Adaptive Zone-1 Setting Following Structural and Operational Changes in Power System

The understanding of dynamics of data streams is greatly affected by the choice of temporal resolution at which the data are discretized, aggregated, and analyzed. Our paper focuses explicitly on data streams represented as dynamic networks. We propose a framework for identifying meaningful resolution levels that best reveal critical changes in the network structure, by balancing the reduction of noise with the loss of information. We demonstrate the applicability of our approach by analyzing various network statistics of both synthetic and real dynamic networks and using those to detect important events and changes in dynamic network structure.

One of the most characteristic features of biological molecular networks is that the network structure itself changes, depending on the cellular environment. Indeed, activated molecules show a variety of responses to distinctive cell conditions, and subsequently the network structures of active molecules also change. Here we present an approach to trace the network structure changes by using the graphical chain model developed from the gene expression data. The previous procedure for applying the graphical chain model to the expression profiles of a limited number of genes has been improved to analyze the entire set of genes. Furthermore, the chain model has been rearranged according to the association strength, and was scrutinized to identify the candidates of essential gene-gene relationships for the network changes, by using the path consistency algorithm. The improved procedure was applied to the expression profiles of 8,427 genes, which were measured in two distinctive stages of liver cancer progression. As a result, the chain model of the 18 gene cluster relationships with strong associations was inferred, in which the coordination of clusters was described in the cell stage progression, and the gene-gene relationships between known cancer-related genes causing the progression were further refined. Thus, the present procedure is a useful method to model the network structure changes in the cell stage progression, and to clarify the gene candidates for the progression.

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives

The opportunity for distributed generators to be connected to the power system has been increasing since the introduction of electricity deregulation. Moreover, a power system which has a new concept such as a micro-grid or a smart-grid is going to appear. The increase in the uncertainty of power flow and the power system operation under an irregular system configuration is supposed in such new power systems. And the sensitivity of a protection relay may decrease or a protection relay may miscoordinate with other protection relays. Under the above conditions, to prevent the fault expansion is required of the electric power utilities. From the background, the development of a program that can check the relay setting and the coordination between protection relay systems is desired.The development of “Support System for Setting and Coordination between protection relays” called SSSC was initiated in 2006, and it will be completed in 2011. SSSC has the following features;·It enables us to check whether the protection relay is set as operate correctly against all of assumed system faults.·It enables us to check automatically whether the coordination between the protection relays is proper as prevent the fault extension even if an unexpected condition occurs.·It enables us to analyze the response of the protection relays in the power system where some apparatus with nonlinear characteristic is installed.This paper describes the prototype of the SSSC based on the dynamic analysis like Y-method. Furthermore, in this paper, the checking method of coordination between protection relays for short circuit fault, and the verification results of the prototype in the 6.6kV model distribution system are described.

Cooperation between ports is known to enhance their competitiveness. This study aims to reveal changes in the global shipping network structure and evaluate the competitiveness of cooperating ports in the shipping network as port connectivity. We apply a backbone flow algorithm, which creates an initial shipping network with backbone flow and reconstructs the network using an adaptive large-neighborhood search, to solve a liner shipping network design problem. Network science measures are used to evaluate changes in network structure and port connectivity. The cooperation between the Osaka and Kobe ports is analyzed as a case study. We find that draft development allows large-sized vessels, which cannot currently call at the Osaka and Kobe ports, to dock there, enhancing their competitiveness. This increased competitiveness surpasses that of the Kaohsiung port but remains lower than that of other large Asian hub ports, including Busan, Singapore, and Tanjung Pelepas. Our findings provide guidelines for developing port strategies to attract more port calls and enhance competitiveness through port cooperation.

While quantitative ethnographers have used epistemic network analysis (ENA) to model trajectories that show change in network structure over time, visualizing trajectory models in a way that facilitates accurate interpretation has been a significant challenge. As a result, ENA has predominantly been used to construct aggregate models, which can obscure key differences in how network structures change over time. This study reports on the development and testing of a new approach to visualizing ENA trajectories. It documents the challenges associated with visualizing ENA trajectory models, the features constructed to address those challenges, and the design decisions that aid in the interpretation of trajectory models. To test this approach, we compare ENA trajectory models with aggregate models using a dataset with previously published results and known temporal features. This comparison focuses on interpretability and consistency with prior qualitative analysis, and we show that ENA trajectories are able to represent information unavailable in aggregate models and facilitate interpretations consistent with qualitative findings. This suggests that this approach to ENA trajectories is an effective tool for representing change in network structure over time.

