Top PDF Mathematical Study of Complex Networks: Brain, Internet, and Power Grid

Mathematical Study of Complex Networks: Brain, Internet, and Power Grid

Mathematical Study of Complex Networks: Brain, Internet, and Power Grid

Many existing fluid-flow models of the Internet congestion control algorithms ignore the effects of buffers on the data flows for simplicity. In particular, they assume that all links in the path of a flow are able to see the original source rate. However, a fluid flow in practice is modified by the queueing processes on its path, so that an intermediate link will generally not see the original source rate. In this chapter, a more accurate model is derived for the behavior of the network under a congestion controller, which takes into account of the effect of buffering on output flows. It is shown how this model can be deployed for some well- known service disciplines such as first-in first-out and generalized weighted fair queueing. Based on the derived model, the dual and primal-dual algorithms are studied under the common pricing mechanisms, and it is shown that these algorithms can become unstable. Sufficient conditions are provided to guarantee the stability of the dual and primal-dual algorithms. Finally, a new pricing mechanism is proposed under which these congestion control algorithms are both stable.
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Analysis of EEG signals using complex brain
networks

Analysis of EEG signals using complex brain networks

The human brain is so complex that two mega projects, the Human Brain Project and the BRAIN Initiative project, are under way in the hope of answering im- portant questions for peoples’ health and wellbeing. Complex networks become powerful tools for studying brain function due to the fact that network topologies on real-world systems share small world properties. Examples of these networks are the Internet, biological networks, social networks, climate networks and com- plex brain networks. Complex brain networks in real time biomedical signal pro- cessing applications are limited because some graph algorithms (such as graph isomorphism), cannot be solved in polynomial time. In addition, they are hard to use in single-channel EEG applications, such as clinic applications in sleep scoring and depth of anaesthesia monitoring.
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Analysis of EEG signals using complex brain
networks

Analysis of EEG signals using complex brain networks

are hard to compare due to different frequency samplings and sizes of data. Fortunately, complex networks (CN) are efficient tools to conduct the challenges study of brain function in small genes and long EEG waves. Because CNs have been widely applied in the study of biological systems, neural networks, social net- works, the Internet and the World Wide Web (Boccaletti et al. 2006), it has been found that the topologies on these networks share some similar properties, such as small world properties (Watts & Strogatz 1998) and scale-free features (Barab´ asi & Albert 1999). The characteristic of different complex systems sharing the same network structure leads biomedical engineers, physicists, mathematicians and computer scientists to participate in neuroscience research. For example, a robust network would be in power-law degree distribution (Albert et al. 2000). Then researchers would see that the complex brain networks from healthy sub- jects should be more like a small-world structure during sleep. Conversely, the dysfunctional brain networks, such as with seizure or alcoholism, should exhibit a random topology. In other words, researchers can find some meaningful results by means of CNs although there are no universally accepted complex brain network models.
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Peak Power Management of Smart Grid Power Networks Using ESC for MPPT in PV Solar Systems
Gayatri Alaparthy & B Anji Babu

Peak Power Management of Smart Grid Power Networks Using ESC for MPPT in PV Solar Systems Gayatri Alaparthy & B Anji Babu

The efficiency of the inverter is measured on the basis of its ability to convert the ac into dc. Presently available inverters have efficiency of about 95 percent to 98.5percent and thus choice of correct inverter is very important aspect in the design process of power plant. The less efficient inverters can be used in the isolated systems or the grid tie. Inverters with efficiency less than 95percent are readily available in the market. Inverters when used at the low end of their maximum power are less efficient and therefore using the inverters at low end of maximum power should be avoided. Inverters are most efficient when used in the range of 30 to 90percent of power.
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A Study on Power System: Smart Grid

A Study on Power System: Smart Grid

ABSTRACT: An electric power system is a network of components used to supply, transmit, distribute and use electrical power. Smart grid is a new power system developed which intelligently increases the efficiency in terms of power consumption. This paper presents the structure and components of the smart grid. The characteristics of the smart grid and its benefits over the present grid have also been explained. It presents the advantages of using smart technologies in homes, appliances, meters and vehicles, leading to greater efficiency and a decrease in carbon emissions. The concept of using consumer interaction through information and communication technology (ICT) to reduce the consumption of electricity has been explained. The difficulties in the implementation of the grid have been discussed. Future scope of the smart gird in India has also been mentioned.
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A Survey on - Vulnerability Analysis on Cascading Failure in Power Grid Complex Network

A Survey on - Vulnerability Analysis on Cascading Failure in Power Grid Complex Network

