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Journal ArticleDOI: 10.1080/23789689.2019.1708182

A hybrid approach for transmission grid resilience assessment using reliability metrics and power system local network topology

04 Mar 2021-Vol. 6, pp 26-41
Abstract: Due to increasing threats on power systems from various extreme events such as adverse weather and cyber/physical attacks, research on power grid resilience is recently gaining a substantial tracti...

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Topics: Resilience (network) (64%), Electric power system (56%), Grid (52%)
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8 results found


Journal ArticleDOI: 10.1109/JIOT.2020.3018687
Liudong Xing1Institutions (1)
Abstract: In the Internet of Things (IoT), various devices operate collaboratively in collecting data, relaying information to one another, and processing information intelligently. Due to interactions and dependencies between the IoT devices, the malfunction of one device may trigger a cascade of unexpected and often undesired state changes of other devices, introducing or accelerating catastrophic cascading failures. Understanding the causes of cascading failures and modeling their behavior and effects is crucial for guaranteeing the reliability of IoT systems and delivering the desired quality of service. This article systematically reviews cascading failures modeling and reliability analysis methodologies, as well as mitigation strategies for building the resilience of IoT systems against cascading failures. The review covers diverse IoT applications, from smart grids to smart homes, from sensor networks to IoT cloud computing, and from transportation networks to interdependent infrastructure networks. Opportunities and open research issues are also discussed in relation to restrictions of the current cascading failure models and methods, and potential new technologies and complexity of the constantly evolving IoT systems.

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Topics: Cascading failure (56%), Resilience (network) (52%)

16 Citations


Open accessJournal ArticleDOI: 10.1002/ENV.2629
05 May 2020-Environmetrics
Abstract: As per the records of the World Health Organization, the first formally reported incidence of Zika virus occurred in Brazil in May 2015. The disease then rapidly spread to other countries in Americas and East Asia, affecting more than 1,000,000 people. Zika virus is primarily transmitted through bites of infected mosquitoes of the species Aedes (Aedes aegypti and Aedes albopictus). The abundance of mosquitoes and, as a result, the prevalence of Zika virus infections are common in areas which have high precipitation, high temperature, and high population density. Nonlinear spatio‐temporal dependency of such data and lack of historical public health records make prediction of the virus spread particularly challenging. In this article, we enhance Zika forecasting by introducing the concepts of topological data analysis and, specifically, persistent homology of atmospheric variables, into the virus spread modeling. The topological summaries allow for capturing higher order dependencies among atmospheric variables that otherwise might be unassessable via conventional spatio‐temporal modeling approaches based on geographical proximity assessed via Euclidean distance. We introduce a new concept of cumulative Betti numbers and then integrate the cumulative Betti numbers as topological descriptors into three predictive machine learning models: random forest, generalized boosted regression, and deep neural network. Furthermore, to better quantify for various sources of uncertainties, we combine the resulting individual model forecasts into an ensemble of the Zika spread predictions using Bayesian model averaging. The proposed methodology is illustrated in application to forecasting of the Zika space‐time spread in Brazil in the year 2018.

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Topics: Zika virus (63%), Aedes (51%)

4 Citations



Journal ArticleDOI: 10.1016/J.RESS.2021.107881
Jesus Beyza1, Jose M. Yusta1Institutions (1)
Abstract: Renewable energy sources and cross-border electrical interconnections can significantly impact the security of the supply of power systems. This article jointly analyses the reliability and vulnerability of electrical networks to quantify systems' performance by increasing and decreasing renewable resources and the degree of coupling of electrical infrastructures. This comparison seeks to measure the influence of renewable generation and the impact of interconnection lines on the operational behaviour of systems under different types of contingencies or disturbances. The reliability assessment is performed using PLEXOS, and the vulnerability assessment is carried out with a network disintegration procedure implemented in MATLAB. Here, different statistical indices of the networks are measured. The procedures are applied sequentially in six case studies with different generation mixes and interconnection lines based on the well-known IEEE RTS-96 and IEEE RTS-GMLC test networks. From the analysed cases, the resulting tables and graphs obtained from the simulation are presented, and the joint impact from the two perspectives is compared. The results obtained show that renewable sources have a greater impact on reliability and that electrical interconnections impact both reliability and vulnerability. These conclusions highlight the importance of analysing the operational security of infrastructures taking into account both approaches simultaneously.

