基于电力大数据的电力骨干通信网络毁伤韧性评估方法

韩雪

doi:10.11959/j.issn.1000-0801.2023105

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基于电力大数据的电力骨干通信网络毁伤韧性评估方法

研究与开发 | 更新时间：2024-06-05

- 基于电力大数据的电力骨干通信网络毁伤韧性评估方法
- Damage toughness assessment method of power backbone communication network based on power big data
- 电信科学 2023年39卷第5期页码：136-143
- 作者机构：
- 作者简介：
  
  [ "韩雪（1993- ），女，国家电网内蒙古东部电力有限公司信息通信分公司工程师，主要研究方向为人工智能与人机对抗、电力大数据分析及应用等" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2023105
  中图分类号： TM76
- 网络出版日期：2023-05，
  
  纸质出版日期：2023-05-20
- 稿件说明：
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韩雪. 基于电力大数据的电力骨干通信网络毁伤韧性评估方法[J]. 电信科学, 2023,39(5):136-143.

Xue HAN. Damage toughness assessment method of power backbone communication network based on power big data[J]. Telecommunications science, 2023, 39(5): 136-143.
韩雪. 基于电力大数据的电力骨干通信网络毁伤韧性评估方法[J]. 电信科学, 2023,39(5):136-143. DOI： 10.11959/j.issn.1000-0801.2023105.

Xue HAN. Damage toughness assessment method of power backbone communication network based on power big data[J]. Telecommunications science, 2023, 39(5): 136-143. DOI： 10.11959/j.issn.1000-0801.2023105.

摘要

研究了基于电力大数据的电力骨干通信网络毁伤韧性评估方法，利用毁伤韧性评估结果制定保护策略，提升网络的生存能力。将电力骨干通信网络与攻击方设为博弈双方，利用极大极小法确定双方的纳什均衡策略，利用纳什均衡策略获取节点的毁伤概率，将节点毁伤概率转化为网络破坏形态。针对网络破坏形态，利用云计算技术调取电力大数据中包含的修复条件，依据各节点重要度为节点分配修复资源以及修复预算，构建电力骨干通信网络的性能时程响应曲线，输出网络毁伤韧性的动态评估结果。实验结果表明，利用云计算技术处理海量电力大数据的所有操作时间不超过 330 ms，当修复预算与修复资源均为最高时，电力骨干通信网络的毁伤韧性最高可达0.925，说明该方法可以有效评估电力骨干通信网络的毁伤韧性。

Abstract

The damage toughness assessment method of power backbone communication network based on power big data was studied

and the damage toughness assessment results were used to formulate protection strategies and improve the network survivability.The power backbone communication network and the attacker were set as the two sides of the game

and the Nash equilibrium strategy of both sides was determined by the minimax method.The damage probability of nodes was obtained by the Nash equilibrium strategy

and the node damage probability was transformed into the network damage form.According to the network damage pattern

the repair conditions contained in the power big data were obtained by cloud computing technology.According to the importance of each node

the repair resources and repair budget were allocated to the nodes in order.The performance time-history response curve of the power backbone communication network was constructed

and the dynamic evaluation results of the network damage toughness were output.The experimental results show that all operations using cloud computing technology to process massive power big data can not exceed 330 ms.When the repair budget and repair resources are the highest

the damage toughness of the power backbone communication network can reach 0.925 at most

indicating that this method can effectively evaluate the damage toughness of the power backbone communication network.

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