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Regular Paper | Open Access

Risk Assessment for Hybrid AC/DC Systems Based on Transient Energy Function

Peng Sun1, Yun Teng1 ( ), Mingli Zhang2, Zhe Chen3
Shenyang University of Technology, Shenyang 110870, China
Liaoning Electric Power Co. Ltd. Economic Research Institute, Shenyang 110000, China
Department of Energy Technology, Aalborg University, Aalborg, DK DK 9220
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Abstract

In order to accurately assess the risk of the hybrid AC/DC network under fault, a risk assessment method for the hybrid AC/DC system based on the transient energy function is proposed. First, based on the energy transfer relationship of the hybrid AC/DC power system, the transient energy function model of the hybrid AC/DC system is established. Based on the operating data of the power grid, the energy function is used as an efficiency variable, and the efficiency variable is integrated into the prior risk probability calculation of nodes in the network, and a Bayesian network-based risk assessment model of hybrid AC/DC system is established. Considering the dynamic update model of network cascading failures, the clique tree propagation algorithm is used to dynamically calculate the posterior risk probability of the node to realize the dynamic assessment of the network risk. Finally, the improved IEEE-39 node hybrid AC/DC system is used as an example for analysis. The results show that the proposed model can not only effectively evaluate the overall safety of the network, but also has feasibility in predicting faults, which can provide a theoretical basis for the stability control of the hybrid AC/DC system.

Keywords

Cascading failureenergy functionhybrid AC-DC systemrisk assessment

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CSEE Journal of Power and Energy Systems
Volume 10 Issue 4,
July 2024
Pages 1654-1663
DOI: 10.17775/CSEEJPES.2021.00860
Cite this article:
Sun P, Teng Y, Zhang M, et al. Risk Assessment for Hybrid AC/DC Systems Based on Transient Energy Function. CSEE Journal of Power and Energy Systems, 2024, 10(4): 1654-1663. https://doi.org/10.17775/CSEEJPES.2021.00860

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Received: 01 February 2021
Revised: 07 March 2021
Accepted: 27 April 2021
Published: 13 November 2021
© 2021 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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