基于图形的智能电网实时运行与控制解决方案

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Ayman M. O. Mohamed, Ramadan El-Shatshat
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引用次数: 0

摘要

在设想的智能电网模式下,配电系统运行和控制对快速、准确、高效的功率流解决方案的需求日益增长。目前已提出了各种解决方案技术,每种技术都有其独特的表述、解决方法、优势和缺点。受可再生分布式能源资源和电动汽车与配电系统集成相关挑战的激励,以及现有工具在速度和收敛性方面的限制,本文提出了一种基于图的新型功率流解决方案,用于智能电网的实时运行和控制,命名为 "Flow-AugmentationPF 算法"。所提方法将功率流问题表述为网络流问题,并受推标签最大流技术的启发,使用最大流算法来解决该问题。所提算法的性能通过几个不同规模、拓扑结构和参数的基准网络进行了测试和验证,并与最常用的求解技术和商业软件包(即 PSS/E 和 PSCAD)进行了比较。所提出的算法基于矩阵-向量乘法,简单、准确、快速且计算效率高,同时还具有可扩展性,因为该算法是一种基于图的方法,本质上允许并行计算以提高计算速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Graph-based solution for smart grid real-time operation and control

Graph-based solution for smart grid real-time operation and control

Under the envisioned smart grid paradigm, there is an increasing demand for a fast, accurate, and efficient power flow solution for distribution system operation and control. Various solution techniques have been proposed, each with its own unique formulation, solution methodology, advantages, and drawbacks. Motivated by challenges associated with the integration of renewable distributed energy resources and electric vehicles into distribution systems and further by the speed and convergence limitations of existing tools, this paper presents a novel graph-based power flow solution for smart grid's real-time operation and control, named Flow-AugmentationPF algorithm. The proposed method formulates a power flow problem as a network-flow problem and solves it by using a maximum-flow algorithm, inspired by the push-relabel max-flow technique. The performance of the proposed algorithm is tested and validated using several benchmark networks of different sizes, topologies, and parameters and compared against the most commonly used solution techniques and commercial software packages, namely PSS/E and PSCAD. The proposed formulation is simple, accurate, fast, yet computationally efficient, as it is based on matrix-vector multiplication, and is also scalable, considering the formulation works as a graph-based method, which, inherently, allows for parallel computation for added computational speed.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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