作者：Mohamed Awadalla François Bouffard
现实世界电力系统及其基础市场的日常运行依赖于机组承诺问题的及时解决。然而，考虑到其计算复杂性，已经提出了几种基于优化的方法，通过消除冗余的线流约束来减轻其问题公式。这些方法往往忽略了可再生能源发电和需求的空间耦合，这对市场结果有着内在的影响。此外，消除程序主要关注可行区域，并排除了问题的目标函数如何在这里发挥作用。为了解决这些陷阱，我们通过添加有效的不等式约束，排除了原始机组承诺可行性区域的紧线性规划松弛上的冗余和非活动约束。我们扩展了基于优化的方法，称为伞形约束发现，通过在约束集上强制执行一致性逻辑，添加所提出的不等式
The daily operation of real-world power systems and their underlying markets relies on the timely solution of the unit commitment problem. However, given its computational complexity, several optimization-based methods have been proposed to lighten its problem formulation by removing redundant line flow constraints. These approaches often ignore the spatial couplings of renewable generation and demand, which have an inherent impact of market outcomes. Moreover, the elimination procedures primarily focus on the feasible region and exclude how the problem’s objective function plays a role here. To address these pitfalls, we move to rule out redundant and inactive constraints over a tight linear programming relaxation of the original unit commitment feasibility region by adding valid inequality constraints. We extend the optimization-based approach called umbrella constraint discovery through the enforcement of a consistency logic on the set of constraints by adding the proposed inequality constraints to the formulation. Hence, we reduce the conservativeness of the screening approach using the available historical data and thus lead to a tighter unit commitment formulation. Numerical tests are performed on standard IEEE test networks to substantiate the effectiveness of the proposed approach.
论文链接：http://arxiv.org/pdf/2303.13322v1
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