Journal articles: 'Distribution Networks'

1

Hampson, J. "Urban network development [distribution networks]." Power Engineering Journal 15, no. 5 (October 1, 2001): 224–32. http://dx.doi.org/10.1049/pe:20010504.

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Boroojeni, Asma Azizi, Jeremy Dewar, Tong Wu, and James M. Hyman. "Generating bipartite networks with a prescribed joint degree distribution." Journal of Complex Networks 5, no. 6 (June 27, 2017): 839–57. http://dx.doi.org/10.1093/comnet/cnx014.

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Abstract We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree–degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor–movie networks, author–article networks, co-occurrence networks and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbours of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite $2K$ ($B2K$) algorithms generate an ensemble of networks that preserve prescribed degree sequences for the two disjoint set of nodes in the bipartite network, and the joint-degree distribution that is the distribution of the degrees of all neighbours of nodes with the same degree. We illustrate the effectiveness of the algorithms on a romance network using the NetworkX software environment to compare other properties of a target network that are not directly enforced by the $B2K$ algorithms. We observe that when average degree of nodes is low, as is the case for romance and heterosexual partnership networks, then the $B2K$ networks tend to preserve additional properties, such as the cluster coefficients, than algorithms that do not preserve the joint-degree distribution of the original network.

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Laylock, W. J. "Intelligent networks [power distribution networks]." Power Engineering Journal 16, no. 1 (February 1, 2002): 25–29. http://dx.doi.org/10.1049/pe:20020104.

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Jones, Chris, and Karoline Wiesner. "Clarifying How Degree Entropies and Degree-Degree Correlations Relate to Network Robustness." Entropy 24, no. 9 (August 24, 2022): 1182. http://dx.doi.org/10.3390/e24091182.

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It is often claimed that the entropy of a network’s degree distribution is a proxy for its robustness. Here, we clarify the link between degree distribution entropy and giant component robustness to node removal by showing that the former merely sets a lower bound to the latter for randomly configured networks when no other network characteristics are specified. Furthermore, we show that, for networks of fixed expected degree that follow degree distributions of the same form, the degree distribution entropy is not indicative of robustness. By contrast, we show that the remaining degree entropy and robustness have a positive monotonic relationship and give an analytic expression for the remaining degree entropy of the log-normal distribution. We also show that degree-degree correlations are not by themselves indicative of a network’s robustness for real networks. We propose an adjustment to how mutual information is measured which better encapsulates structural properties related to robustness.

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Wang, Bing, Zhiwen Sun, and Yuexing Han. "A Path-Based Distribution Measure for Network Comparison." Entropy 22, no. 11 (November 12, 2020): 1287. http://dx.doi.org/10.3390/e22111287.

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As network data increases, it is more common than ever for researchers to analyze a set of networks rather than a single network and measure the difference between networks by developing a number of network comparison methods. Network comparison is able to quantify dissimilarity between networks by comparing the structural topological difference of networks. Here, we propose a kind of measures for network comparison based on the shortest path distribution combined with node centrality, capturing the global topological difference with local features. Based on the characterized path distributions, we define and compare network distance between networks to measure how dissimilar the two networks are, and the network entropy to characterize a typical network system. We find that the network distance is able to discriminate networks generated by different models. Combining more information on end nodes along a path can further amplify the dissimilarity of networks. The network entropy is able to detect tipping points in the evolution of synthetic networks. Extensive numerical simulations reveal the effectivity of the proposed measure in network reduction of multilayer networks, and identification of typical system states in temporal networks as well.

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GOYAL, RAVI, JOSEPH BLITZSTEIN, and VICTOR DE GRUTTOLA. "Sampling networks from their posterior predictive distribution." Network Science 2, no. 1 (April 2014): 107–31. http://dx.doi.org/10.1017/nws.2014.2.

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AbstractRecent research indicates that knowledge about social networks can be leveraged to increase efficiency of interventions (Valente, 2012). However, in many settings, there exists considerable uncertainty regarding the structure of the network. This can render the estimation of potential effects of network-based interventions difficult, as providing appropriate guidance to select interventions often requires a representation of the whole network. In order to make use of the network property estimates to simulate the effect of interventions, it may be beneficial to sample networks from an estimated posterior predictive distribution, which can be specified using a wide range of models. Sampling networks from a posterior predictive distribution of network properties ensures that the uncertainty about network property parameters is adequately captured. The tendency for relationships among network properties to exhibit sharp thresholds has important implications for understanding global network topology in the presence of uncertainty; therefore, it is essential to account for uncertainty. We provide detail needed to sample networks for the specific network properties of degree distribution, mixing frequency, and clustering. Our methods to generate networks are demonstrated using simulated data and data from the National Longitudinal Study of Adolescent Health.

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Masuda, Naoki, and Fanlin Meng. "Dynamical stability of water distribution networks." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 475, no. 2230 (October 2019): 20190291. http://dx.doi.org/10.1098/rspa.2019.0291.