Social network research has begun to take advantage of fine-grained communications regarding coordination, decision-making, and knowledge sharing. These studies, however, have not generally analyzed how external events are associated with a social network’s structure and communicative properties. Here, we study how external events are associated with a network’s change in structure and communications. Analyzing a complete dataset of millions of instant messages among the decision-makers with different roles in a large hedge fund and their network of outside contacts, we investigate the link between price shocks, network structure, and change in the affect and cognition of decision-makers embedded in the network. We also analyze the communication dynamics among specialized teams in the organization. When price shocks occur the communication network tends not to display structural changes associated with adaptiveness such as the activation of weak ties to obtain novel information. Rather, the network “turtles up.” It displays a propensity for higher clustering, strong tie interaction, and an intensification of insider vs. outsider and within-role vs. between-role communication. Further, we find changes in network structure predict shifts in cognitive and affective processes, execution of new transactions, and local optimality of transactions better than prices, revealing the important predictive relationship between network structure and collective behavior within a social network.

The impact of interorganizational systems (IOSs) on the structure of market networks is analyzed from a management perspective. A research framework is applied to various organizational settings, yielding a range of mixed mode forms in which elements of both market and hierarchy are evident. These forms are more complex than the simple network or hybrid structures postulated in the management and information systems literature. The framework represents a departure from electronic markets theory, questioning its basic predictions that as companies trade electronically there will be proportionately more markets than hierarchies. Instead, IOSs make possible relationships that combine market and hierarchy elements simultaneously. Although economic forces are driving the changes in network structure, economic variables are tempered by individual firm strategies reflecting investment, network structure and IOS choices. The implications for theory are that traditional analyses of network structures and competition in business markets do not describe or explain adequately the structure and dynamics of competition in an electronic trading environment. The implications for managers are that they should consider the effects of mixed mode network structures on their processes for forming and managing business relationships supported by IOSs. The contribution of the paper is to provide a more accurate model of competition in business markets by demonstrating that multiple forms of mixed mode network structures exist. The mixed mode proposition is illustrated with case data from a range of mixed mode network structures.

Optimal allocation of fault current limiters for sustaining overcurrent relays coordination in a power system with distributed generation

Agent-based modeling of China’s rural–urban migration and social network structure

Network analysis provides a powerful framework for the interpretation of genome-wide data. While static network approaches have proved fruitful, there is increasing interest in the insights gained from the analysis of cellular networks under different conditions. In this work, we study the effect of stress on cellular networks in fission yeast. Stress elicits a sophisticated and large scale cellular response, involving a shift of resources from cell growth and metabolism towards protection and maintenance. Previous work has suggested that these changes can be appreciated at the network level. In this paper, we study two types of cellular networks: gene co-regulation networks and weighted protein interaction networks. We show that in response to oxidative stress, the co-regulation networks re-organize towards a more modularised structure: while sets of genes become more tightly co-regulated, co-regulation between these modules is decreased. This shift translates into longer average shortest path length, increased transitivity, and decreased modular overlap in these networks. We also find a similar change in structure in the weighted protein interaction network in response to both oxidative stress and nitrogen starvation, confirming and extending previous findings. These changes in network structure could represent an increase in network robustness and/or the emergence of more specialised functional modules. Additionally, we find stress induces tighter co-regulation of non-coding RNAs, decreased functional importance of splicing factors, as well as changes in the centrality of genes involved in chromatin organization, cytoskeleton organization, cell division, and protein turnover.

Technological developments in protective devices have established the basis for appearance of numerical overcurrent relays (OCRs), which enable the users to apply their desired time‐current characteristics (TCCs). This study propounds novel stepwise and combined stepwise–piece‐wise linear TCCs and presents clear procedure to utilise them for coordinating OCRs in large meshed power systems. The TCCs keep constant time interval between the main/backup relay pairs within entire fault current range. They are examined first by coordinating the OCRs in a 4‐bus power system and by coordinating the ground fault OCRs in a practical 60 kV looped power system. Then, the OCRs of the IEEE 14‐bus test system, which is a rather large meshed power system with 39 OCRs and 102 main/backup pairs, are coordinated by using the novel TCCs. The same relays in the aforesaid power systems are coordinated using some non‐standard TCCs recently introduced in the literature. The comparison verifies that the lowest operating times are achieved by using the novel TCCs. The devised TCCs are simply formed as look‐up tables to be exactly set on the existing industrial relays. This fact is verified by setting them on an industrial OCR, and then, by testing the relay through the current injection method.

