Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 7, Issue 2


Published
on

July 15, 2022


Pages

1037-1044


DOI

Article

Power Flow Calculation in Smart Distribution Network Based on Power Machine Learning Based on Fractional Differential Equations

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Authors

Yuan Ji Affiliation:
Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China
, Jie Yuan Affiliation:
Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China
, Junfeng Qian Affiliation:
Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China
, Liya Huang Affiliation:
Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China
and Moaiad Ahmad Khder Affiliation:
College of Arts & Science, Applied Science University, Bahrain


Abstract

Based on the theory of fractional differential equations, this paper proposes a simple recursive, iterative scheme for power flow calculation in pure radial networks. The paper determines the network hierarchy formed by the ADT stack through breadth theory. This helps us define the branch sequence of the forward and backward generation in the power flow calculation of the smart distribution network. We ensure that the Jacobian matrix remains unchanged in the smart distribution grid power flow calculation. The interval model is more practical and computationally simpler than the point model. The research results show that the power flow calculation method is efficient based on the fractional differential equation.


Keywords

Fractional differential equation, Power distribution network, Power flow calculation, Smart grid, Machine learning, 34A08


Citation

Ji, Y., Yuan, J., Qian, J., Huang, L., & Khder, M. A. (2022). Power flow calculation in smart distribution network based on power machine learning based on fractional differential equations. Applied Mathematics and Nonlinear Sciences, 7(2), 1037–1044. https://doi.org/10.2478/amns.2022.2.0187

Published by: Engineering Journals

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