论文标题
AC功率流的基于MISOCP的分解方法
An MISOCP-Based Decomposition Approach for the Unit Commitment Problem with AC Power Flows
论文作者
论文摘要
单位承诺（UC）和最佳功率流（OPF）是短期电力系统计划中的两个基本问题，这些问题传统上是顺序解决的。最新的最新方法主要使用UC级别功率流程方程的直流流近似，并且获得的生成器承诺作为输入发送到OPF级别。但是，这种方法可以产生不可行的或次优的发电机时间表。在本文中，我们旨在通过交替的电流（AC）功率流方程来同时解决UC问题，这结合了UC和OPF问题的挑战性质。由于AC流程方程的高度非概念性质，我们利用了UC问题的混合校准二阶编程（MISOCP）松弛作为解决方案方法的基础。对于较小的实例，我们开发了两种不同的算法，以利用OPF文献中最新进展，并获得具有较小最佳差距的高质量可行解决方案。对于较大的实例，我们提出了一种基于拉格朗日分解的新型方法，可以产生有希望的结果。
Unit Commitment (UC) and Optimal Power Flow (OPF) are two fundamental problems in short-term electric power systems planning that are traditionally solved sequentially. The state-of-the-art mostly uses a direct current flow approximation of the power flow equations in the UC-level and the generator commitments obtained are sent as input to the OPF-level. However, such an approach can yield infeasible or suboptimal generator schedules. In this paper, we aim to simultaneously solve the UC Problem with alternating current (AC) power flow equations, which combines the challenging nature of both UC and OPF problems. Due to the highly nonconvex nature of the AC flow equations, we utilize the mixed-integer second-order cone programming (MISOCP) relaxation of the UC Problem as the basis of our solution approach. For smaller instances, we develop two different algorithms that exploit the recent advances in the OPF literature and obtain high-quality feasible solutions with provably small optimality gaps. For larger instances, we propose a novel Lagrangian decomposition based approach that yields promising results.