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Topics: Vulnerability assessment (57%), Reliability (statistics) (52%), Vulnerability (computing) (52%) ... read more

2 Citations


Journal ArticleDOI: 10.1109/TLA.2021.9448550
Abstract: Electric power systems are prone to disturbances and contingencies, which can trigger cascading failures with severe consequences for society. These undesirable events could disintegrate the electrical infrastructure in areas with disconnected elements. In this article, we propose a novel procedure to restore a collapsed power grid composed of multiple islands and isolated assets. The framework developed identifies the power lines to be closed during the electrical network recovery stages. In the latter, link overload limits and generation thresholds are taken into account. Two disintegrated networks based on the well-known IEEE 57-bus test system are built to demonstrate the performance of our proposal. In summary, this methodology provides a solution to recover the power system optimally and reliably.

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Topics: Electric power system (56%), Cascading failure (55%), Electric power transmission (54%) ... read more

1 Citations


References
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43 results found


Open accessBook
01 Jan 1984-
Abstract: Topics considered include characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security. This book is a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems. Material used was generated in the post-1966 period. Many (if not most) of the chapter problems require a digital computer. A background in steady-state power circuit analysis is required.

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Topics: Power transmission (64%), Electric power (63%), Distributed generation (63%) ... read more

6,152 Citations


Open accessJournal ArticleDOI: 10.1109/TPWRS.2010.2051168
Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.

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Topics: Power-flow study (52%), Power system simulation (51%), Electric power system (51%) ... read more

4,645 Citations


Open accessBook
01 Jan 2006-
Abstract: Introduction. Generating Capacity-Basic Probability Methods. Generating Capacity-Frequency and Duration Method. Interconnected Systems. Operating Reserve. Composite Generation and Transmission Systems. Distribution Systems-Basic Techniques and Radial Networks. Distribution Systems-Parallel and Meshed Networks. Distribution Systems-Extended Techniques. Substations and Switching Stations. Plant and Station Availability. Applications of Monte Carlo Simulation. Evaluation of Reliability Worth. Epilogue. Appendix 1: Definitions. Appendix 2: Analysis of the IEEE Reliability Test System. Appendix 3: Thirdorder Equations for Overlapping Events. Solutions to Problems. Index.

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Topics: Forced outage (53%), Operating reserve (53%), Reliability (statistics) (52%) ... read more

3,691 Citations


Open accessJournal ArticleDOI: 10.1090/S0273-0979-09-01249-X
Gunnar E. Carlsson1Institutions (1)
Abstract: An important feature of modern science and engineering is that data of various kinds is being produced at an unprecedented rate This is so in part because of new experimental methods, and in part because of the increase in the availability of high powered computing technology It is also clear that the nature of the data we are obtaining is significantly different For example, it is now often the case that we are given data in the form of very long vectors, where all but a few of the coordinates turn out to be irrelevant to the questions of interest, and further that we don’t necessarily know which coordinates are the interesting ones A related fact is that the data is often very high-dimensional, which severely restricts our ability to visualize it The data obtained is also often much noisier than in the past and has more missing information (missing data) This is particularly so in the case of biological data, particularly high throughput data from microarray or other sources Our ability to analyze this data, both in terms of quantity and the nature of the data, is clearly not keeping pace with the data being produced In this paper, we will discuss how geometry and topology can be applied to make useful contributions to the analysis of various kinds of data Geometry and topology are very natural tools to apply in this direction, since geometry can be regarded as the study of distance functions, and what one often works with are distance functions on large finite sets of data The mathematical formalism which has been developed for incorporating geometric and topological techniques deals with point clouds, ie finite sets of points equipped with a distance function It then adapts tools from the various branches of geometry to the study of point clouds The point clouds are intended to be thought of as finite samples taken from a geometric object, perhaps with noise Here are some of the key points which come up when applying these geometric methods to data analysis • Qualitative information is needed: One important goal of data analysis is to allow the user to obtain knowledge about the data, ie to understand how it is organized on a large scale For example, if we imagine that we are looking at a data set constructed somehow from diabetes patients, it would be important to develop the understanding that there are two types of the disease, namely the juvenile and adult onset forms Once that is established, one of course wants to develop quantitative methods for distinguishing them, but the first insight about the distinct forms of the disease is key

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Topics: Biological data (58%), Missing data (56%), Topological data analysis (54%) ... read more

1,816 Citations


Journal ArticleDOI: 10.1109/TPWRS.2006.876672
Miguel Carrión, Jose M. Arroyo1Institutions (1)
Abstract: This paper presents a new mixed-integer linear formulation for the unit commitment problem of thermal units. The formulation proposed requires fewer binary variables and constraints than previously reported models, yielding a significant computational saving. Furthermore, the modeling framework provided by the new formulation allows including a precise description of time-dependent startup costs and intertemporal constraints such as ramping limits and minimum up and down times. A commercially available mixed-integer linear programming algorithm has been applied to efficiently solve the unit commitment problem for practical large-scale cases. Simulation results back these conclusions

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1,446 Citations


Performance
Metrics
No. of citations received by the Paper in previous years
YearCitations
20215
20203