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Water distribution networks are hydraulic infrastructures that aim to meet water demands at their various nodes. Water flows through pipes in the network create nonlinear dynamics on networks. A desirable feature of water distribution networks is high resistance to failures and other shocks to the system. Such threats would at least transiently change the flow rate in various pipes, potentially undermining the functionality of the whole water distribution system. Here we carry out a linear stability analysis for a nonlinear dynamical system representing the flow rate through pipes that are interconnected through an arbitrary pipe network with reservoirs and consumer nodes. We show that the steady state is always locally stable and develop a method to calculate the eigenvalue that corresponds to the mode that decays the most slowly towards the equilibrium, which we use as an index for resilience of the system. We show that the proposed index is positively correlated with the recovery rate of the pipe network, which was derived from a realistic and industrially popular simulator. The present analytical framework is expected to be useful for deploying tools from nonlinear dynamics and network analysis in the design, resilience management and scenario testing of water distribution networks.

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Li, Faxu, Liang Wei, Haixing Zhao, and Feng Hu. "On the Distributions of Subgraph Centralities in Complex Networks." Discrete Dynamics in Nature and Society 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/473248.

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Subgraph centrality measure characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than large ones, which makes this measure appropriate for characterizing network motifs. This measure is better in being able to discriminate the nodes of a network than alternate measures. In this paper, the important issue of subgraph centrality distributions is investigated through theory-guided extensive numerical simulations, for three typical complex network models, namely, the ER random-graph networks, WS small-world networks, and BA scale-free networks. It is found that these three very different types of complex networks share some common features, particularly that the subgraph centrality distributions in increasing order are all insensitive to the network connectivity characteristics, and also found that the probability distributions of subgraph centrality of the ER and of the WS models both follow the gamma distribution, and the BA scale-free networks exhibit a power-law distribution with an exponential cutoff.

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Liang, Jianxiong, Xiaoguang Chen, and Tianyi Wang. "Percolation Distribution in Small-World Quantum Networks." Applied Sciences 12, no. 2 (January 11, 2022): 701. http://dx.doi.org/10.3390/app12020701.

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Quantum networks have good prospects for applications in the future. Compared with classical networks, small-world quantum networks have some interesting properties. The topology of the network can be changed through entanglement exchange operations, and different network topologies will result in different percolation thresholds when performing entanglement percolation. A lower percolation threshold means that quantum networks require fewer minimum resources for communication. Since a shared singlet between two nodes can still be a limitation, concurrency percolation theory (ConPT) can be used to relax the condition. In this paper, we investigate how entanglement distribution is performed in small-world quantum networks to ensure that nodes in the network can communicate with each other by establishing communication links through entanglement swapping. Any node can perform entanglement swapping on only part of the connected edges, which can reduce the influence of each node in the network during entanglement swapping. In addition, the ConPT method is used to reduce the percolation threshold even further, thus obtaining a better network structure and reducing the resources required.

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Henderson, W., and P. G. Taylor. "Some new results on queueing networks with batch movement." Journal of Applied Probability 28, no. 2 (June 1991): 409–21. http://dx.doi.org/10.2307/3214876.

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Product-form equilibrium distributions in networks of queues in which customers move singly have been known since 1957, when Jackson derived some surprising independence results. A product-form equilibrium distribution has also recently been shown to be valid for certain queueing networks with batch arrivals, batch services and even correlated routing.This paper derives the joint equilibrium distribution of states immediately before and after a batch of customers is released into the network. The results are valid for either discrete- or continuous-time queueing networks: previously obtained results can be seen as marginal distributions within a more general framework. A generalisation of the classical ‘arrival theorem' for continuous-time networks is given, which compares the equilibrium distribution as seen by arrivals to the time-averaged equilibrium distribution.

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Henderson, W., and P. G. Taylor. "Some new results on queueing networks with batch movement." Journal of Applied Probability 28, no. 02 (June 1991): 409–21. http://dx.doi.org/10.1017/s0021900200039784.

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Product-form equilibrium distributions in networks of queues in which customers move singly have been known since 1957, when Jackson derived some surprising independence results. A product-form equilibrium distribution has also recently been shown to be valid for certain queueing networks with batch arrivals, batch services and even correlated routing. This paper derives the joint equilibrium distribution of states immediately before and after a batch of customers is released into the network. The results are valid for either discrete- or continuous-time queueing networks: previously obtained results can be seen as marginal distributions within a more general framework. A generalisation of the classical ‘arrival theorem' for continuous-time networks is given, which compares the equilibrium distribution as seen by arrivals to the time-averaged equilibrium distribution.

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12

Artico, I., I. Smolyarenko, V. Vinciotti, and E. C. Wit. "How rare are power-law networks really?" Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476, no. 2241 (September 2020): 20190742. http://dx.doi.org/10.1098/rspa.2019.0742.

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The putative scale-free nature of real-world networks has generated a lot of interest in the past 20 years: if networks from many different fields share a common structure, then perhaps this suggests some underlying ‘network law’. Testing the degree distribution of networks for power-law tails has been a topic of considerable discussion. Ad hoc statistical methodology has been used both to discredit power-laws as well as to support them. This paper proposes a statistical testing procedure that considers the complex issues in testing degree distributions in networks that result from observing a finite network, having dependent degree sequences and suffering from insufficient power. We focus on testing whether the tail of the empirical degrees behaves like the tail of a de Solla Price model, a two-parameter power-law distribution. We modify the well-known Kolmogorov–Smirnov test to achieve even sensitivity along the tail, considering the dependence between the empirical degrees under the null distribution, while guaranteeing sufficient power of the test. We apply the method to many empirical degree distributions. Our results show that power-law network degree distributions are not rare, classifying almost 65% of the tested networks as having a power-law tail with at least 80% power.

