Open Access
ARTICLE
The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology
Fuquan Huang1, Zijun Liu1, Tinghuang Wang1, Haitai Zhang2, *, Tony Yip3
1 Shenzhen Power Utility Co., Ltd., Shenzhen, 518000, China.
2 Shandong Kehui Electric Power Automation Co., Ltd., Zibo, 255000, China.
3 Kehui International Ltd., Studio 206, Mill Studio Business Centre, Crane Mead, Ware, Herts, SG12 9PY, UK.
* Corresponding Author: Haitai Zhang. Email: .
Computers, Materials & Continua 2020, 65(1), 865-878. https://doi.org/10.32604/cmc.2020.010724
Received 23 March 2020; Accepted 02 May 2020; Issue published 23 July 2020
Abstract
In order to quickly and accurately locate the fault location of the distribution
network and increase the stability of the distribution network, a fault recovery method
based on multi-objective optimization algorithm is proposed. The optimization of the
power distribution network fault system based on multiagent technology realizes fast
recovery of multi-objective fault, solve the problem of network learning and parameter
adjustment in the later stage of particle swarm optimization algorithm falling into the
local extreme value dilemma, and realize the multi-dimensional nonlinear optimization of
the main grid and the auxiliary grid. The system proposed in this study takes power
distribution network as the goal, applies fuzzy probability algorithm, simplifies the
calculation process, avoids local extreme value, and finally realizes the energy balance
between each power grid. Simulation results show that the Multi-Agent Technology
enjoys priority in restoring important load, shortening the recovery time of power grid
balance, and reducing the overall line loss rate of power grid. Therefore, the power grid
fault self-healing system can improve the safety and stability of the important power grid,
and reduce the economic loss rate of the whole power grid.
Keywords
Cite This Article
F. Huang, Z. Liu, T. Wang, H. Zhang and T. Yip, "The optimization study about fault self-healing restoration of power distribution network based on multi-agent technology,"
Computers, Materials & Continua, vol. 65, no.1, pp. 865–878, 2020. https://doi.org/10.32604/cmc.2020.010724
Citations