Dr. Guanglong Xie Profile

Dr. Guanglong Xie

at State Grid Energy Research Institute Co., Ltd

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Proceedings Article | 25 April 2022 Paper

Resilience evaluation method of multi-energy coupled distribution networks under extreme events

Xubin Wang, Jun Zhang, Guanglong Xie

Proceedings Volume 12244, 122445H (2022) https://doi.org/10.1117/12.2634825

KEYWORDS: System integration, Power supplies, Lawrencium, Integration, Quantum efficiency, Resistance, Natural disasters, Composites, Computer simulations, Quantitative analysis

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Frequent extreme natural disasters and man-made attacks have a great impact on the safe and stable operation of multienergy coupled distribution system, resulting in large-scale and long-term power loss of lifeline load. How to consider the whole process of extreme events and accurately evaluate the power loss of multi-energy system load and restore power supply has become an urgent problem to be solved. Aiming at the problem that the multi energy coupling relationship and the whole process of extreme events are not considered in the existing toughness evaluation of multi energy coupled distribution system, a toughness evaluation method of multi energy coupled distribution system considering the whole process of extreme events is proposed in this paper. Considering the whole process of extreme events, a hierarchical evaluation index system of multi energy coupled distribution system including pre disaster bearing capacity and post disaster recovery capacity is proposed; on this basis, the loss speed, loss degree, recovery speed and recovery degree of multi-energy load are quantitatively analyzed. Through the simulation test of the actual multi energy coupled distribution system, the evaluation effect of the proposed multi energy coupled distribution system toughness evaluation method on the whole process load loss and post disaster recovery effect of extreme events is verified, which provides a reliable basis for the formulation of toughness improvement strategy of multi energy coupled distribution network under extreme events.

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