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

被引:0
|
作者
Mohamed, Ayman M. O. [1 ]
El-Shatshat, Ramadan [2 ]
机构
[1] Univ Benghazi, Elect & Elect Engn Dept, Benghazi, Libya
[2] Univ Waterloo, Elect & Comp Engn Dept, Waterloo, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
graph theory; load flow; smart power grids; LOAD-FLOW; NETWORK RECONFIGURATION; DISTRIBUTION-SYSTEM;
D O I
10.1049/gtd2.13094
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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. This article presents a versatile graph-based method for power system operation and control. The proposed method is suitable for real-time smart grid operation with high supply-demand variability. This method is simple, efficient, and fast in comparison with existing methods. image
引用
收藏
页码:1971 / 1979
页数:9
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