论文标题

使用周期流量的扩展计划

Transmission Expansion Planning Using Cycle Flows

论文作者

Neumann, Fabian, Brown, Tom

论文摘要

构成大多数传输扩展计划(TEP)配方的常见线性最佳功率流(LOPF)公式使用总线电压作为辅助优化变量来描述Kirchhoff的电压定律。除了引入大量的辅助变量外,基于角度的配方具有缺点,即不适合考虑多个断开网络的连接,但是,可以通过表达基于Kirchhoff的电压映射的网络绘制量循环的范围来缩小这些辅助变量并减少所需数量的约束数量。在计算挑战性的基准中,例如通过多周期LOPF的发电能力扩展,在先前的工作中显示了这种等效的重新制作,以减少LOPF问题的解决时间。在离散的TEP问题中允许将线路容量合作使其成为一个非凸的混合企业问题。本文通过LOPF开发了针对TEP问题的新型基于周期的重新制定,并将其与基于标准角度的公式进行了比较。多个断开网络连接的组合是针对这两种配方的形式化的,这是文献中尚未受到关注的主题。基于周期的公式显示可方便地适应同步选项。由于这两种配方都使用了大$ m $析取放松,因此提供了适合大$ m $值的有用推导。竞争配方以不同的空间和时间分辨率的欧洲传输系统的现实产生和传输扩展模型进行了基准测试。基于周期的配方在特定情况下求解高达31倍,而平均速度为4。

The common linear optimal power flow (LOPF) formulation that underlies most transmission expansion planning (TEP) formulations uses bus voltage angles as auxiliary optimization variables to describe Kirchhoff's voltage law. As well as introducing a large number of auxiliary variables, the angle-based formulation has the disadvantage that it is not well-suited to considering the connection of multiple disconnected networks, It is, however, possible to circumvent these auxiliary variables and reduce the required number of constraints by expressing Kirchhoff's voltage law directly in terms of the power flows, based on a cycle decomposition of the network graph. In computationally challenging benchmarks such as generation capacity expansion with multi-period LOPF, this equivalent reformulation was shown in previous work to reduce solving times for LOPF problems by an order of magnitude. Allowing line capacity to be co-optimized in a discrete TEP problem makes it a non-convex mixed-integer problem. This paper develops a novel cycle-based reformulation for the TEP problem with LOPF and compares it to the standard angle-based formulation. The combinatorics of the connection of multiple disconnected networks is formalized for both formulations, a topic which has not received attention in the literature. The cycle-based formulation is shown to conveniently accommodate synchronization options. Since both formulations use the big-$M$ disjunctive relaxation, useful derivations for suitable big-$M$ values are provided. The competing formulations are benchmarked on a realistic generation and transmission expansion model of the European transmission system at varying spatial and temporal resolutions. The cycle-based formulation solves up to 31 times faster for particular cases, while averaging at a speed-up of factor 4.

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