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Mundher, Zaid. "A Method for Investigating Coverage Area Issue in Dynamic Networks." Technium: Romanian Journal of Applied Sciences and Technology 4, no. 3 (April 16, 2022): 19–27. http://dx.doi.org/10.47577/technium.v4i3.6342.

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Coverage area in dynamic networks is considered an important issue that affects their general performance. It also affects the delay time when exchanging data and the consumption of resources in the network. Moreover, the coverage area issue in dynamic networks is directly affected by the distributions of nodes within the environment. Movement patterns may also affect the performance when it comes to coverage area. Therefore, this work develops a method that simulates different scenarios. These scenarios include a variety of settings and parameters that are believed to affect the coverage area issue of dynamic networks. These experiments enable network developers to be aware of the optimal conditions that maximize the coverage area of dynamic network nodes and eventually improve the overall performance of the network. Three distributions are used in the experiments namely, Cauchy distribution, Power-Law distribution, and Normal distribution. Also, the simulations incorporate the correlation mobility model for nodes dynamics. The findings show that Cauchy distribution is not appropriate for simulating dynamic networks due to the large uncovered areas by nodes communications. Also, the stability of an approach is considered an important factor when measuring the performance of a dynamic network. The results of this research are important to avoid wasting network resources.

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14

Cunningham, Joseph J. "AC network centennial: Years of distribution networks [History]." IEEE Power and Energy Magazine 20, no. 2 (March 2022): 64–76. http://dx.doi.org/10.1109/mpe.2021.3134345.

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15

Shirmohammadi, D. "Service restoration in distribution networks via network reconfiguration." IEEE Transactions on Power Delivery 7, no. 2 (April 1992): 952–58. http://dx.doi.org/10.1109/61.127104.

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Kashem, M. A., V. Ganapathy, and G. B. Jasmon. "Network reconfiguration for load balancing in distribution networks." IEE Proceedings - Generation, Transmission and Distribution 146, no. 6 (1999): 563. http://dx.doi.org/10.1049/ip-gtd:19990694.

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Han, Seung Chul, and Ye Xia. "Network load-aware content distribution in overlay networks." Computer Communications 32, no. 1 (January 2009): 51–61. http://dx.doi.org/10.1016/j.comcom.2008.09.021.

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Small, Michael, Lvlin Hou, and Linjun Zhang. "Random complex networks." National Science Review 1, no. 3 (July 18, 2014): 357–67. http://dx.doi.org/10.1093/nsr/nwu021.

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Abstract Exactly what is meant by a ‘complex’ network is not clear; however, what is clear is that it is something other than a random graph. Complex networks arise in a wide range of real social, technological and physical systems. In all cases, the most basic categorization of these graphs is their node degree distribution. Particular groups of complex networks may exhibit additional interesting features, including the so-called small-world effect or being scale-free. There are many algorithms with which one may generate networks with particular degree distributions (perhaps the most famous of which is preferential attachment). In this paper, we address what it means to randomly choose a network from the class of networks with a particular degree distribution, and in doing so we show that the networks one gets from the preferential attachment process are actually highly pathological. Certain properties (including robustness and fragility) which have been attributed to the (scale-free) degree distribution are actually more intimately related to the preferential attachment growth mechanism. We focus here on scale-free networks with power-law degree sequences—but our methods and results are perfectly generic.

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DA FONTOURA COSTA, LUCIANO, and GONZALO TRAVIESO. "STRENGTH DISTRIBUTION IN DERIVATIVE NETWORKS." International Journal of Modern Physics C 16, no. 07 (July 2005): 1097–105. http://dx.doi.org/10.1142/s0129183105007765.

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This article describes a complex network model whose weights are proportional to the difference between uniformly distributed "fitness" values assigned to the nodes. It is shown both analytically and experimentally that the strength density (i.e., the weighted node degree) for this model, called derivative complex networks, follows a power law with exponent γ<1 if the fitness has an upper limit and γ>1 if the fitness has no upper limit but a positive lower limit. Possible implications for neuronal networks topology and dynamics are also discussed.

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DAI, MEIFENG, and DANPING ZHANG. "A WEIGHTED EVOLVING NETWORK WITH AGING-NODE-DELETING AND LOCAL REARRANGEMENTS OF WEIGHTS." International Journal of Modern Physics C 25, no. 02 (February 2014): 1350093. http://dx.doi.org/10.1142/s0129183113500939.