Where and corresponds to ( ) with a positive sign and negative sign, respectively. It is notable that in [14] the extended betweenness is interpreted as a representation of the total power transmitted on a branch in the grid. However, in the power flow theories, the positive and negative power flow on a branch will cancel each other; in this case, the actual load is measured differently as the sum of both values. As the focus of this paper is to develop a CFS based on extended betweenness for cascading failure analysis, we adopted the definition of ( ) as originally proposed by E. Bompard , while further modifications can be implemented to adapt to the power flow assumptions. In this paper, we adopt extended betweenness as the load on each bus and branch because of its strength to capture both topological and electrical characteristics of power grids. Although the term extended betweenness resembles the concept of betweenness centrality in graphic theory and complex network studies, it should be noted that there is a distinctive difference between them as the extended betweenness is not based on the geodesic shortest paths. Although it borrows the idea of pairwise transmission, the “extended betweenness” is not purely topological as it does not characterize the power flow as a geodesic shortest path. Instead, it is the overall power transmission capacity according to a power system based model; consequently, the measurement is closer to the real power systems. In addition, this model utilizes the sensitivity and flow-limit on each branch to calculate the transmission capacity; thereby it provides a better approximation on power transmission than pure topological approaches as well. In summary, it captures physical characteristics of a real power system that add to its robustness while still retains the strength of security analyses of complex networks.
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An Improvement Approach for Reducing Transmission Power in Wireless Sensor Networks

An Improvement Approach for Reducing Transmission Power in Wireless Sensor Networks

In first part of our experiment setup, we have two different settings based on mote mobility; slow mobility and brisk mobility. The packet delivery ratio and power transmission levels are expected to come head to head in a trade-off and hence are used as our performance metrics. Both of the experiments are carried out in RF Digital Lab, IIUM. Testing is performed by moving the mobile sender along the grid shown in figure 3 from the point (2,1) through (2,7) then to (13,7) and back to (2,7). Note that, the base station mote was stationary at position (2,9). The aim of this experiment is to see how much energy could be saved on successful packet delivery based on different positions of motes/nodes and blocking scenarios such as furniture in RF lab. In second phase of our experiment setup, we aim at finding the effect of proposed TPC mechanism in static mode with different distances between the transceiver (Tx) and receiver (Rx). Moreover, we examine the efficiency of this mechanism with different height of the nodes with respect to the lab floor. In this case, we always calculate the
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Power Transmission and Distribution Monitoring using Internet of Things (IoT) for Smart Grid

Power Transmission and Distribution Monitoring using Internet of Things (IoT) for Smart Grid

In designing the transmission and distribution based IoT one can consider using Wireless Sensor Network (WSN) and General Packet Radio Services (GPRS). A WSN is a wireless network formed by large numbers of sensor nodes where each node equipped with sensors to monitor physical conditions. GPRS is a GSM-based wireless communication packet network that provides wide-range IP protocol connection from point to point node. GPRS is a high-speed data processing, for which allows multiple packet data transmission, extensive signal coverage, fast installation feature and low maintenance cost [7]. GPRS technology seems out of date if compared to the 3G/4G technologies. However it’s still reliable and good alternative for data processing and communication. Moreover, several transmission and distribution networks in Indonesia are located in a remote area where the 3G/4G network is not available.
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Fuzzy Based Hybrid Wave, Photo Voltaic and Fuel Cells Power Generation System Dynamic Stability Analysis with Distributed Power Grid

Fuzzy Based Hybrid Wave, Photo Voltaic and Fuel Cells Power Generation System Dynamic Stability Analysis with Distributed Power Grid

Since the depletion of the fossil fuel reserve on the earth , the need of usage of the renewable energy is of utmost importance in the current scenario. The renewable generation systems would be integrated to the bulk transmission line with the issues like the harmonics, synchronisation etc [1]. While large renewable energy generation is taking place[1] even the small scale renewable energy system is taken in to account in [2] and [3] for grid integration.A grid integration technique with the PV and the Wind Energy Conversion System(WECS) is carried out in the literature [4] which controls the VSC to provide a efficient grid integration applied. In [5] the microgrid kind of implementation is carried out which is a retrofitted PV and Wind hybrid system .In [6] the power management system which combines both the PV and the wind hybrid system is developed.
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INTERNET AND GRID COMPUTING

INTERNET AND GRID COMPUTING

The growth of the Internet, along with the availability of powerful computers and high- speed networks as low-cost commodity components, is changing the way scientists and an engineer do computing, and is also changing how society in general manages information and information services. These new technologies have enabled the clustering of a wide variety of geographically distributed resources, such as supercomputers, storage systems, data sources, instruments, and special devices and services, which can then be used as a unified resource. Furthermore, they have enabled seamless access to and interaction among these distributed resources, services, applications, and data. The new paradigm that has evolved is popularly termed as “Grid computing”. Grid computing and the utilization of the global Grid infrastructure have presented significant challenges at all levels including conceptual and implementation models, application formulation and development, Programming systems and services resource management, networking and security and
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Analyzing the similitude between Internet Service Providers and Brain Functional Networks

