高压输电线路工程设计若干问题研究

随着国民经济快速增长,各地电网建设迅猛发展,如何应对新形势,最大限度地满足电网建设需要已成为技术部门不断研究的课题。文章从设计角度围绕方便施工、降低造价、利于运行等方面,对输电线路设计中应注意的问题进行了探讨。

基于电力线路工程设计的路线选择方案分析

近些年我国的电力工程有了快速发展,电力线路工程的规模在不断扩大,面对的环境越来越复杂,这也对线路工程设计提出了更多的挑战。因此需要在线路工程设计中制定出相应的路线选择方案,同时按照工程具体情况进行设计方案的优化,最终选择出最佳路线方案,确保电力工程的顺利实施。

现行《通信线路工程设计规范》相关标准商榷

原架空光缆线路工程设计规范带有原明线线路规范的深刻烙印,对架空光缆线路工程建设带来极大的困难,造成极大的浪费。现行GB51158—2015《通信线路工程设计规范》仍然有不符合光缆线路工程实际的错误,应当进行讨论并予以纠正。本文将对明线线路规范和光缆线路规范进行对比分析,对现行规范中的错误提出解决方案。

西二线枣阳—十堰支干线线路工程设计要点

枣阳—十堰支干线经过湖北省8个县市区,沿途地形复杂多变、地质情况复杂,地质灾害发育,环境敏感点和地方规划众多,设计难度和施工难度极大,文章针对路由选线、管材选择、敷设方式、地质灾害处理、水工保护等方面进行了总结,并论述了管线与地方规划的关系。

基于电力线路工程设计的路线选择方案分析

电力行业的发展直接关系到我国整体经济建设的发展速度和发展走向,在我国电力行业发展中,对于电力线路工程设计来说, 线路路径方案的选择是最为基础、最为核心的内容,路径方案的合理性直接影响着整个线路工程的安全性、投入费用以及运行情况。路线 选择方案的制定会受到地质、水文、气象以及生态环境等多方面因素的影响,随着近些年来我国经济的快速提升以及电力规模的不断扩大, 电力线路选线所面对的外部环境越来越复杂,涉及到的避让设施不断增加,要充分分析线路工程设计的路线选择方案,确保其科学性、合 理性,进一步推动电力工程的发展。

Multi-Objective Genetic Algorithm to Design Manufacturing Process Line Including Feasible and Infeasible Solutions in Neighborhood

This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.