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arXiv 2207.04896eess.SYcs.SY
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光滑互补条件求解双层AC OPF问题--第一部分:模型描述与算法

Solving Bilevel AC OPF Problems by Smoothing the Complementary Conditions -- Part I: Model Description and the Algorithm

Karlo Šepetanc, Hrvoje Pandžić, Tomislav Capuder

摘要:

现有的研究市场价格的影响因素,即价格制定者,忽略或简化的电力系统中的交流潮流的性质,因为它主要依赖于直流潮流。本文提出了一种新的双层制定的平滑技术的基础上,其中任何价格影响的战略球员可以在上层建模,而在较低的水平上的市场出清问题使用凸二次输电交流最优潮流(AC OPF),与目标是实现精度接近的精确的非线性配方之一。在较低的层次上实现凸性是双层建模的基础,因为传统的单级约简技术不适用于非凸模型。将下层具有AC最优潮流的双层市场参与问题转化为单层问题,并采用原对偶、强对偶定理、McCormick包络、互补松弛、惩罚因子、交互离散化以及平滑技术等多种技术进行求解.由于广泛的信息量和描述,整体工作作为一个两部分的文件。这第一部分提供了一个文献综述,定位工作,并提出了模型和解决方案的算法,而解决方案的技术和案例研究中提供的随附文件。

英文摘要:

The existing research on market price-affecting agents, i.e. price makers, neglects or simplifies the nature of AC power flows in the power system as it predominantly relies on DC power flows. This paper proposes a novel bilevel formulation based on the smoothing technique, where any price-affecting strategic player can be modelled in the upper level, while the market clearing problem in the lower level uses convex quadratic transmission AC optimal power flow (AC OPF), with the goal of achieving accuracy close to the one of the exact nonlinear formulations. Achieving convexity in the lower level is the foundation for bilevel modeling since traditional single-level reduction techniques do not hold for nonconvex models. The bilevel market participation problem with the AC OPF formulation in the lower level is transformed into a single-level problem and solved using multiple techniques such as the primal-dual counterpart, the strong duality theorem, the McCormick envelopes, the complementary slackness, the penalty factor, the interaction discretization as well as the proposed smoothing techniques. Due to an extensive amount of information and descriptions, the overall work is presented as a two-part paper. This first part provides a literature overview, positions the work and presents the model and the solution algorithm, while the solution techniques and case studies are provided in the accompanying paper.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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