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Fault Self-Healing Cooperative Strategy of New Energy Distribution Network Based on Improved Ant Colony-Genetic Hybrid Algorithm
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作者 Fengchao Chen Aoqi Mei +2 位作者 Zheng Liu Ruhao Wu Qiwei Li 《Energy Engineering》 2026年第4期247-267,共21页
With the high proportion of new energy access,the traditional fault self-healing mechanism of the distribution network is challenged.Aiming at the demand for fast recovery of new distribution network faults,this paper... With the high proportion of new energy access,the traditional fault self-healing mechanism of the distribution network is challenged.Aiming at the demand for fast recovery of new distribution network faults,this paper proposes a fault self-healing cooperative strategy for the new energy distribution network based on an improved ant colony-genetic hybrid algorithm.Firstly,the graph theory adjacency matrix is used to characterize the topology of the distribution network,and the dynamic positioning of new energy nodes is realized.Secondly,based on the output model and load characteristic model of wind,photovoltaic,and energy storage,a two-layer cooperative self-healing model of the distribution network is constructed.The upper layer is based on the improved depth-breadth hybrid search(DFS-BFS)to divide the island,with the maximum weight load recovery and the minimum number of switching actions as the goal,combined with the load priority to dynamically restore the key load.The lower layer uses the improved ant colony-genetic hybrid algorithm to solve the fault recovery path with the minimum total power loss load and the minimum network loss as the goal,generate the optimal switching sequence,and verify the power flow constraints.Finally,the simulation results based on the IEEE 33-bus system show that the proposed method can guarantee the power supply of key loads in the distribution network with high-tech energy penetration,restore the power supply of more load nodes with the least switching operation,and effectively reduce the line loss,which verifies the effectiveness and superiority of the method. 展开更多
关键词 Fault recovery identification of topology improved ant colony-genetic hybrid algorithm distribution network self-healing
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农村客运车辆货邮融合配送的优化模型与算法
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作者 冶瑞 丁楠 +1 位作者 邓续晖 封丛 《交通科技与经济》 2026年第2期25-32,共8页
为解决农村客货邮融合发展中车货匹配与路径规划问题,通过货邮路径优化与订单指派联合优化的方法来构建以运输成本、装卸搬运成本、碳排放成本、时间惩罚成本以及储存成本在内的总成本最小为目标的混合整数货邮搭载模型,并设计改进蚁群... 为解决农村客货邮融合发展中车货匹配与路径规划问题,通过货邮路径优化与订单指派联合优化的方法来构建以运输成本、装卸搬运成本、碳排放成本、时间惩罚成本以及储存成本在内的总成本最小为目标的混合整数货邮搭载模型,并设计改进蚁群-遗传双层算法进行求解,来优化农村客货邮融合运输系统的配送时间及成本。以陕西省商洛市洛南县为例,通过求解不同规模算例发现,改进算法在1000个订单规模算例的重复试验结果差异仅为0.24%,算法具有良好的稳定性;在不同规模算例中,“路线合并”方法相较“路线不合并”的求解质量平均降低0.59%,求解时间平均节约14.52%。敏感度分析发现,拓宽送货时间窗有助于降低总成本;当参数θ≥0.6时,继续增加行李舱最大货邮承载力不会显著降低总成本。 展开更多
关键词 农村物流 车辆路径优化 客货邮融合 混合整数规划 改进蚁群-遗传双层算法
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