基于云计算平台的0.4kV低压带电作业任务调度与资源优化算法的研究
Research on Task Scheduling and Resource Optimization Algorithm for 0.4 kV Low-Voltage Live Working Based on Cloud Computing Platform
张小江 1王荔明 1田世芳1
作者信息
- 1. 国网甘肃省电力公司白银供电公司,甘肃白银 730900
- 折叠
摘要
针对电力系统维护中低压带电作业的复杂性和高风险性,提出了一种综合考虑资源利用率和任务完成率的优化模型.该模型以最大化资源利用率和任务完成率为目标,通过引入烟花算法等优化算法,实现了任务的高效调度和资源的合理分配.结果表明,所提算法在提高作业效率的同时,能有效降低带电作业的安全风险,具有良好的实用性和可行性.
Abstract
A comprehensive optimization model considering resource utilization and task completion rate is proposed to address the complexity and high risk of low-voltage live work in power system maintenance.The model aims to maximize resource utilization and task completion rate,and achieves efficient task scheduling and reasonable resource allocation by introducing optimization algorithms such as fireworks algorithm.The results show that the proposed algorithm can effectively reduce the safety risks of live working while improving work efficiency,and has good practicality and feasibility.
关键词
云计算平台/0.4kV低压带电作业/任务调度/资源优化Key words
cloud computing platform/0.4 kV low-voltage live work/task scheduling/resource optimization引用本文复制引用
出版年
2024
NETL
NSTL
万方数据