Power system state estimation method based on denoising diffusion probability model data generation and multi-source data fusion

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research Pub Date : 2025-10-04 DOI:10.1016/j.epsr.2025.112302

Maosong Zhang , Xudong Zhu , Lingxiao Yang , Jie Yang

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引用次数: 0

Abstract

State estimation is fundamental for power system situational awareness but faces challenges of data scarcity, heterogeneous data fusion difficulties, and limited accuracy. This study proposes a novel state estimation method integrating Denoising Diffusion Probabilistic Models (DDPM) with multi-source data fusion. Firstly, we constructed a DDPM data generation model with embedded physical constraints, thereby effectively addressing the issue of data scarcity. Secondly, a weighted fusion strategy based on credibility was designed to integrate heterogeneous data sources. Finally, a least squares estimation algorithm based on dynamic decoupling and adaptive fusion was proposed, which improved the performance of state estimation. The IEEE 57-node system test shows that this method achieves a better balance between data quality generation and training cost. The state estimation error after integrating multi-source data is lower, and the convergence speed is 33% faster. In the presence of noise and data missing, the errors are reduced by 51% and 63% respectively.

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基于去噪扩散概率模型数据生成和多源数据融合的电力系统状态估计方法

状态估计是电力系统态势感知的基础，但存在数据稀缺性、异构数据融合困难和准确性有限等问题。提出了一种将去噪扩散概率模型（DDPM）与多源数据融合相结合的状态估计方法。首先，我们构建了具有嵌入式物理约束的DDPM数据生成模型，从而有效地解决了数据稀缺性问题。其次，设计了基于可信度的加权融合策略，实现了异构数据源的融合。最后，提出了一种基于动态解耦和自适应融合的最小二乘估计算法，提高了状态估计的性能。IEEE 57节点系统测试表明，该方法在数据质量生成和训练成本之间取得了较好的平衡。多源数据融合后的状态估计误差更小，收敛速度提高33%。在存在噪声和数据缺失的情况下，误差分别降低了51%和63%。

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来源期刊

Electric Power Systems Research 工程技术-工程：电子与电气

CiteScore

7.50

自引率

17.90%

发文量

963

审稿时长

3.8 months

期刊介绍： Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview. • Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation. • Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design. • Substation work: equipment design, protection and control systems. • Distribution techniques, equipment development, and smart grids. • The utilization area from energy efficiency to distributed load levelling techniques. • Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.