面向配电网故障快速处理的边缘计算单元优化配置方法

doi:10.12204/j.issn.1000-7229.2022.03.004

摘要/Abstract

摘要：

随着配电网自动化水平不断提高,感知终端数目和接入数据量激增,数据传输慢、信息漏报误报等问题严重影响了故障处理速度和准确性。边缘计算可就地高效地快速处理数据并决策。为此,提出一种面向配电网故障快速处理的边缘计算单元优化配置方法,包括体系架构、边缘生成、划分方法等内容。首先以经济性、通信实时性指标构造目标函数,可靠性及系统要求等为约束求解实际配网中边缘的最优个数。再通过谱聚类结合k-means算法划分边缘管辖范围和位置分布,根据分区均衡性、实际要求等修正分区。最后以IEEE 33节点、IEEE 69节点系统进行算例验证,并基于Matlab/Simulink建立模型进行故障仿真,与传统方法对比表明该法能够实现配电网故障的正确快速处理,有效保障了配电网安全稳定运行。

关键词: 配电网, 故障处理, 边缘计算, 优化配置, 边缘划分

Abstract:

With the continuous improvement of the automation level of distribution network, the sensing terminals and access data have increased sharply. Problems such as slow data transmission and information missing and false alarms have seriously affected the speed and accuracy of fault handling. Edge computing can quickly and efficiently process data and make decisions on the spot. To this end, an optimized configuration method of edge computing units for rapid processing of distribution network faults is proposed, including system architecture, edge generation, and division methods. Firstly, the objective function is constructed by economic and communication real-time indicators, and reliability and system requirements are constraints to solve the optimal number of edge. Then, spectral clustering combined with k-means algorithm is used to divide the jurisdiction and location of edge, and partitions are modified according to balance and actual requirements. Finally, the IEEE 33-node and IEEE 69-node systems are verified as examples. The fault simulation model based on Matlab/Simulink is established. Compared with traditional methods, this method can deal with distribution network faults correctly and quickly, and effectively guarantee the safe and stable operation of distribution network.

Key words: distribution network, fault handling, edge computing, optimal configuration, edge division

中图分类号:

TM73

潘思宇, 刘宝柱. 面向配电网故障快速处理的边缘计算单元优化配置方法[J]. 电力建设, 2022, 43(3): 31-41.

PAN Siyu, LIU Baozhu. Optimal Configuration Method of Edge Computing Units forRapid Faults Processing in Distribution Network[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(3): 31-41.

图/表 15

图1 边缘计算体系架构

Fig.1 Architecture of edge computing

图2 边缘计算工作策略

Fig.2 Working strategy of edge computing

图3 边缘生成流程

Fig.3 Edge generation process

图4 开、断24-28联络开关分区情况对比

Fig.4 Zoning comparison when 24-28 liaisonswitch open and closed

图5 IEEE 33节点系统聚类结果

Fig.5 Clustering results of IEEE 33-node system

图6 IEEE 33节点系统分区结果(修正前)

Fig.6 Zoning results of IEEE 33-node system(before revision)

图7 IEEE 33节点系统分区结果(修正后)

Fig.7 Zoning results of IEEE 33-node system(after correction)

表1 IEEE 33节点系统均衡性

Table 1 Balance of IEEE 33-node system

图8 IEEE 69节点系统聚类结果

Fig.8 Clustering results of IEEE 69-node system

图9 IEEE 69节点系统分区结果(修正前)

Fig.9 Zoning results of IEEE 69-node system (before revision)

图10 IEEE 69节点系统分区结果(修正后)

Fig.10 Zoning results of IEEE 69-node system (after revision)

图11 A相电流电压波形对比

Fig.11 Comparison of A-phase current andvoltage waveforms

表2 传统模式与本文模式平均排队时间

Table 2 Average queuing time of traditionalmodel and the proposed model

表3 传统模式与本文模式故障处理总时间(区域1)

Table 3 Total time for fault processing in traditional mode and the proposed mode (area 1)ms

表4 传统模式与本文模式故障处理总时间(区域3)

Table 4 Total time for fault processing in traditional mode and the proposed mode (area 3)ms

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