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| Resilience Enhancement Strategy for Distribution Networks Considering the Spatiotemporal Characteristics of Typhoon and the Collaborative Optimization of Flexible Resources |
| Xiao Juanxia1, Li Yong1, Han Yu1, Qiao Xuebo2, Zhong Junjie1 |
1. School of Electrical and Information Engineering Hunan University Changsha 410082 China;
2. Southern Power Grid Research Institute Co. Ltd Guangzhou 510663 China |
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Abstract Enhancing the resilience of distribution networks is an urgent task to resist the frequent typhoon disasters. Generally, typhoon has the spatiotemporal characteristics, which causes the uncertainty of distribution network failures. However, the current researches ignore this feature and fail to deeply analyze the principle of distribution network failure caused by typhoon. Moreover, most of them overlook the potential of flexible resources in enhancing the resilience of distribution networks. To address these issues, this paper proposes a resilience enhancement strategy that takes into account the spatiotemporal characteristics of typhoon and the coordinated optimization of flexible resources.
Firstly, a spatiotemporal evolution model of typhoon is constructed using the typhoon path model and the Batts wind field model, which is capable of simulating the moving path and wind field of typhoon in real time. Secondly, according to the principle of structural reliability, the time-varying failure probability of distribution lines can be obtained by comparing the strength of line components with load effects. On this basis, the information entropy theory is used to identify fragile lines. Then, a two-stage and three-layer defense-attack-defense (DAD) model combining pre-disaster defense and post-disaster restoration is established, with the load shedding cost as the resilience quantification indicator. In the proposed model, flexible resources such as line hardening, distributed generation (DG), energy storage system (ESS), and soft open point (SOP) are coordinated to enhance the resilience of distribution networks. The proposed model can reflect the uncertain effects of typhoon spatiotemporal characteristics on the time, location and scale of distribution network failures. Meanwhile, flexible resources can be fully utilized to enhance the resilience of distribution networks.
In the numerical test section, two aspects of typhoon simulation and flexible resources performance analysis are tested. In the test of typhoon simulation, the numerical results show that the proposed spatiotemporal evolution model of typhoon is able to simulate the moving path and wind field of typhoon after landfall. Moreover, the failure probability of distribution lines is affected by various factors, such as line length, the angle between the line and the wind speed, the line location coordinates, and the distance between the line and the typhoon center. Besides, the typhoon with spatiotemporal characteristics causes different locations and quantities of distribution line failures at different periods. Several comparison schemes are developed to test the performance of flexible resources in enhancing the resilience of distribution networks. The numerical results show that the number of line hardening and the installation number of DG/ESS/SOP affect the resilience of distribution networks. Compared with the scheme without any optimization measures, the de-energized loads obtained by the optimization scheme considering the coordination of flexible resources is reduced by 97%, and all the de-energized loads are third priority loads.
The following conclusions can be drawn from the study: (1) The proposed spatiotemporal evolution model of typhoon and the fault model of distribution line can effectively simulate the internal mechanism of the influence of typhoon on the failure probability of distribution lines. (2) In terms of resilience enhancement effects, the deployments of DG and SOP are better than line hardening and BSS measure. (3) The coordination of flexible resources greatly reduces the amount of de-energized loads and enhances the resilience of distribution networks compared with the optimization schemes that use only a single measure.
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Received: 12 October 2023
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2024, Vol. 39 
