配电网的重要节点和主要线路的故障会对网架供电造成巨大影响。为了有效辨别配电网的薄弱环节,本研究为网架数字化和脆弱性评估提出了一系列节点和线路的脆弱性指标,前者在较为传统的指标改进节点度数、节点介数、节点紧密中心度、节点...配电网的重要节点和主要线路的故障会对网架供电造成巨大影响。为了有效辨别配电网的薄弱环节,本研究为网架数字化和脆弱性评估提出了一系列节点和线路的脆弱性指标,前者在较为传统的指标改进节点度数、节点介数、节点紧密中心度、节点注入功率、电压偏离度的基础上加入基于电源和负载考虑的网络效率(source-demand considered efficiency,SDE),即结构脆弱性指标和基于线路越限考虑的抗扰动脆弱性指标:后者分别为线路度数,线路介数和线路SDE指标。在计算各项指标的基础上,采用熵权法和直接赋权法分别计算节点和线路的脆弱度指标权重,并最终得出节点和边的综合脆弱性评分。本研究最后采用IEEE33网络和某中型城市中心城区的网架来检验算法的有效性,结果证明本文提出的方法可以很好地识别配电网节点和线路的薄弱环节,及时发现潜在的隐患。展开更多
The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to opti...The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest (POI) were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. (1) Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of "marginal area of downtown area, suburbs and exurban area", which have a weak coupling degree with logis- tics employment space. (2) The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. (3) In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterprises meet the diverse de- mands of service objects through differentiation of asset allocation to promote the specializa- tion of division and form the object differentiation of logistics space.展开更多
摘要配电网的重要节点和主要线路的故障会对网架供电造成巨大影响。为了有效辨别配电网的薄弱环节,本研究为网架数字化和脆弱性评估提出了一系列节点和线路的脆弱性指标,前者在较为传统的指标改进节点度数、节点介数、节点紧密中心度、节点注入功率、电压偏离度的基础上加入基于电源和负载考虑的网络效率(source-demand considered efficiency,SDE),即结构脆弱性指标和基于线路越限考虑的抗扰动脆弱性指标:后者分别为线路度数,线路介数和线路SDE指标。在计算各项指标的基础上,采用熵权法和直接赋权法分别计算节点和线路的脆弱度指标权重,并最终得出节点和边的综合脆弱性评分。本研究最后采用IEEE33网络和某中型城市中心城区的网架来检验算法的有效性,结果证明本文提出的方法可以很好地识别配电网节点和线路的薄弱环节,及时发现潜在的隐患。
基金Foundation: National Natural Science Foundation of China, No.41501123, No.71703219
摘要The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest (POI) were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. (1) Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of "marginal area of downtown area, suburbs and exurban area", which have a weak coupling degree with logis- tics employment space. (2) The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. (3) In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterprises meet the diverse de- mands of service objects through differentiation of asset allocation to promote the specializa- tion of division and form the object differentiation of logistics space.