Robust resilience enhancement strategy for gas-electricity integrated energy system considering multiple reinforcement levels

Shichao Zhou, Shuhan Luo,Lingling Wang,Chuanwen Jiang, Zhan Xiong, Jiu Gu, Ke Zhang

IET RENEWABLE POWER GENERATION(2024)

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摘要
Natural disasters are extreme events with low probability but strong destructive ability, which have a serious impact on the power system. The gas-electricity integrated energy system is more likely to be affected by natural disasters due to its complex multi-energy coupling characteristic. In order to improve the resilience of the gas-electricity integrated energy system under natural disasters, this paper proposes a three-layer defence-attack-defence robust resilience improvement model with the objective of minimizing the load loss in the gas-electricity integrated energy system. Firstly, in order to cope with various levels of disaster and improve the economy of line/pipeline reinforcement in the gas-electricity integrated energy system, a multi-level line/pipeline reinforcement model is proposed on the basis of load weight in the upper layer. Then, information entropy is introduced to represent the impact of natural disasters in the middle layer. Based on the operation constraints of the gas-electricity integrated energy system, the optimal allocation of the mobile electricity storage and liquefied gas storage is established in the lower layer. The three-layer resilience improvement model is solved by the nested column and constraint generation algorithm. Finally, the case study proves the feasibility of the model and the effectiveness of the solution method. In order to improve the resilience of the gas-electricity integrated energy system under natural disasters, this paper proposes a three-layer defence-attack-defence robust resilience improvement model with the objective of minimizing the load loss in the gas-electricity integrated energy system. image
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关键词
gas-electricity integrated energy system,multi-level reinforcement,natural disasters,resilience enhancement,robust optimization
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