Title: Optimisation method of distribution network planning based on wireless communication and multimodal information learning

Authors: Jun Jiang; Jiwu Liu; Qingzhu Li; Yangfu Luo; Zixin Li

Addresses: Luzhou Power Supply Company State Grid Sichuan Power Supply Company, Luzhou 646000, China ' Luzhou Power Supply Company State Grid Sichuan Power Supply Company, Luzhou 646000, China ' Luzhou Power Supply Company State Grid Sichuan Power Supply Company, Luzhou 646000, China ' Luzhou Power Supply Company State Grid Sichuan Power Supply Company, Luzhou 646000, China ' Luzhou Power Supply Company State Grid Sichuan Power Supply Company, Luzhou 646000, China

Abstract: In this article, a new dispatching method was proposed based on the power demand and the existing problems in the current distribution network planning. Through physical communication, data interaction and communication between multiple nodes were achieved, which provided users with a more convenient and comfortable electricity experience. The intelligent optimisation algorithm can carry out planning calculation and decision-making by itself according to the user's use, the planning can run more accurately and reasonably, and has strong performance. According to the mathematical model of intelligent optimisation algorithm, the distribution network planning problem has been solved efficiently. The application of wireless communication and intelligent optimisation algorithm in distribution network planning can not only decrease the cost of existing schemes and operation and management costs but also improve the network computing efficiency, which decreases the workload of operation and maintenance personnel and enables lines and distribution equipment to truly play their due role.

Keywords: distribution grid; wireless communication; intelligent optimisation algorithm; physical communication.

DOI: 10.1504/IJIIDS.2025.147434

International Journal of Intelligent Information and Database Systems, 2025 Vol.17 No.3/4, pp.516 - 534

Received: 13 May 2024
Accepted: 05 Nov 2024
Published online: 15 Jul 2025 *

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