基于优化蚁群算法的电缆敷设路径规划
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1.国网河南省电力公司经济技术研究院;2.上海电力大学电气工程学院 上海市 杨浦区

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国家自然科学基金项目(61873159,基于多储能调节的多源直流微电网鲁棒协调控制及稳定性研究)


Cable laying path planning based on optimized ant colony algorithm
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1.Economic and Technological Research Institute of State Grid Henan Electric Power Company,Henan Province,Zhengzhou City;2.Shanghai Electric Power University of electrical engineering,Shanghai,Yangpu District

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    摘要:

    针对基于传统手工设计的电缆敷设存在误差大和效率低等问题,将蚁群算法优化的计算机辅助设计应用到电缆敷设路径规划中。利用蚁群算法在复杂线路中多端点的线路计算优势,解决电缆敷设的最短路径问题。同时,本文将电缆敷设路径平面化,进一步利用Gompertz函数从信息素限定和挥发因子自适应调整两方面进行优化,提高了蚁群算法的收敛速度和全局性。仿真试验表明,优化的蚁群算法在变电站数字化三维电缆敷设过程能够快速得出最短电缆敷设路径,节省人力物资成本,提高了设计精度。

    Abstract:

    Aiming at the problems of large error and low efficiency in cable laying based on traditional manual design, the computer-aided design optimized by ant colony algorithm is applied to cable laying path planning. The ant colony algorithm (ACA) is used to solve the shortest path problem of cable laying by taking advantage of the advantages of multi terminal line calculation in complex lines. At the same time, this paper planarizes the cable laying path, and further optimizes it by using Gompertz function from two aspects: pheromone restriction and self-adaptive adjustment of volatilization factor, which improves the convergence speed and global performance of ant colony algorithm. The simulation results show that the optimized ant colony algorithm can quickly get the shortest cable laying path in the process of substation digital three-dimensional cable laying, save the cost of manpower and materials, and improve the design accuracy.

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历史
  • 收稿日期:2022-01-04
  • 最后修改日期:2022-06-01
  • 录用日期:2022-06-06
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