Network hierarchy evolution and system vulnerability in power grids

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft

Power system vulnerability and performance: application from complexity scienze and complex network

Power system has been acknowledged as a complex system owing to its complexity resulting from interactions of different layers which include physical layer like generators, transformers, substations and cyber layer like communication units and human decision layer. Complex network theory has been widely used to analyze the power grids from basic topological properties to statistic robustness analysis and dynamic resilience property. However, there are still many problems need to be addressed. This thesis will pay more attention on the application and extension of complexity science and complex network theory in power system analysis from different aspects

Spatial and performance optimality in power distribution networks

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Complex network theory has been widely used in vulnerability analysis of power networks, especially for power transmission ones. With the development of the smart grid concept, power distribution networks are becoming increasingly relevant. In this paper, we model power distribution systems as spatial networks. Topological and spatial properties of 14 European power distribution networks are analyzed, together with the relationship between geographical constraints and performance optimization, taking into account economic and vulnerability issues. Supported by empirical reliability data, our results suggest that power distribution networks are influenced by spatial constraints which clearly affect their overall performance.Peer ReviewedPostprint (author's final draft

Sublethal and intergenerational effects of fipronil on Binodoxys communis larvae based on transcriptome sequencing

Fipronil is widely used in the agricultural world as an efficient phenylpyrazole insecticide to control pests. Binodoxys communis is a key parasitic natural enemy of major homopteran pests and can successfully control the population of pests such as cotton aphids. It has not yet been studied what effects would sublethal doses of fipronil have on Binodoxys communis larvae. Here, this study evaluated the effect of fipronil on Binodoxys communis larvae and analyze the transcriptome results. The results showed that LC10 (1.19 mg/L) and LC25 (1.73 mg/L) had significant negative effects on the survival rate and parasitism rate of F0 generation. Moreover, exposure to high concentrations (LC25) of fipronil still had obvious passive effect on the F1 generation of Binodoxys communis. These results indicated that sublethal doses of fipronil have malignant effects on the biological functions of parasitoids and their offspring. The results of transcriptome analysis showed that differentially expressed genes (DEGs) of Binodoxys communis after LC10 treatment are mainly related to immunity and detoxification. LC25 treatment instead resulted in changes in the expression of genes related to nutrition, energy and metabolism reactions. Seven of the identified DEGs were selected for real-time fluorescence quantitative PCR analysis. To the best of our knowledge, this is the first report to evaluate the sublethal, intergenerational, and transcriptomic side effects of fipronil on larvae of parasitic natural pest enemies. Our findings provide data to accurately assess the risk of fipronil usage on Binodoxys communis larvae, and provide important theoretical support for the comprehensive prevention and control of natural enemies and pesticides

Overview of China’s Antarctic research progress 1984–2016

It is more than 30 years since the first Chinese National Antarctic Research Expedition (CHINARE) landed in Antarctica in 1984, representing China’s initiation in polar research. This review briefly summarizes the Chinese Antarctic scientific research and output accomplished over the past 30 years. The developments and progress in Antarctic research and the enhancement of international scientific cooperation achieved through the implementation of the CHINARE program have been remarkable. Since the 1980s, four permanent Chinese Antarctic research stations have been established successively and 33 CHINAREs have been completed. The research results have been derived from a series of spatiotemporal observations in association with various projects and multidisciplinary studies in the fields of oceanography, glaciology, geology, geophysics, geochemistry, atmospheric science, upper atmospheric physics, Antarctic astronomy, biology and ecology, human medicine, polar environment observation, and polar engineering

On the difficulty (and success) of correlating empirical data and (extended) topological measures in power grid networks

Power grids are considered complex networks. Their structure and dynamics have been thoroughly studied and many topological measures have been used to classify them, evaluate their behaviour or model their response to malfunctions. Results have been theoretical and correlations between real dynamical behaviour (i.e., major events) and structural measures have not yet been found. New electrically modified topological measures have been recently used to quantify the ability of a network in sustaining its functions. Here, we present a first attempt to correlate these new measures with real malfunction data for some European power transmission grids. Similar behaviour is found, in terms of robustness to selected attacks to buses, between different networks. These behaviours can be correlated with similar probability distributions of major events, identifying similar dynamical response among topologically similar grids. This would raise hopes in finding a more meaningful linkage between structural measures and the real dynamical output of a grid.Peer Reviewe

A perspective overview of topological approaches for vulnerability analysis of power transmission grids

Vulnerability analysis is a key issue in power systems since power transmission grids play a crucial role as a critical infrastructure. The power grid structure (number of nodes and lines, their connections, and their physical properties and operational constraints) is one of the main factors to assure power system security. Complex network theory as a promising topological approach for the structural vulnerability analysis has been widely used in many different fields. Recently, many complex network metrics have been proposed to assess the topological vulnerability of power transmission grids. However, these approaches are purely topological and fail in capturing the specific features of power systems. In this paper, an extended topological approach which incorporates electrical features such as flow path, line flow limits, etc., is presented. Three new metrics, net-ability, electrical betweenness and entropy degree are provided and used to assess structural vulnerability in power transmission grid

On the difficulty (and success) of correlating empirical data and (extended) topological measures in power grid networks

Power grids have entered the complex networks realm for quite a long time now. Their structure (i.e., topology) and dynamics have been thoroughly studied and many topological measures have been used in order to classify them, evaluate their behavior in terms of robustness or model their dynamic response to malfunctions. Generally speaking, results have been mainly theoretical and sound correlations between real grid’s dynamical behavior (i.e., malfunctions and major events) and any of the mentioned before measures have not yet been found. In recent years, though, new extended topological measures have been used to quantify the ability of a network in sustaining its basic functions. In this paper we present a first attempt to correlate these new measures with real malfunction data for some major European power transmission grids. Similar behavior is found, in terms of robustness to selected attacks to buses, between different networks. This is measured by means of extended topological indexes electrically better defined. These behaviors can be (weakly) correlated with similar probability distributions of major events, identifying similar dynamical response among topologically similar grids. This would raise hopes in finding a more meaningful and significant linkage between structural measures and the real dynamical output (i.e., major events) of a grid.Peer Reviewe

On the difficulty (and success) of correlating empirical data and (extended) topological measures in power grid networks

Power grids have entered the complex networks realm for quite a long time now. Their structure (i.e., topology) and dynamics have been thoroughly studied and many topological measures have been used in order to classify them, evaluate their behavior in terms of robustness or model their dynamic response to malfunctions. Generally speaking, results have been mainly theoretical and sound correlations between real grid’s dynamical behavior (i.e., malfunctions and major events) and any of the mentioned before measures have not yet been found. In recent years, though, new extended topological measures have been used to quantify the ability of a network in sustaining its basic functions. In this paper we present a first attempt to correlate these new measures with real malfunction data for some major European power transmission grids. Similar behavior is found, in terms of robustness to selected attacks to buses, between different networks. This is measured by means of extended topological indexes electrically better defined. These behaviors can be (weakly) correlated with similar probability distributions of major events, identifying similar dynamical response among topologically similar grids. This would raise hopes in finding a more meaningful and significant linkage between structural measures and the real dynamical output (i.e., major events) of a grid.Peer ReviewedPostprint (published version