,gray fuzzy prediction, massive power data, task scheduling, storage block, scheduling priority ,"/> 基于灰色模糊预测的海量电力数据自动调度算法

吉林大学学报(信息科学版) ›› 2022, Vol. 40 ›› Issue (3): 437-443.

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基于灰色模糊预测的海量电力数据自动调度算法

向 颖1 , 余旭阳1 , 严慧峰1 , 许 轲2   

  1. 1. 国网湖南省电力有限公司 发展策划部, 长沙 410007; 2. 北京国电通网络技术有限公司 规划与计划管理业务事业部, 北京 100085
  • 收稿日期:2021-12-16 出版日期:2022-07-14 发布日期:2022-07-14
  • 作者简介:向颖(1972— ), 女, 长沙人, 国网湖南省电力有限公司高级经济师, 主要从事电网投资、 电力技经、 统计管理等研究, (Tel)86-13873131935(E-mail)kjxmabc@ 163. com。
  • 基金资助:
    国网湖南省电力有限公司供电服务中心基金资助项目(5700-202055484A-0-0-00)

Automatic Scheduling Algorithm for Massive Power Data Based on Grey Fuzzy Prediction

XIANG Ying1 , YU Xuyang1 , YAN Huifeng1 , XU Ke2   

  1. 1. Development Planning Department, State Grid Hunan Electric Power Company Limited, Changsha 410007, China; 2. Planning and Plan Management Business Division, Beijing Guodiantong Network Technology Company Limited, Beijing 100085, China
  • Received:2021-12-16 Online:2022-07-14 Published:2022-07-14

摘要: 针对当前调度算法调度电力系统中的海量数据时, 存在调度效率低、稳定性差的问题, 设计了一种基于灰色模糊预测的海量电力数据自动调度算法。 考虑电力系统任务调度实时性和可靠性, 制定电力任务调度策略。将调度任务的分析选择截止期与价值作为特征参数, 计算负载率衡量服务节点的实际负载情况, 完成电力系统的负载均衡分配。 运用灰色模糊预测算法对电力数据进行调度, 根据递进函数对单个存在的存储块未来趋势进行预测, 再结合任务的优先级, 实现海量电力数据的自动调度。实验结果表明, 所提算法能在短时间内使所有任务协同调度、 资源合理分配, 并保证数据平台处于稳定状态, 提高了数据调度效率, 增强了调度稳定性。

关键词: 灰色模糊预测, 海量电力数据, 任务调度, 存储块, 调度优先级

Abstract: In order to solve the problem of low efficiency and poor stability in dispatching massive data in power system, a scheduling algorithm of massive power data based on grey fuzzy prediction is designed. Considering the real-time and reliability of power system task scheduling, the power task scheduling strategy is formulated. The deadline and value of scheduling task are selected as characteristic parameters, and the load rate is calculated to measure the actual load of service nodes to complete the load balance distribution of power system. The grey fuzzy prediction algorithm is used to schedule the power data, the future trend of a single existing storage block is predicted according to the progressive function, and then combined with the priority of the task to realize the automatic scheduling of massive power data. The experimental results show that the proposed algorithm can make the collaborative scheduling and resource allocation in a short time, ensure the stable state of the data platform, improve the data scheduling efficiency and enhance the scheduling stability. 

Key words:  ')">

 , gray fuzzy prediction, massive power data, task scheduling, storage block, scheduling priority

中图分类号: 

  • TP399