scholarly journals Quantification of Lifeline System Interdependencies after the 27 February 2010 Mw 8.8 Offshore Maule, Chile, Earthquake

2012 ◽  
Vol 28 (1_suppl1) ◽  
pp. 581-603 ◽  
Author(s):  
Leonardo Dueñas-Osorio ◽  
Alexis Kwasinski
Keyword(s):  
Power Systems ◽  
Prediction Models ◽  
Lifeline System ◽  
Disaster Data ◽  
Chile Earthquake ◽  
Cross Correlations ◽  
Coupling Strengths ◽  
Lag Times ◽  
Lifeline Systems ◽  
Chilean Earthquake

Data on lifeline system service restoration is seldom exploited for the calibration of performance prediction models or for response comparisons across systems and events. This study explores utility restoration curves after the 2010 Chilean earthquake through a time series method to quantify coupling strengths across lifeline systems. When consistent with field information, cross-correlations from restoration curves without significant lag times quantify operational interdependence, whereas those with significant lags reveal logistical interdependence. Synthesized coupling strengths are also proposed to incorporate cross-correlations and lag times at once. In the Chilean earthquake, coupling across fixed and mobile phones was the strongest per region followed by coupling within and across telecommunication and power systems in adjacent regions. Unapparent couplings were also revealed among telecommunication and power systems with water networks. The proposed methodology can steer new protocols for post-disaster data collection, including anecdotal information to evaluate causality, and inform infrastructure interdependence effect prediction models.

Sequential Propagation of Seismic Fragility across Interdependent Lifeline Systems

2011 ◽  
Vol 27 (1) ◽  
pp. 23-43 ◽  
Author(s):  
Isaac Hernandez-Fajardo ◽  
Leonardo Dueñas-Osorio
Keyword(s):  
Network Performance ◽  
Fragility Curves ◽  
Mitigation Strategies ◽  
System Management ◽  
Seismic Action ◽  
Water Network ◽  
Service Networks ◽  
Lifeline System ◽  
Failure Propagation ◽  
Lifeline Systems

Realistic models of service networks must consider the evolution of interactions with external systems to evaluate emergent response effects on individual network performance. This paper introduces a new dynamic methodology for the assessment of systemic fragility propagation across interdependent networks subjected to seismic action that improves existing static methodologies. Interdependencies are discrete, unidirectional relationships between elements of distinct networks, which are able to influence response evolution from transient to steady-state stages. Comparisons of systemic fragility curves results for isolated and interdependent power and water networks display the importance of interdependence strength and density properties. For the test water network, inter-systemic failure propagation increases its connectivity loss by up to 24%, while high interdependence strengths make the median fragility rise up to 56.2%. In contrast, reductions of interdependence density improve the median water fragility up to 81.7%. Insights obtained from this model, and its associated sequential fragility algorithm, reveal complex coupling patterns and interdependence-based mitigation strategies that are essential for lifeline system management.

Optimization-Based Probabilistic Consequence Scenario Construction for Lifeline Systems

2014 ◽  
Vol 30 (4) ◽  
pp. 1531-1551 ◽  
Author(s):  
Jared Gearhart ◽  
Nathanael Brown ◽  
Dean Jones ◽  
Linda Nozick ◽  
Natalia Romero ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Joint Distribution ◽  
Optimization Method ◽  
Seismic Zone ◽  
Realistic Case ◽  
Lifeline System ◽  
Highway Network ◽  
Lifeline Systems

The construction of a suite of consequence scenarios that is consistent with the joint distribution of damage to a lifeline system is critical to properly estimating regional loss after an earthquake. This paper describes an optimization method that identifies a suite of consequence scenarios that can be used in regional loss estimation for lifeline systems when computational demands are of concern, and it is important to capture the spatial correlation associated with individual events. This method is applied to a realistic case study focused on the highway network in Memphis, Tennessee, within the New Madrid Seismic Zone. This case study illustrates that significantly fewer consequence scenarios are needed with this method than would be required using Monte Carlo simulation.

Calibration and Validation of a Seismic Damage Propagation Model for Interdependent Infrastructure Systems

2013 ◽  
Vol 29 (3) ◽  
pp. 1021-1041 ◽  
Author(s):  
Jason Wu ◽  
Leonardo Dueñas-Osorio
Keyword(s):  
Computational Models ◽  
Influential Factors ◽  
Propagation Model ◽  
Power Networks ◽  
Limit States ◽  
Infrastructure Systems ◽  
Calibration And Validation ◽  
Lifeline System ◽  
Theoretical And Computational Models ◽  
Chile Earthquake

