了前键入的分配问题，以及在失败组件的多个周期修复过程中微电网中的验证后调度问题。这个问题在计算上具有挑战性，因为场景（分别二进制变量）的数量在网络大小中呈指数增加（分别四次）。我们解决所得的两阶段混合构成线性程序（MILP）的总体解决方案方法涉及实施样本平均近似方法（SAA）方法和弯曲器分解。此外，我们实施了一种贪婪的方法，以减少迅速修复计划和调度问题的计算时间要求。在修改的IEEE 36节点网络上评估所得解决方案的最佳性。
In recent years, it has become crucial to improve the resilience of electricity distribution networks (DNs) against storm-induced failures. Microgrids enabled by Distributed Energy Resources (DERs) can significantly help speed up re-energization of loads, particularly in the complete absence of bulk power supply. We describe an integrated approach which considers a pre-storm DER allocation problem under the uncertainty of failure scenarios as well as a post-storm dispatch problem in microgrids during the multi-period repair of the failed components. This problem is computationally challenging because the number of scenarios (resp. binary variables) increases exponentially (resp. quadratically) in the network size. Our overall solution approach for solving the resulting two-stage mixed-integer linear program (MILP) involves implementing the sample average approximation (SAA) method and Benders Decomposition. Additionally, we implement a greedy approach to reduce the computational time requirements of the post-storm repair scheduling and dispatch problem. The optimality of the resulting solution is evaluated on a modified IEEE 36-node network.
