Network model of bilateral power markets based on complex networks

2014 ◽  
Vol 28 (22) ◽  
pp. 1450144 ◽  
Author(s):  
Yang Wu ◽  
Junyong Liu ◽  
Furong Li ◽  
Zhanxin Yan ◽  
Li Zhang
Keyword(s):  
Complex Networks ◽  
Network Model ◽  
Simulation Analysis ◽  
Electric Power Industry ◽  
Clustering Coefficient ◽  
Power Markets ◽  
Cascading Failure ◽  
Topological Stability ◽  
Market Organization ◽  
Topological Robustness

The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.

Building Complex Network Similar to Facebook

2014 ◽  
Vol 513-517 ◽  
pp. 909-913
Author(s):  
Dong Wei Guo ◽  
Xiang Yan Meng ◽  
Cai Fang Hou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Complex Networks ◽  
Complex Network ◽  
Network Model ◽  
Clustering Coefficient ◽  
Network Characteristics ◽  
Modeling Methods ◽  
Community Strength ◽  
Strength Based

Social networks have been developed rapidly, especially for Facebook which is very popular with 10 billion users. It is a considerable significant job to build complex network similar to Facebook. There are many modeling methods of complex networks but which cant describe characteristics similar to Facebook. This paper provide a building method of complex networks with tunable clustering coefficient and community strength based on BA network model to imitate Facebook. The strategies of edge adding based on link-via-triangular, link-via-BA and link-via-type are used to build a complex network with tunable clustering coefficient and community strength. Under different parameters, statistical properties of the complex network model are analyzed. The differences and similarities are studied among complex network model proposed by this paper and real social network on Facebook. It is found that the network characteristics of the network model and real social network on Facebook are similar under some specific parameters. It is proved that the building method of complex networks is feasible.

scholarly journals Topological Properties of a 3-Regular Small World Network

2014 ◽  
Vol 2014 ◽  
pp. 1-4
Author(s):  
Huanshen Jia ◽  
Guona Hu ◽  
Haixing Zhao
Keyword(s):  
Complex Networks ◽  
Network Model ◽  
Spanning Trees ◽  
Small World ◽  
Clustering Coefficient ◽  
Deterministic Models ◽  
Engineering Technology ◽  
Research Fields ◽  
Potential Applications ◽  
Regular Network

Complex networks have seen much interest from all research fields and have found many potential applications in a variety of areas including natural, social, biological, and engineering technology. The deterministic models for complex networks play an indispensable role in the field of network model. The construction of a network model in a deterministic way not only has important theoretical significance, but also has potential application value. In this paper, we present a class of 3-regular network model with small world phenomenon. We determine its relevant topological characteristics, such as diameter and clustering coefficient. We also give a calculation method of number of spanning trees in the 3-regular network and derive the number and entropy of spanning trees, respectively.

scholarly journals Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 207
Author(s):  
Javier Gómez-Gómez ◽  
Rafael Carmona-Cabezas ◽  
Elena Sánchez-López ◽  
Eduardo Gutiérrez de Ravé ◽  
Francisco José Jiménez-Hornero
Keyword(s):  
Complex Networks ◽  
Global Climate ◽  
Spatial Relation ◽  
Clustering Coefficient ◽  
Horizontal Visibility ◽  
Climate Conditions ◽  
Mean Values ◽  
Intrinsic Nature ◽  
Temperature Anomalies ◽  
Mean Temperature

The last decades have been successively warmer at the Earth’s surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations. In this work, the authors investigate whether topological properties change over several years. To this aim, we explore the application of the horizontal visibility graph (HVG) approach which maps a time series into a complex network. Data used in this study include a 60-year period of daily mean temperature anomalies in several stations over the Iberian Peninsula (Spain). Average degree, degree distribution exponent, and global clustering coefficient were analyzed. Interestingly, results show that they agree on a lack of significant trends, unlike annual mean values of anomalies, which present a characteristic upward trend. The main conclusions obtained are that complex networks structures and nonlinear features, such as weak correlations, appear not to be affected by rising temperatures derived from global climate conditions. Furthermore, different locations present a similar behavior and the intrinsic nature of these signals seems to be well described by network parameters.

scholarly journals Network isolators inhibit failure spreading in complex networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Franz Kaiser ◽  
Vito Latora ◽  
Dirk Witthaut
Keyword(s):  
Complex Networks ◽  
Large Scale ◽  
Power Transmission ◽  
Power Grids ◽  
Cascading Failure ◽  
Critical Infrastructures ◽  
Daily Lives ◽  
Supply Networks ◽  
Water Transmission ◽  
Complete Collapse

AbstractIn our daily lives, we rely on the proper functioning of supply networks, from power grids to water transmission systems. A single failure in these critical infrastructures can lead to a complete collapse through a cascading failure mechanism. Counteracting strategies are thus heavily sought after. In this article, we introduce a general framework to analyse the spreading of failures in complex networks and demostrate that not only decreasing but also increasing the connectivity of the network can be an effective method to contain damages. We rigorously prove the existence of certain subgraphs, called network isolators, that can completely inhibit any failure spreading, and we show how to create such isolators in synthetic and real-world networks. The addition of selected links can thus prevent large scale outages as demonstrated for power transmission grids.

Abnormal cascading failure spreading on complex networks

2016 ◽  
Vol 91 ◽  
pp. 695-701 ◽  
Author(s):  
Jianwei Wang ◽  
Enhui Sun ◽  
Bo Xu ◽  
Peng Li ◽  
Chengzhang Ni
Keyword(s):  
Complex Networks ◽  
Cascading Failure

Modeling and Simulation on Knowledge Transfer among Unofficial Groups Based on Communication Networks

2013 ◽  
Vol 411-414 ◽  
pp. 145-151
Author(s):  
Xiao Dong Kou ◽  
Bo Zhang ◽  
Lin Yang
Keyword(s):  
Knowledge Transfer ◽  
Complex Networks ◽  
Communication Networks ◽  
Simulation Analysis ◽  
China National Knowledge Infrastructure ◽  
Simulation Research ◽  
Knowledge Infrastructure ◽  
Learned Societies ◽  
Agent Simulation ◽  
Multi Agent

With features of good interactivity and fast spread speed, unofficial networks play a significant role in knowledge transfer. Based on theories of communication networks and computational modeling method, the transfer situation of complex networks theory within Chinas learned societies, including its rising, spread and development, was modeled and then made simulation analysis by using the Blanche software. By comparing the analysis results with periodicals data from China National Knowledge Infrastructure, the effectiveness of the built model and the reliability of Blanche in multi-agent simulation research are all validated. Furthermore, the future development of complex networks theory in China is predicted as well.

scholarly journals Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hui Teng ◽  
Yukun Ma ◽  
Di Teng
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Association Rules ◽  
Association Rule ◽  
Simulation Analysis ◽  
Pharmaceutical Research ◽  
Accurate Analysis ◽  
Systematic Analysis ◽  
Relationship Of ◽  
The Relationship

Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis.

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