BackgroundPatients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) show functional and structural connectivity alterations in the default mode network (DMN) while cerebrovascular disease (CeVD) shows functional and structural connectivity changes in the executive control network (ECN). Such disruptions are associated with memory and executive function impairment, respectively. Concurrent AD and CeVD pathology is associated with a higher rate of cognitive decline and differential neurodegenerative patterns. Together, such findings are likely reflective of different underlying pathology in AD with and without CeVD. However, few studies have examined the effect of CeVD on network functional connectivity (task-free functional magnetic resonance imaging (fMRI)) and structural connectivity (diffusion MRI) of the DMN and ECN in aMCI and AD using a hypothesis-driven multiple seed-based approach.MethodsWe examined functional and structural connectivity network changes in 39 aMCI, 50 aMCI+CeVD, 47 AD, 47 AD+CeVD, and 65 healthy controls (HCs) and their associations with cognitive impairment in the executive/attention and memory domains.ResultsWe demonstrate divergent DMN and ECN functional connectivity changes in CeVD and non-CeVD subjects. Compared with controls, intra-DMN hippocampal functional connectivity reductions were observed in both AD and AD+CeVD, while intra-DMN parietal and medial prefrontal-parietal functional connectivity was higher in AD+CeVD and aMCI+CeVD, but lower in AD. Intra-ECN frontal functional connectivity increases and fronto-parietal functional connectivity decreases occurred in CeVD but not non-CeVD subjects. Such functional connectivity alterations were related with cognitive impairment in a dissociative manner: intra-DMN functional connectivity changes were associated with worse cognition primarily in non-CeVD groups, while intra-ECN functional connectivity changes were associated with worse cognition primarily in CeVD groups. Additionally, CeVD and non-CeVD groups showed overlapping and distinct alterations in inter-network DMN-ECN functional connectivity depending on disease severity. In contrast to functional connectivity, CeVD groups had greater network structural connectivity damage compared with non-CeVD groups in both aMCI and AD patients. Network structural connectivity damage was associated with worse cognition.ConclusionsWe demonstrate differential functional and structural network changes between aMCI and AD patients with and without CeVD through diverging and deleterious network-based degeneration underlying domain-specific cognitive impairment.

An analytic model for fault diagnosis of power system using optimization technique is expressed as unconstrained 0-1 integer programming problem, and consequently faulty equipment identification can be solved by refined mathematical operation. Considering the configuration of automatic devices in modern power systems, such as protective relays and reclosing relays, an improved analytic model and optimization technique-based method for fault diagnosis of power system is proposed in this paper. The evaluation criteria of the presented model is improved considering the relationship of multiple main protective relays, backup protective relays, malfunctioning protective relays and reclosing relays. Improvements of analytic model for fault diagnosis of electric power system based on optimization techniques are presented firstly. A brief description about the modulars and functions of the online fault diagnosis software which is developed by the authors for Jiangsu Provincial Power Company is given. The adopted EMS data acquisition method and simulated online test results for the power system of Jiangsu Power Company are described.

In order to sustain the stability of the power system, the power line carrier direction protection, as the main protection, is required to rapidly and exactly and selectively remove the fault in the high voltage or extra-high voltage system of our county. Thus directional relay used by protection equipment must be able to correctly and rapidly reflect the orientation of the fault site, namely positive direction or negative direction. At present, the generally used directional relays based on the sequence components, transient energy directional relay and variation of power frequency component based directional relay etc. can rapidly and correctly determine the orientation of the fault site when a single fault or multiple faults with the same orientation occur in the power system and such directional relays have comparatively high sensitivity. But when faults at different directional sites simultaneously occur on the different phases within the protected range, abnormal performance of directional relays above would appear, and which would finally result in the fault being removed with time delay or the non-action of protection relays. This paper theoretically analyzes this abnormal performance of directional relays mentioned above, and RTDS (real time digital simulation) dynamic simulation test results prove this point. And an integrated directional relay with high sensitivity is presented in this paper, which could exactly and quickly act under the multiple fault conditions. Theoretical analysis and lots of dynamic simulation tests show that the integrated directional relay presented in the paper could quickly and precisely decide the fault site direction under multiple fault conditions, with the same sensitivity as that under the single fault condition