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In previous study of complex network, researchers generally considered the increase of the un-weighted network by the method of adding new nodes and new links. However, most of real networks are weighted and characterized by capacities or strength instead of a binary state (present or absent), and their nodes and links experience both increase and deletion. Barrat, Barthlemy and Vespignani, Phys. Rev. Lett.92, 228701 (2004) presented an evolutionary model (BBV model) to investigate weighted networks. We present a weighted evolution network model based on BBV model, which not only considers to add a new node and m links, but also to remove an old node and corresponding links with probability at each time step. By using rate equation and mean-field method, we study the network's properties: The weight, strength and their distributions. We find that the relationship between weight and strength is nonlinear. In addition, we theoretically prove that the weight distribution and the strength distribution follow a power-law distribution, respectively.

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Li, Zhang-Wei, Xu-Hua Yang, Feng-Ling Jiang, Guang Chen, Guo-Qing Weng, and Mei Zhu. "Dynamically Weighted Clique Evolution Model in Clique Networks." Mathematical Problems in Engineering 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/182638.

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This paper proposes a weighted clique evolution model based on clique (maximal complete subgraph) growth and edge-weight driven for complex networks. The model simulates the scheme of real-world networks that the evolution of networks is likely to be driven by the flow, such as traffic or information flow needs, as well as considers that real-world networks commonly consist of communities. At each time step of a network’s evolution progress, an edge is randomly selected according to a preferential scheme. Then a new clique which contains the edge is added into the network while the weight of the edge is adjusted to simulate the flow change brought by the new clique addition. We give the theoretical analysis based on the mean field theory, as well as some numerical simulation for this model. The result shows that the model can generate networks with scale-free distributions, such as edge weight distribution and node strength distribution, which can be found in many real-world networks. It indicates that the evolution rule of the model may attribute to the formation of real-world networks.

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Kyriakou, Dimitra G., and Fotios D. Kanellos. "Sustainable Operation of Active Distribution Networks." Applied Sciences 13, no. 5 (February 28, 2023): 3115. http://dx.doi.org/10.3390/app13053115.

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The present and future conditions in the energy market impose extremely high standards to the operation of building energy systems. Moreover, distribution networks face new operational and technical challenges as a result of the rapid penetration of renewable energy sources (RES) and other forms of distributed generation. Consequently, active distribution networks (ADNs) will play a crucial role in the exploitation of smart building prosumers, smart grids, and RES. In this paper, an optimization method for the sustainable operation of active distribution networks hosting smart residential building prosumers, plug-in electric vehicle (PEV) aggregators, and RES was developed. The thermal and electrical loads of the residential buildings were modeled in detail and an aggregation method was implemented to the hosted PEVs. Moreover, smart power dispatch techniques were applied at each building prosumer and PEV aggregator hosted by the active distribution network. Simultaneously, all the operational limitations of the active distribution network, building energy systems, and the hosted PEVs were satisfied. The constrained optimal power flow (OPF) algorithm was exploited to keep the voltages of the hosting distribution network between the permissible bounds. A significant operation cost reduction of 17% was achieved. The developed models were verified through detailed simulation results.

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Ge, Guo Zhou, Jing Chang Pan, and Cong Liu. "Research and Implementation of Internet Topology Based on AB Model." Advanced Materials Research 1042 (October 2014): 207–11. http://dx.doi.org/10.4028/www.scientific.net/amr.1042.207.

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Complex network topological characteristics are mainly reflected in the next three different kinds of features, like the power-law distribution, the rich-club characteristic and assortativity coefficient. With increasing the number of the network’s nodes and edges and resetting the edges, AB model generator makes the network to grow and expand effectively. This paper has realized the generator with the algorithm to get a topological network. And based on that, this paper has also done some comparative analysis between AB network and the WEB network. Experimental results show that the two networks are similar on the power-law distributions and some other characteristics, and both of the two networks are disassortative.

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Siino, Marianna, Salvatore Scudero, Luca Greco, and Antonino D’Alessandro. "Spatial analysis for an evaluation of monitoring networks: examples from the Italian seismic and accelerometric networks." Journal of Seismology 24, no. 6 (September 18, 2020): 1045–61. http://dx.doi.org/10.1007/s10950-020-09937-0.

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AbstractIn this work, we propose a statistical approach to evaluate the coverage of a network based on the spatial distribution of its nodes and the target information, including all those data related to the final objectives of the network itself. This statistical approach encompasses descriptive spatial statistics in combination with point pattern techniques. As case studies, we evaluate the spatial arrangements of the stations within the Italian National Seismic Network and the Italian Strong Motion Network. Seismic networks are essential tools for observing earthquakes and assessing seismic hazards, while strong motion (accelerometric) networks allow us to describe seismic shaking and to measure the expected effects on buildings and infrastructures. The capability of both networks is a function of an adequate number of optimally distributed stations. We compare the seismic network with the spatial distributions of historical and instrument seismicity and with the distribution of well-known seismogenic sources, and we compare the strong motion station distribution with seismic hazard maps and the population distribution. This simple and reliable methodological approach is able to provide quantitative information on the coverage of any type of network and is able to identify critical areas that require optimization and therefore address areas of future development.

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Abdul-Wahhab, Thamir M., and Adeeb Nasser Hussein. "Planning of Distribution Networks in Baghdad City." Journal of Engineering 21, no. 2 (February 1, 2015): 66–86. http://dx.doi.org/10.31026/j.eng.2015.02.05.

