基于多源信息融合的有源配电网故障信息治理方法-电气工程与自动化-CSCIED科技核心评价数据库-手机版

基于多源信息融合的有源配电网故障信息治理方法

Active distribution network outage information fusion governance method based on multi-source information fusion

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DOI	10.12208/j.jeea.20250067
刊名	电气工程与自动化 Journal of Electrical Engineering and Automation
年，卷(期)	2025, 4(2)
作者	葛辉^1,2,3, 过祈睿¹, 胡国洋¹, 刘程子¹, 徐俊俊¹, 邹德龙²,
作者单位	1 南京邮电大学自动化学院、人工智能学院江苏南京 2 国电南瑞科技股份有限公司江苏南京 3 南京邮电大学碳中和先进技术研究院江苏南京
摘要	为实现“双碳”战略目标，分布式能源迅猛发展并广泛接入到配电网，导致有源配电网的网络结构和运行环境更加复杂，影响系统安全稳定运行的故障迅速飙升，加之故障信息多源异构的特性，使故障溯源面临巨大挑战。针对上述问题，本文提出了一种基于改进D-S证据融合理论（Dempster-Shafer evidence theory）的有源配电网多源故障信息融合治理方法。首先，基于多模态的分析数据，确立特征层融合策略以突破传统数据级融合的计算复杂度瓶颈；其次，针对开关量信息与电气量信息的时频域特性差异，构建小波变换驱动的电气量特征提取模型，充分发挥其时频局部化表征优势；随后基于D-S证据理论融合算法改进融合规则，量化处理多源证据间的矛盾关系，以充分考虑各个证据源间的矛盾情况；最终对特征数据进行融合，为故障诊断提供多维信息支撑。基于IEEE-39网络与实际网络作为算例进行仿真验证，结果表明相较于传统组合规则，本文方法所得到的融合结果综合准确率有所提升，可高效、准确地表征信息采集系统所收集到的电气量信息，为有源配电网运维系统故障信息诊断、定位以及决策响应等提供有力支撑。
Abstract	To achieve the "dual-carbon" strategic goals, the rapid development and extensive integration of distributed energy resources (DERs) into power distribution networks have resulted in increasingly complex topological structures and operational environments for active distribution networks. This complexity has led to a surge in system faults that threaten grid security and stability. Coupled with the multi-source heterogeneous nature of fault information, these challenges significantly impede effective fault traceability. Addressing these issues, this paper proposes a multi-source fault information fusion governance method for active distribution networks based on an improved Dempster-Shafer (D-S) evidence theory. The methodology establishes a technical framework encompassing "feature dimension reduction-information representation-rule optimization-decision fusion". First, leveraging multimodal analytical data, a feature-level fusion strategy is established to circumvent the computational complexity bottlenecks inherent in conventional data-level fusion approaches. Second, recognizing the distinct time-frequency characteristics between switching quantity information and electrical quantity information, a wavelet transform-driven feature extraction model is constructed for electrical quantities, harnessing its inherent advantages in time-frequency localized representation. Subsequently, the D-S evidence fusion rules are innovatively redesigned through dynamic conflict factor correction mechanisms to quantitatively resolve contradictions among multi-source evidence. The final fusion decision vector provides multidimensional information support for fault diagnosis. Simulation validations conducted on both the IEEE-39 standard network and practical distribution networks demonstrate that compared with traditional combination rules, the proposed method achieves a 12.3% improvement in comprehensive accuracy while reducing feature extraction time consumption by 42%. The fusion results precisely characterize the dynamic electrical quantity information collected by monitoring systems, offering robust technical support for fault diagnosis, localization, and decision-making responses in active distribution network operation and maintenance systems. This research advances the field of multi-source heterogeneous information fusion through innovative rule design and computational architecture optimization, providing a novel technical paradigm for intelligent grid fault management.
关键词	改进证据理论；多源信息融合；暂态特征提取；配电网停电故障
KeyWord	Improved evidence theory; Multi-source information fusion; Transient feature extraction; Distribution network outage fault
基金项目
页码	133-144

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引用本文

葛辉^,,, 过祈睿, 胡国洋, 刘程子, 徐俊俊, 邹德龙. 基于多源信息融合的有源配电网故障信息治理方法 [J]. 电气工程与自动化. 2025; 4; (2). 133 - 144.

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