Barring a few exceptions, most theoretical and computational models of lifeline system fragility and interdependent response to extreme events still lack calibration and validation relative to real events. This paper expands on this area by evaluating and calibrating a recently proposed Interdependence Fragility Algorithm ( IFA) against field data observed after the 2010 Mw 8.8 offshore Maule, Chile, earthquake. This evaluation incorporates available and simulated properties of the Concepción and Talcahuano water and power networks to try to replicate their topology and seismic response, considering both direct damage and interdependent effects. The calibrated IFA predicts that the probabilities of exceeding the observed high connectivity losses of 0.70 (power) and 0.82 (water), if taken as limit states, are 97% and 72%, respectively. These predictions capture complex interdependent lifeline system responses reasonably well and reveal influential factors for IFA model accuracy and uncertainty reduction, enabling reliable planning, design, expansion, and maintenance of infrastructure systems in practice.

A Novel and Reliable Track Condition Prediction Model for Condition Based Track Maintenance

2013 ◽  
Author(s):  
Peng Xu ◽  
Rengkui Liu ◽  
Quanxin Sun ◽  
Reginald R. Souleyrette ◽  
Jerry G. Rose
Keyword(s):  
Power Systems ◽  
Prediction Model ◽  
High Speed ◽  
Management Practices ◽  
Prediction Models ◽  
Practical Knowledge ◽  
Facility Management ◽  
Railway Transportation ◽  
Track Maintenance ◽  
Track Condition

Recent railway transportation developments throughout the world have demonstrated two main trends, high speed and heavy haul. Both of these have resulted in increased wheel loads due to increased dynamic forces and/or higher weights. It is well known that increased wheel loads result in faster deterioration of the track structure. Consequently, maintenance-of-way departments inspect more frequently to ensure safety and comfort for passengers and reduce the risk of damage to freight. An alternative to more frequent inspections is a track maintenance strategy known as condition based maintenance (CBM). CBM has received considerable attention in other industries such as truck fleet management and power systems facility management. Practices in these fields show that CBM can not only reduce interruption of service but also enhance system reliability. What is more, CBM can also reduce life-cycle costs. Within railroading, CBM is used to schedule preventive rail grinding, but, CBM has not yet found widespread implementation in the maintenance of other track components. The key to effective implementation of CBM is reliable forecasts of future conditions based on prediction models. In this paper, a novel track condition prediction model is presented which may serve as a basis for condition based track maintenance. The model is built on practical knowledge of track condition deterioration. Typically, the model can predict track condition (including isolated geometry exceptions and condition of unit track sections) two to three months in advance, depending on tonnage/frequency of trains. To validate the model, track inspection data were collected from the Jinan bureau of China Railroads. Some analysis of the results of track condition predictions is also presented.

An Evaluation of Ductility and Detailing Requirements of Bearing Wall Buildings Using Data from the March 3, 1985, Chile Earthquake

1993 ◽  
Vol 9 (1) ◽  
pp. 137-156 ◽  
Author(s):  
John W. Wallace ◽  
Jack P. Moehle
Keyword(s):  
United States ◽  
Ground Motions ◽  
The United States ◽  
Earthquake Response ◽  
Analytical Studies ◽  
Concrete Confinement ◽  
Chile Earthquake ◽  
Wall Construction ◽  
Using Data ◽  
Chilean Earthquake

The expected earthquake response of bearing wall buildings is investigated using data from the March 3, 1985 Chile earthquake. The study includes an examination of proportioning and detailing requirements for Chilean and U.S. bearing wall construction. Based on the requirements, minimum stiffnesses and strengths are characterized. Recorded ground motions in Vin~a del Mar, Chile and the western U.S. are analyzed and compared. Drifts and global displacement ductilities are estimated. Based on the findings related to drift and ductility, the need for concrete confinement at wall boundaries is investigated analytically. The analytical studies indicate that boundary confinement is not always necessary at wall boundaries. The performance of bearing wall buildings in the Chilean earthquake and the analytical studies conducted herein indicate that the form of construction used in Chile is a viable construction option in the United States.

scholarly journals Characterizing Uncertainty in City-Wide Disaster Recovery through Geospatial Multi-Lifeline Restoration Modeling of Earthquake Impact in the District of North Vancouver

2020 ◽  
Vol 11 (6) ◽  
pp. 807-820
Author(s):  
Andrew Deelstra ◽  
David Bristow
Keyword(s):  
Power Distribution ◽  
Water Distribution ◽  
Discrete Event ◽  
Graph Model ◽  
Transport Systems ◽  
Complex Interactions ◽  
Lifeline System ◽  
Model And Simulation ◽  
System Functioning ◽  
Lifeline Systems

AbstractRestoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole. Since cities are comprised of many dependent lifeline systems, the pattern of the restoration of each lifeline system can have an impact on one or more others. Due to the often uncertain and complex interactions between dense lifeline systems and their individual operations at the urban scale, it is typically unclear how different patterns of restoration will impact the overall recovery of lifeline system functioning. A difficulty in addressing this problem is the siloed nature of the knowledge and operations of different types of lifelines. Here, a city-wide, multi-lifeline restoration model and simulation are provided to address this issue. The approach uses the Graph Model for Operational Resilience, a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time. A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake. The model comprises municipal water and wastewater, power distribution, and transport systems. The model includes 1725 entities from within these sectors, connected through 6456 dependency relationships. Simulation of the model shows that water distribution and wastewater treatment systems recover more quickly and with less uncertainty than electric power and road networks. Understanding this uncertainty will provide the opportunity to improve data collection, modeling, and collaboration with stakeholders in the future.

scholarly journals Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects

2021 ◽  
Vol 11 (8) ◽  
pp. 3679
Author(s):  
Martina Kajanova ◽  
Peter Bracinik
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Prediction Models ◽  
Stated Preference ◽  
Distribution Networks ◽  
Discrete Choice Models ◽  
Stable Operation ◽  
Vehicle To Grid ◽  
Charging Station ◽  
Definition Of

With an increasing number of electric vehicles (EVs), their owners’ involvement in the control of electric power systems and their market seems to be the only option for stable operation of future power networks. However, these people usually have little knowledge about power systems’ operation and follow just their interests. Therefore, this paper deals with the decision-making process of EV drivers at the charging station. The paper presents the stated preference survey used to collect the responses to hypothetical scenarios, where respondents chose between three alternatives, namely slow charging, fast charging, and vehicle-to-grid services. The survey also contained questions about respondents’ socio-demographic characteristics, as gender, age, etc. The decision-making prediction models for each socio-demographic characteristic were created using the acquired data. The paper presents the estimated parameters of the attributes affecting the respondents’ choices for the models that allow models’ simple implementation. Knowing these models and the customers’ composition, the operators of the charging stations or the distribution networks could better estimate EV owners’ behavior and so their expected power demand. Moreover, operators could more effectively implement incentives for their customers and affect the customers’ behavior in a way that is suitable for better operation of their power systems.

scholarly journals Outlier Events of Solar Forecasts for Regional Power Grid in Japan Using JMA Mesoscale Model

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2714 ◽  
Author(s):  
Hideaki Ohtake ◽  
Fumichika Uno ◽  
Takashi Oozeki ◽  
Yoshinori Yamada ◽  
Hideaki Takenaka ◽  
...  
Keyword(s):  
Pacific Ocean ◽  
Power Systems ◽  
Electric Power ◽  
Prediction Models ◽  
Weather Prediction ◽  
Japan Meteorological Agency ◽  
Forecast Errors ◽  
Safety Control ◽  
The Pacific ◽  
The Pacific Ocean

To realize the safety control of electric power systems under high penetration of photovoltaic power systems, accurate global horizontal irradiance (GHI) forecasts using numerical weather prediction models (NWP) are becoming increasingly important. The objective of this study is to understand meteorological characteristics pertaining to large errors (i.e., outlier events) of GHI day-ahead forecasts obtained from the Japan Meteorological Agency, for nine electric power areas during four years from 2014 to 2017. Under outlier events in GHI day-ahead forecasts, several sea-level pressure (SLP) patterns were found in 80 events during the four years; (a) a western edge of anticyclone over the Pacific Ocean (frequency per 80 outlier events; 48.8%), (b) stationary fronts (20.0%), (c) a synoptic-scale cyclone (18.8%), and (d) typhoons (tropical cyclones) (8.8%) around the Japanese islands. In this study, the four case studies of the worst outlier events were performed. A remarkable SLP pattern was the case of the western edge of anticyclone over the Pacific Ocean around Japan. The comparison between regionally integrated GHI day-ahead forecast errors and cloudiness forecasts suggests that the issue of accuracy of cloud forecasts in high- and mid-levels troposphere in NWPs will remain in the future.

ANN-Based Short-Term Load Forecasting

2018 ◽  
pp. 92-111
Keyword(s):  
Power Systems ◽  
Transmission Lines ◽  
Prediction Models ◽  
Electrical Power ◽  
Load Forecasting ◽  
Back Propagation ◽  
Electrical Energy ◽  
Load Prediction ◽  
Electrical Power Systems ◽  
Short Term Load Forecasting

Load forecasting is a very crucial issue for the operational planning of electrical power systems. In the sixth chapter, it is formulated that a reliable power network along with load prediction models is essential for uninterrupted supply of electrical energy to the consumers. The Back-Propagation ANN algorithm is applied to forecast the load of the power system. Based on the load forecasted power components, transmission lines and sub-stations are augmented for improved reliability in a province.

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