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Planning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development. Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance. The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city based on the powerful and efficient CYMDist software as a tool for the simulation and analysis of the network. The planning method proposed in this thesis is to reach the optimum operating conditions of the network by combining the network reconfiguration in sequence with the insertion of capacitors with optimal sizing and locations. The optimum performance of the network is achieved by reducing losses, improving voltage profile and alleviating overload for transformers and cables.

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Díaz, J. A. Rodríguez, L. Pérez Urrestarazu, E. Camacho Poyato, and P. Montesinos. "Modernizing Water Distribution Networks." Outlook on Agriculture 41, no. 4 (December 2012): 229–36. http://dx.doi.org/10.5367/oa.2012.0105.

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Melen, R., and J. S. Turner. "Nonblocking multirate distribution networks." IEEE Transactions on Communications 41, no. 2 (1993): 362–69. http://dx.doi.org/10.1109/26.216511.

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Nietsch, C., and D. Povh. "Optimizing power distribution networks." IEEE Computer Applications in Power 14, no. 2 (April 2001): 18–21. http://dx.doi.org/10.1109/67.917580.

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Kuznetsov, Alexander Lvovitch, Sergei Sergeyevich Pavlenko, and Victoria Nickolaevna Scherbackova-Slysarenko. "CONTAINER DISTRIBUTION NETWORKS MODELING." Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 7, no. 5 (October 30, 2015): 33–42. http://dx.doi.org/10.21821/2309-5180-2015-7-5-33-42.

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Vinh Nguyen, Thanh, Farzad Safaei, Paul Boustead, and Chun Tung Chou. "Provisioning overlay distribution networks." Computer Networks 49, no. 1 (September 2005): 103–18. http://dx.doi.org/10.1016/j.comnet.2005.04.001.

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Ilea, Valentin, Cristian Bovo, Davide Falabretti, Marco Merlo, Carlo Arrigoni, Roberto Bonera, and Marco Rodolfi. "Voltage Control Methodologies in Active Distribution Networks." Energies 13, no. 12 (June 26, 2020): 3293. http://dx.doi.org/10.3390/en13123293.

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Renewable Energy Sources are becoming widely spread, as they are sustainable and low-carbon emission. They are mostly penetrating the MV Distribution Networks as Distributed Generators, which has determined the evolution of the networks’ control and supervision systems, from almost a complete lack to becoming fully centralized. This paper proposes innovative voltage control architectures for the distribution networks, tailored for different development levels of the control and supervision systems encountered in real life: a Coordinated Control for networks with basic development, and an optimization-based Centralized Control for networks with fully articulated systems. The Centralized Control fits the requirements of the network: the challenging harmonization of the generator’s capability curves with the regulatory framework, and modelling of the discrete control of the On-Load Tap Changer transformer. A realistic network is used for tests and comparisons with the Local Strategy currently specified by regulations. The proposed Coordinated Control gives much better results with respect to the Local Strategy, in terms of loss minimization and voltage violations mitigation, and can be used for networks with poorly developed supervision and control systems, while Centralized Control proves the best solution, but can be applied only in fully supervised and controlled networks.

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Sim, Dong-Hi, Jongyoon Shin, and Min Hyung Kim. "Software-Defined Networking Orchestration for Interoperable Key Management of Quantum Key Distribution Networks." Entropy 25, no. 6 (June 15, 2023): 943. http://dx.doi.org/10.3390/e25060943.

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This paper demonstrates the use of software-defined networking (SDN) orchestration to integrate regionally separated networks in which different network parts use incompatible key management systems (KMSs) managed by different SDN controllers to ensure end-to-end QKD service provisioning to deliver the QKD keys between geographically different QKD networks. The study focuses on scenarios in which different parts of the network are managed separately by different SDN controllers, requiring an SDN orchestrator to coordinate and manage these controllers. In practical network deployments, operators often utilize multiple vendors for their network equipment. This practice also enables the expansion of the QKD network’s coverage by interconnecting various QKD networks equipped with devices from different vendors. However, as coordinating different parts of the QKD network is a complex task, this paper proposes the implementation of an SDN orchestrator which acts as a central entity to manage multiple SDN controllers, ensuring end-to-end QKD service provisioning to address this challenge. For instance, when there are multiple border nodes to interconnect different networks, the SDN orchestrator calculates the path in advance for the end-to-end delivery of keys between initiating and target applications belonging to different networks. This path selection requires the SDN orchestrator to gather information from each SDN controller managing the respective parts of the QKD network. This work shows the practical implementation of SDN orchestration for interoperable KMS in commercial QKD networks in South Korea. By employing an SDN orchestrator, it becomes possible to coordinate multiple SDN controllers and ensure the efficient and secure delivery of QKD keys between different QKD networks with varying vendor equipment.

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SHANG, YILUN. "DISTRIBUTION DYNAMICS FOR SIS MODEL ON RANDOM NETWORKS." Journal of Biological Systems 20, no. 02 (June 2012): 213–20. http://dx.doi.org/10.1142/s0218339012500076.