Analyzing the similitude between Internet Service Providers and Brain Functional Networks

________________________________________________________________________________________________________ Abstract— The objective of this paper is to compare the brain functional network with the ISP(Internet Service Provider) Topology. Even-though the current internet topology works well, there are some problems such as traffic, slow rate of transmission, robustness, scalability, QoS, etc. Networks fail in untold situations and they do not have self adaptive nature. To overcome these problems networks can be designed with some measures which improve the performance of the network. For the designing of such robust networks, we can use properties of a biological network particularly that of brain functional networks, as the human brain has self-adaptive nature and does not fail in most of the situations. By analyzing the similarity measures between ISP and brain functional networks, we can incorporate the features of the brain which make it fail-free into the architecture of ISP. The comparison is done by using measures such as degree, clustering coefficient, modularity, etc. This project will be helpful in designing more robust and self-adaptable networks. Keywords: Brain functional network, fMRI, Internet Service Provider.
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Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health

Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health

Results: The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (E local ), global efficiency (E global ), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal–temporal regions in obese subjects compared with non-obese controls. Conclusion: We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese. Keywords: obesity, diffusion tensor imaging, DTI, generalized q-sampling imaging, GQI, graph theoretical analysis, GTA, network-based statistical analysis, NBS
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A novel framework for community modeling and characterization in directed temporal networks

A novel framework for community modeling and characterization in directed temporal networks

Many seminal studies have revealed that communities are ubiquitous in networked sys- tems of diverse nature. In fact, community structures have been identified in social, financial, biological, and in many other networks (Girvan and Newman 2002; Newman 2006; Estrada 2011; Benson et al. 2016; Yang and Leskovec 2014). Such communities typically have a complex structure: they present a hierarchical and overlapping organi- zation (Ravasz et al. 2002; Palla et al. 2005; Lancichinetti et al. 2009; Pons and Latapy 2011) and their components have heterogeneous attitudes in the link formation process (Palla et al. 2007), acting as sources, mainly generating connections, or as drains, on the contrary. Further challenges have to be tackled toward a comprehensive analysis of real-world systems. First, evidence suggests that the patterns of connections between the components of a real-world networked system evolve in time (Volz and Meyers 2008; Holme and Saramäki 2012; Pastor-Satorras et al. 2015; Latapy et al. 2018). Second, the nature of interactions in many biological and technological systems has an inher- ent direction and is thus nonsymmetrical (Leicht and Newman 2008). Finally, there exist connections that are generated by dyadic relationships between nodes, rather than by
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Two reduction methods to simplify complex ODE mathematical models of biological networks and a case study: The G1/S checkpoint/DNA-damage signal transduction pathways

Two reduction methods to simplify complex ODE mathematical models of biological networks and a case study: The G1/S checkpoint/DNA-damage signal transduction pathways

Complex biological systems include many different processes, such as metabolism, cell growth and cell division, as in the case of cancer. The complexity of these processes emerges from the interactions components, such as genes, proteins and metabolites (Sauer et al., 2007). For instance, Barillot and his colleagues (2012) discussed this in "Computational Systems Biology of Cancer". Zinovyev (2014) said that in order to understand cancer, one must understand the disease mechanism by understanding cell cycle (the process by which individual cells divide into two cells), death, motility, and the survival immune and angiogenesis mechanisms, as well as DNA repair and replication. For example, if the cell DNA changes, it may transfer to become a tumour cell; this infected cell grows faster than a normal one and the change occurs at the cell and tissue levels (Castiglione et al., 2014). Immunity is considered a complex system; it operates with complex self-regulatory networks, emergent attributes and nonlinear dynamics. Ideker and his colleagues (2001) said that the term "emergent" is applicable to biological systems as it explains the emergence of a complex structure from simple interactions of components. In the same way, Weng and his colleagues (1999) said that complexity arises from the connections between the components and the spatial correlations between them.
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An Algorithm for using Internet of Things (IoTs) to Improve Load Management in Electric Power Grid

An Algorithm for using Internet of Things (IoTs) to Improve Load Management in Electric Power Grid

