Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 1


Published
on

December 27, 2021


Pages

685-694


DOI

Article

Distribution network monitoring and management system based on intelligent recognition and judgement


Authors

Yiwei Xue Affiliation:
Guangzhou Huangpu Power Supply Bureau of Guangdong Power Grid Co. Ltd, Guangdong Guangzhou 510000, China
, Qizhen Sun Affiliation:
Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd, Guangdong Guangzhou 510000, China
, Chendi Li Affiliation:
Guangzhou Huangpu Power Supply Bureau of Guangdong Power Grid Co. Ltd, Guangdong Guangzhou 510000, China
, Weijun Dang Affiliation:
Guangzhou Huangpu Power Supply Bureau of Guangdong Power Grid Co. Ltd, Guangdong Guangzhou 510000, China
and Fangzhou Hao Affiliation:
Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd, Guangdong Guangzhou 510000, China


Abstract

Based on the shortcomings of the current intelligent management of distribution networks, the article designs and implements a remote intelligent detection system for live distribution networks. The article constructs and realises an algorithm based on a genetic algorithm (GA) and agent system. The algorithm is applied to energy-saving intelligent supervision of equipment in the distribution network. The simulation experiment shows that the integrated algorithm based on GA and agent system can accurately detect power quality in real time. At the same time, the algorithm can monitor the energy consumption of equipment in the distribution network under multiple disturbances.


Keywords

intelligent identification and judgement, distribution network, energy saving and consumption reduction, monitoring management, genetic algorithm, 17D92


Citation

Xue, Y., Sun, Q., Li, C., Dang, W., & Hao, F. (2021). Distribution network monitoring and management system based on intelligent recognition and judgement. Applied Mathematics and Nonlinear Sciences, 6(1), 685–694. https://doi.org/10.2478/amns.2021.1.00057

Published by: Engineering Journals

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