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We study the evolution of degree distributions of susceptible-infected-susceptible (SIS) model on random networks, where susceptible nodes are capable of being infected, and infected nodes can spread the disease further. The network of contacts is modeled as a configuration model featuring heterogeneous degree distribution. We derive systematically the (excess) degree distributions among susceptible and infected individuals by using the probability generating function formalism.

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Jin, Zhaoyan, and Quanyuan Wu. "Using Power-Law Degree Distribution to Accelerate PageRank." Computer Engineering and Applications Journal 1, no. 2 (December 15, 2012): 63–70. http://dx.doi.org/10.18495/comengapp.v1i2.8.

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The PageRank vector of a network is very important, for it can reflect the importance of a Web page in the World Wide Web, or of a people in a social network. However, with the growth of the World Wide Web and social networks, it needs more and more time to compute the PageRank vector of a network. In many real-world applications, the degree and PageRank distributions of these complex networks conform to the Power-Law distribution. This paper utilizes the degree distribution of a network to initialize its PageRank vector, and presents a Power-Law degree distribution accelerating algorithm of PageRank computation. Experiments on four real-world datasets show that the proposed algorithm converges more quickly than the original PageRank algorithm.DOI:Â 10.18495/comengapp.12.063070

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Prakash, K., F. R. Islam, K. A. Mamun, and H. R. Pota. "Configurations of Aromatic Networks for Power Distribution System." Sustainability 12, no. 10 (May 25, 2020): 4317. http://dx.doi.org/10.3390/su12104317.

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A distribution network is one of the main parts of a power system that distributes power to customers. While there are various types of power distribution networks, a recently introduced novel structure of an aromatic network could begin a new era in the distribution levels of power systems and designs of microgrids or smart grids. In order to minimize blackout periods during natural disasters and provide sustainable energy, improve energy efficiency and maintain stability of a distribution network, it is essential to configure/reconfigure the network topology based on its geographical location and power demand, and also important to realize its self-healing function. In this paper, a strategy for reconfiguring aromatic networks based on structures of natural aromatic molecules is explained. Various network structures are designed, and simulations have been conducted to justify the performance of each configuration. It is found that an aromatic network does not need to be fixed in a specific configuration (i.e., a DDT structure), which provides flexibility in designing networks and demonstrates that the successful use of such structures will be a perfect solution for both distribution networks and microgrid systems in providing sustainable energy to the end users.

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Misiunas, D., J. Vítkovský, G. Olsson, M. Lambert, and A. Simpson. "Failure monitoring in water distribution networks." Water Science and Technology 53, no. 4-5 (February 1, 2006): 503–11. http://dx.doi.org/10.2166/wst.2006.154.

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An algorithm for the burst detection and location in water distribution networks based on the continuous monitoring of the flow rate at the entry point of the network and the pressure at a number of points within the network is presented. The approach is designed for medium to large bursts with opening times in the order of a few minutes and is suitable for networks of relatively small size, such as district metered areas (DMAs). The burst-induced increase in the inlet flow rate is detected using the modified cumulative sum (CUSUM) change detection test. Based on parameters obtained from the CUSUM test, the burst is simulated at a number of burst candidate locations. The calculated changes in pressure at the pressure monitoring points are then compared to the measured values and the location resulting in the best fit is selected as the burst location. The EPANET steady-state hydraulic solver is utilised to simulate the flows and pressures in the network. A sensitivity-based sampling design procedure is introduced to find the optimal positions for pressure monitoring points. The proposed algorithm is tested on a case study example network and shows potential for burst detection and location in real water distribution systems.

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Zhou, Bin, Xiangyi Meng, and H. Eugene Stanley. "Power-law distribution of degree–degree distance: A better representation of the scale-free property of complex networks." Proceedings of the National Academy of Sciences 117, no. 26 (June 15, 2020): 14812–18. http://dx.doi.org/10.1073/pnas.1918901117.

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Whether real-world complex networks are scale free or not has long been controversial. Recently, in Broido and Clauset [A. D. Broido, A. Clauset,Nat. Commun.10, 1017 (2019)], it was claimed that the degree distributions of real-world networks are rarely power law under statistical tests. Here, we attempt to address this issue by defining a fundamental property possessed by each link, the degree–degree distance, the distribution of which also shows signs of being power law by our empirical study. Surprisingly, although full-range statistical tests show that degree distributions are not often power law in real-world networks, we find that in more than half of the cases the degree–degree distance distributions can still be described by power laws. To explain these findings, we introduce a bidirectional preferential selection model where the link configuration is a randomly weighted, two-way selection process. The model does not always produce solid power-law distributions but predicts that the degree–degree distance distribution exhibits stronger power-law behavior than the degree distribution of a finite-size network, especially when the network is dense. We test the strength of our model and its predictive power by examining how real-world networks evolve into an overly dense stage and how the corresponding distributions change. We propose that being scale free is a property of a complex network that should be determined by its underlying mechanism (e.g., preferential attachment) rather than by apparent distribution statistics of finite size. We thus conclude that the degree–degree distance distribution better represents the scale-free property of a complex network.

