论文标题
分配网络中修复问题的新型分解解决方案方法
A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks
论文作者
论文摘要
由于切换决策和最佳功率流(OPF)约束,分布网络恢复问题本质上是混合整数和非线性优化问题。这两个部分之间的联系涉及通过大型M系数建模的逻辑含义。这些系数的存在使使用分支和结合方法在计算负担方面非常贫穷,因此可以放松混合企业问题。此外,该链接抑制了经典弯曲器算法在分解问题中的使用,因为所得的切割仍然取决于大M系数。在本文中,提出了一种新颖的分解方法,用于称为修饰组合弯曲器(MCB)的恢复问题。在这方面,重新配置问题和OPF问题分解为主问题和子问题,这些问题是通过连续迭代解决的。在大量中断区域的情况下,数值结果表明,MCB在短时间内(经过几次迭代后)提供了一种恢复解决方案,其质量在可以展示时接近可靠的最佳性。
The distribution network restoration problem is by nature a mixed integer and non-linear optimization problem due to the switching decisions and Optimal Power Flow (OPF) constraints, respectively. The link between these two parts involves logical implications modelled through big-M coefficients. The presence of these coefficients makes the relaxation of the mixed-integer problem using branch-and-bound method very poor in terms of computation burden. Moreover, this link inhibits the use of classical Benders algorithm in decomposing the problem because the resulting cuts will still depend on the big-M coefficients. In this paper, a novel decomposition approach is proposed for the restoration problem named Modified Combinatorial Benders (MCB). In this regard, the reconfiguration problem and the OPF problem are decomposed into master and sub problems, which are solved through successive iterations. In the case of a large outage area, the numerical results show that the MCB provides, within a short time (after a few iterations), a restoration solution with a quality that is close to the proven optimality when it can be exhibited.