Several new technologies, for example, the Internet of Things (IoTs) continue to surface in the frontage of ubiquitous and pervasive computing. Internet of things is slowly being embraced in different domains to support control and monitoring systems. The advent of microprocessors embedded with communication facilities has enabled the possibility of integrating ICTs within people and their environments. With the power utilities industry grappling with serious issues like load management which has a potential of damaging their equipment, first movers are turning to advanced technologies such as the IoTs to achieve demand- side management. The purpose of this study was to conduct a theoretical and empirical review on the approaches used by Power utilities to manage load in order to determine how IoTs can be used particularly by Zimbabwe’s Power utility to solve the supply-demand problem. Currently, the load management approaches used by the Power utility in Zimbabwe are load shifting and load shedding. A conceptual model was developed using C++ guided by the algorithm for load management. The model development was motivated by the research gap establish from the literature review and the problem faced by the Power utility in Zimbabwe in balancing demand and supply during peak periods. The idea is modelled around continuous monitoring of the feeder or substation, activating the automatic control and carrying out load allocation procedure based on priority settings, connection, and re-connection timings. The proposed model is also based on the dependence of demand and consumer priority perception. The model will ensure that electricity is available for basic and essential use in times of increased demand. It requires that load demand is constantly monitored to trigger automatic control and appliances should connect to the electric power grid using smart plugs.
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Design A Charge Controller For Wind Generator

Design A Charge Controller For Wind Generator

Solar thermal power stations operate in the USA and Spain, and the largest of these is the 354 MW SEGS power plant in the Mojave Desert. The world's largest geothermal power installation is The Geysers in California, with a rated capacity of 750 MW. Brazil has one of the largest renewable energy programs in the world, involving production of ethanol fuel from sugar cane, and ethanol now provides 18 percent of the country's automotive fuel. Ethanol fuel is also widely available in the USA.

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Mathematical model of an off-grid hybrid solar and wind power generating system

Mathematical model of an off-grid hybrid solar and wind power generating system

Therefore, a strict analogy between this hydrodynamic model in Fig. 1 and an off-grid electric power generator associated to a storage system and a specific consumer is initially considered. In the following section Bernoulli’s theorem and standard methods in solving ordinary differential equations are used to obtain sensible answers to the proposed problem. The effect of small perturbations in the function p(t) on the response of the system are considered in the third section. Finally, in the Conclusions a generalization to different types of consumers (other than Torricelli’s smart consumer, for whom the strict hydrodynamic analogy holds) is proposed and further extension of the present work to more realistic cases is suggested.
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On the application of advanced power electronics technology in smart grid

On the application of advanced power electronics technology in smart grid

SVC is a kind of transmission equipment. Its most remarkable characteristic is the strong flexibility. It has broad functions such as adjusting the voltage, controlling current, improving the stability of transmission system and strengthening the increase transmission capacity and so on. It is a new method to help our country to establish a smart grid. China imported several sets of SVC equipment from other countries in the 1980s and in 2004, under the auspices of the national power grid; the electric power research institute of China independently developed a set of SVC equipment. Research and development success marks THAT China has fully mastered the SVC system manufacturing technology. The next few years, through the unremitting efforts, SVC power system popularized in our country. SVC has the function of reactive compensation and the trend of optimization, which can not only improve the power grid transmission capacity and transmission efficiency of power quality but can also; improve the power grid security and stability. In addition, it is also suitable for various levels of power grid. The SVC technology has promoted the process of power grid in the intelligent direction in our country. By the year 2009, 20 sets of SVC have been put into use, saving a lot of fiscal expenditure of the government. One set of equipment has saved more than one thousand millions RMB. Below is the chart about the rate of the growth of the amount of fiscal expenditure SVC saved in these years:
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MITIGATION OF VOLTAGE SAGS IN A HYBRID DISTRIBUTION SYSTEM BY USING INTELLIGENT TECHNIQUE

MITIGATION OF VOLTAGE SAGS IN A HYBRID DISTRIBUTION SYSTEM BY USING INTELLIGENT TECHNIQUE

A voltage-source converter is a power electronic device, which can generate a sinusoidal voltage with any required magnitude, frequency and phase angle. Voltage source converters are widely used in adjustable-speed drives, but can also be used to mitigate voltage dips. The VSC is used to either completely replace the voltage or to inject the ‘missing voltage’. The ‘missing voltage’ is the difference between the nominal voltage and the actual. The converter is normally based on some kind of energy storage, which will supply the converter with a DC voltage. The solid-state electronics in the converter is then switched to get the desired output voltage. Normally the VSC is not only used for voltage dip mitigation, but also for other power quality issues, e.g. flicker and harmonics.
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Comparative Study on Evolution of State of Art Practices on Smart Grid with the Challenges Faced and Transitory Solutions

Comparative Study on Evolution of State of Art Practices on Smart Grid with the Challenges Faced and Transitory Solutions

The transparency in Communication between various clusters in smart grid has though solved many problems related to monitoring and control but led to serious threat to the security of data. As the data exchange is all on web, which is vulnerable, can be easily accessed and tampered. The cyber-attack can mislead with wrong information and even directly or indirectly obstruct the system. The attack can be classified mainly in two categories i.e passive and active attack. Passive attack can be understood as the theft of data and using the same without causing any damage to the existing system. Where as in case of active attack the real time data can be distorted and directly affect the system. Active attack can be dangerous which can even lead
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