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ZHOU, JIN, XIAOKE XU, JIE ZHANG, JUNFENG SUN, MICHAEL SMALL, and JUN-AN LU. "GENERATING AN ASSORTATIVE NETWORK WITH A GIVEN DEGREE DISTRIBUTION." International Journal of Bifurcation and Chaos 18, no. 11 (November 2008): 3495–502. http://dx.doi.org/10.1142/s0218127408022536.

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Recently, the assortative mixing of complex networks has received much attention partly because of its significance in various social networks. In this paper, a new scheme to generate an assortative growth network with given degree distribution is presented using a Monte Carlo sampling method. Since the degrees of a great number of real-life networks obey either power-law or Poisson distribution, we employ these two distributions to grow our models. The models generated by this method exhibit interesting characteristics such as high average path length, high clustering coefficient and strong rich-club effects.

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Yamashita, Hideaki, and Masakiyo Miyazawa. "Geometric product form queueing networks with concurrent batch movements." Advances in Applied Probability 30, no. 4 (December 1998): 1111–29. http://dx.doi.org/10.1239/aap/1035228210.

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Queueing networks have been rather restricted in order to have product form distributions for network states. Recently, several new models have appeared and enlarged this class of product form networks. In this paper, we consider another new type of queueing network with concurrent batch movements in terms of such product form results. A joint distribution of the requested batch sizes for departures and the batch sizes of the corresponding arrivals may be arbitrary. Under a certain modification of the network and mild regularity conditions, we give necessary and sufficient conditions for the network state to have the product form distribution, which is shown to provide an upper bound for the one in the original network. It is shown that two special settings satisfy these conditions. Algorithms to calculate their stationary distributions are considered, with numerical examples.

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Yamashita, Hideaki, and Masakiyo Miyazawa. "Geometric product form queueing networks with concurrent batch movements." Advances in Applied Probability 30, no. 04 (December 1998): 1111–29. http://dx.doi.org/10.1017/s000186780000882x.

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Queueing networks have been rather restricted in order to have product form distributions for network states. Recently, several new models have appeared and enlarged this class of product form networks. In this paper, we consider another new type of queueing network with concurrent batch movements in terms of such product form results. A joint distribution of the requested batch sizes for departures and the batch sizes of the corresponding arrivals may be arbitrary. Under a certain modification of the network and mild regularity conditions, we give necessary and sufficient conditions for the network state to have the product form distribution, which is shown to provide an upper bound for the one in the original network. It is shown that two special settings satisfy these conditions. Algorithms to calculate their stationary distributions are considered, with numerical examples.

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Wright, Robert, Ivan Stoianov, Panos Parpas, Kevin Henderson, and John King. "Adaptive water distribution networks with dynamically reconfigurable topology." Journal of Hydroinformatics 16, no. 6 (May 19, 2014): 1280–301. http://dx.doi.org/10.2166/hydro.2014.086.

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This paper presents a novel concept of adaptive water distribution networks with dynamically reconfigurable topology for optimal pressure control, leakage management and improved system resilience. The implementation of District Meter Areas (DMAs) has greatly assisted water utilities in reducing leakage. DMAs segregate water networks into small areas, the flow in and out of each area is monitored and thresholds are derived from the minimum night flow to trigger the leak localization. A major drawback of the DMA approach is the reduced redundancy in network connectivity which has a severe impact on network resilience, incident management and water quality deterioration. The presented approach for adaptively reconfigurable networks integrates the benefits of DMAs for managing leakage with the advantages of large-scale looped networks for increased redundancy in connectivity, reliability and resilience. Self-powered multi-function network controllers are designed and integrated with novel telemetry tools for high-speed time-synchronized monitoring of the dynamic hydraulic conditions. A computationally efficient and robust optimization method based on sequential convex programming is developed and applied for the dynamic topology reconfiguration and pressure control of water distribution networks. An investigation is carried out using an operational network to evaluate the implementation and benefits of the proposed method.

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Henderson, W., B. S. Northcote, and P. G. Taylor. "State-dependent signalling in queueing networks." Advances in Applied Probability 26, no. 02 (June 1994): 436–55. http://dx.doi.org/10.1017/s0001867800026288.

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It has recently been shown that networks of queues with state-dependent movement of negative customers, and with state-independent triggering of customer movement have product-form equilibrium distributions. Triggers and negative customers are entities which, when arriving to a queue, force a single customer to be routed through the network or leave the network respectively. They are ‘signals' which affect/control network behaviour. The provision of state-dependent intensities introduces queues other than single-server queues into the network. This paper considers networks with state-dependent intensities in which signals can be either a trigger or a batch of negative customers (the batch size being determined by an arbitrary probability distribution). It is shown that such networks still have a product-form equilibrium distribution. Natural methods for state space truncation and for the inclusion of multiple customer types in the network can be viewed as special cases of this state dependence. A further generalisation allows for the possibility of signals building up at nodes.

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Antunes, Nelson, Tianjian Guo, and Vladas Pipiras. "Sampling methods and estimation of triangle count distributions in large networks." Network Science 9, S1 (February 26, 2021): S134—S156. http://dx.doi.org/10.1017/nws.2021.2.

