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Research on Strategies to Enhance the Resilience of Urban Power-Transportation Systems by Considering Mobile Energy Storage in Severe Sandstorm Environments
One-line summary
A solar energy research paper on Research on Strategies to Enhance the Resilience of Urban Power-Transportation Systems by Considering Mobile Energy Storage in Severe Sandstorm Environments.
Engineering notes
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Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
With the increasing frequency of extreme weather events, the vulnerability of urban power-transportation systems in severe dust storm conditions has become increasingly apparent. Addressing the shortcomings of existing research regarding the quantitative assessment and enhancement of system resilience, this paper proposes a set of strategies and methods for evaluating and improving the resilience of urban power-transportation systems under severe dust storm conditions, taking mobile energy storage into account. The study first establishes a multidimensional failure probability model for severe dust storm conditions: on the power grid side, it comprehensively considers fluctuations in renewable energy output, wind speed variations, and line insulation performance to propose a probabilistic failure model that accounts for the sand accumulation effect; on the transportation side, it considers road visibility and traffic flow to propose an improved BPR traffic flow model, using the Floyd algorithm to plan MES travel routes. Fault scenarios are generated using the Monte Carlo algorithm, and multidimensional system performance metrics for the power grid–road network-coupled nodes are established. A quantification method for resilience metrics applicable to urban power-transportation systems is proposed based on the ΦΛEΠ resilience index. Furthermore, a multi-objective, multi-stage resilience enhancement strategy for urban power-transportation systems that incorporates mobile energy storage is proposed using the NSGA-II algorithm. Finally, the effectiveness of the proposed optimization strategy was verified through coupled simulation cases using the IEEE-33 node test system and the Sioux Falls network. The results demonstrate that the proposed optimization strategy can significantly enhance system resilience under different optimization objectives.
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