Abstract
With the continuous advancement of energy transition and the application of advanced mature technologies such as cloud computing, big data, the Internet of Things, mobile Internet, artificial intelligence, blockchain, etc., the electric power dispatch automation system has become increasingly vast and complex.In R&D construction of new generation operation supporting systems, as the core of the system construction and operation, the reliability and robustness evaluation of the support platform is particularly crucial. Given the limitations and challenges in testing and fault injection methods for large-scale complex systems, we propose a multipoint heterogeneous testing method based on complex networks. By abstracting the support platform as a complex network model and adopting the importance calculation based on the Laplacian matrix as the fault injection selection strategy, multi-point heterogeneous concurrent fault injection is realized. A networked distributed fault injection test system is designed, enabling dynamic monitoring and assessment of system states. Using the support platform in a test environment as the testing subject, and selecting dual-active center data synchronization as a typical scenario, single-point, dual-point, and three-point concurrent testing experiments are conducted based on different node selection strategies to validate the effectiveness of the proposed method. Experimental results indicate that, compared with degree matrix and betweenness centrality matrix, the fault injection strategy based on the Laplacian matrix causes the most significant degradation in two key testing metrics of platform dual-active synchronization timeliness and data consistency. This method proves to be more efficient in identifying system vulnerabilities, providing effective technical means for enhancing the robustness and resilience of the support platform.
| Translated title of the contribution | Research on Complex Networks Multi-point Heterogeneous Testing Method for Support Platform of New Generation Operation Supporting System |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 3020-3030 |
| Number of pages | 11 |
| Journal | Dianwang Jishu/Power System Technology |
| Volume | 49 |
| Issue number | 7 |
| DOIs | |
| State | Published - 5 Jul 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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