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AbstractThis paper investigates the distributions of triangle counts per vertex and edge, as a means for network description, analysis, model building, and other tasks. The main interest is in estimating these distributions through sampling, especially for large networks. A novel sampling method tailored for the estimation analysis is proposed, with three sampling designs motivated by several network access scenarios. An estimation method based on inversion and an asymptotic method are developed to recover the entire distribution. A single method to estimate the distribution using multiple samples is also considered. Algorithms are presented to sample the network under the various access scenarios. Finally, the estimation methods on synthetic and real-world networks are evaluated in a data study.

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SUN, HUIJUN, and JIANJUN WU. "SCALE-FREE CHARACTERISTICS OF SUPPLY CHAIN DISTRIBUTION NETWORKS." Modern Physics Letters B 19, no. 17 (July 30, 2005): 841–48. http://dx.doi.org/10.1142/s0217984905008797.

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This paper is the first step to a study of supply chain distribution networks based on the scale-free theory, and we attempt to analyze the growth of supply chain distribution networks. We construct the supply chain distribution network and divide it into two groups. Through empirical theory and numerical study, it is found that supply chain networks have scale-free characteristics. Additionally, other three features of supply chain distribution network are proposed in this paper. Finally, the exponent of degree distribution is given.

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He, Jing, Gang Liu, Weile Li, Chuan Tang, and Jiayan Lu. "An evaluation approach for segmentation results of high-resolution remote sensing images based on the degree distribution of land cover networks." International Journal of Modern Physics B 32, no. 25 (October 8, 2018): 1850283. http://dx.doi.org/10.1142/s0217979218502831.

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Identifying the degree distribution of land cover networks is helpful to find analytical methods for characterizing complex land cover, including segmentation techniques of remote sensing images of land cover. After segmentation, we can obtain the geographical objects and corresponding relationships. In order to evaluate the segmentation results, we introduce the concept of land cover network and present an analysis method based on statistics of its degree distribution. Considering the object-oriented segmentation and objects merge-based spectral difference segmentation, we construct the land cover networks for different segmentation scales and spatial resolutions under these two segmentation strategies, and study the degree distribution of each land cover network. Experimental results indicate that, for the object-oriented segmentation, the degree distributions of land cover networks follow approximately a Poisson distribution, regardless of the segmentation scales and spatial resolutions. For the objects-merge method based on spectral difference segmentation, degree distributions exhibit heavy tails. Compared with all the segmentation results, the pattern spots after objects-merge better retain the integrity of geographical features and the land cover network can reflect more accurately the topological properties of real land cover when the threshold of objects merge is suitable. This study shows that we can evaluate the reliability of segmentation results objectively by analyzing the degree distribution pattern of land cover networks.

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Candelieri, Antonio, Davide Soldi, and Francesco Archetti. "NETWORK ANALYSIS FOR RESILIENCE EVALUATION IN WATER DISTRIBUTION NETWORKS." Environmental Engineering and Management Journal 14, no. 6 (2015): 1261–70. http://dx.doi.org/10.30638/eemj.2015.136.

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Ochoa, L. F., C. J. Dent, and G. P. Harrison. "Distribution Network Capacity Assessment: Variable DG and Active Networks." IEEE Transactions on Power Systems 25, no. 1 (February 2010): 87–95. http://dx.doi.org/10.1109/tpwrs.2009.2031223.

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Li, Ran, Zhipeng Zhang, Furong Li, and Petri Ahokangas. "A Shared Network Access Business Model for Distribution Networks." IEEE Transactions on Power Systems 33, no. 1 (January 2018): 1082–84. http://dx.doi.org/10.1109/tec.2017.2688137.

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YANG, SHU-XIA, ZHI-XUAN YANG, XUE-QING WANG, SHOU-LIANG BU, and I.-MIN JIANG. "ESTIMATING WEIGHT DISTRIBUTION IN COUPLED OSCILLATOR NETWORKS." International Journal of Modern Physics C 21, no. 03 (March 2010): 423–32. http://dx.doi.org/10.1142/s0129183110015191.

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This work proposes a method for estimating the weight distribution of a network with Gauss edge weights using a time series collected from controlled measurements of the stable dynamics of the network. Comparing the weight distribution obtained using this method with that using another scheme demonstrates that the former is effective and accurate for estimating the weight distribution P(w) of coupled oscillator networks in a broad coupling strength region. This method enables the topological properties of underlying networks to be determined from only a time series of measurements because it depends on no prior information about the dynamical system. In addition, the method is rather robust against noise.

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Archundia-Aranda, I., and R. O. Mota-Palomino. "Harmonic Penetration Method for Radial Distribution Networks." International Journal of Emerging Electric Power Systems 15, no. 2 (April 1, 2014): 111–17. http://dx.doi.org/10.1515/ijeeps-2013-0093.

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Abstract This work presents a method for calculating harmonic voltages and currents in radial distribution networks. The proposed method is an extension of the backward/forward sweep method for load flow studies in distribution systems and as such preserves its good convergence characteristics besides of not requiring of any network matrix. The method was tested on an eight-node one-phase radial test feeder and results were similar to those that were obtained by the well-known current injection method. Also it was tested on a 2000-node network, showing this way that this is a more suitable method for large three-phase radial distribution networks.

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Journal articles on the topic 'Distribution Networks'

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