Advanced e-Infrastructures for civil protection applications : the CYCLOPS project

During the full cycle of the emergency management, Civil Protection operative procedures involve many actors belonging to several institutions (civil protection agencies, public administrations, research centers, etc.) playing different roles (decision-makers, data and service providers, emergency squads, etc.). In this context the sharing of information is a vital requirement to make correct and effective decisions. Therefore a European-wide technologi- cal infrastructure providing a distributed and coordinated access to different kinds of resources (data, information, services, expertise, etc.) could enhance existing Civil Protection applications and even enable new ones. Such European Civil Protection e-Infrastructure should be designed taking into account the specific requirements of Civil Protection applications and the state-of-the-art in the scientific and technological disciplines which could make the emergency management more effective. In the recent years Grid technologies have reached a mature state providing a platform for secure and coordinated resource sharing between the participants collected in the so-called Virtual Organizations. Moreover the Earth and Space Sciences Informatics provide the conceptual tools for modeling the geospatial information shared in Civil Protection applications during its entire lifecycle. Therefore a European Civil Protection e-infrastructure might be based on a Grid platform enhanced with Earth Sciences services. In the context of the 6th Framework Programme the EU co-funded Project CYCLOPS (CYber-infrastructure for CiviL protection Operative ProcedureS), ended in December 2008, has addressed the problem of defining the re- quirements and identifying the research strategies and innovation guidelines towards an advanced e-Infrastructure for Civil Protection. Starting from the requirement analysis CYCLOPS has proposed an architectural framework for a European Civil Protection e-Infrastructure. This architectural framework has been evaluated through the development of prototypes of two operative applications used by the Italian Civil Protection for Wild Fires Risk Assessment (RISICO) and by the French Civil Protection for Flash Flood Risk Management (SPC-GD). The results of these studies and proof-of-concepts have been used as the basis for the definition of research and innovation strategies aiming to the detailed design and implementation of the infrastructure. In particular the main research themes and topics to be addressed have been identified and detailed. Finally the obstacles to the innovation required for the adoption of this infrastructure and possible strategies to overcome them have been discussed

Performance enhancement of a GIS-based facility location problem using desktop grid infrastructure

This paper presents the integration of desktop grid infrastructure with GIS technologies, by proposing a parallel resolution method in a generic distributed environment. A case study focused on a discrete facility location problem, in the biomass area, exemplifies the high amount of computing resources (CPU, memory, HDD) required to solve the spatial problem. A comprehensive analysis is undertaken in order to analyse the behaviour of the grid-enabled GIS system. This analysis, consisting of a set of the experiments on the case study, concludes that the desktop grid infrastructure is able to use a commercial GIS system to solve the spatial problem achieving high speedup and computational resource utilization. Particularly, the results of the experiments showed an increase in speedup of fourteen times using sixteen computers and a computational efficiency greater than 87 % compared with the sequential procedure.This work has been developed under the support of the program Formacion de Personal Investigador, grants number BFPI/2009/103 and BES-2007-17019, from the Conselleria d'Educacio of the Generalitat Valenciana and the Spanish Ministry of Science and Technology.García García, A.; Perpiñá Castillo, C.; Alfonso Laguna, CD.; Hernández García, V. (2013). Performance enhancement of a GIS-based facility location problem using desktop grid infrastructure. Earth Science Informatics. 6(4):199-207. https://doi.org/10.1007/s12145-013-0119-1S19920764Anderson D (2004) Boinc: a system for public-resource computing and storage. Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, Washington DC, pp 4–10Available scripts webpage: http://personales.upv.es/angarg12/Campos I et al (2012) Modelling of a watershed: a distributed parallel application in a grid framework. Comput Informat 27(2):285–296Church RL (2002) Geographical information systems and location science. Comput Oper Res 29:541–562Clarke KC (1986) Advances in geographic information systems, computers. Environ Urban Syst 10:175–184Dowers S, Gittings BM, Mineter MJ (2000) Towards a framework for high-performance geocomputation: handling vector-topology within a distributed service environment. Comput Environ Urban Syst 24:471–486Geograma SL (2009). Teleatlas. http://www.geograma.com . Accessed September 2009GRASS Development Team (2012) GRASS GIS. http://grass.osgeo.org/Hoekstra AG, Sloot PMA (2005) Introducing grid speedup: a scalability metric for parallel applications on the grid, EGC 2005, LNCS 3470, pp. 245–254Hu Y et al. (2004) Feasibility study of geo-spatial analysis using grid computing. Computational Science-ICCS. Springer Berlin Heidelberg, 956–963Huang Z et al (2009) Geobarn: a practical grid geospatial database system. Adv Electr Comput Eng 9:7–11Huang F et al (2011) Explorations of the implementation of a parallel IDW interpolation algorithm in a Linux cluster-based parallel GIS. Comput Geosci 37:426–434Laure E et al (2006) Programming the grid with gLite. CMST 12(1):33–45Li WJ et al (2005) The Design and Implementation of GIS Grid Services. In: Zhuge H, Fox G (eds) Grid and Cooperative Computing. Vol. 3795 of Lecture Notes in Computer Science 10. Springer, Berlin, pp 220–225National Geographic Institute (2010) BCN25: numerical cartographic database. http://www.ign.es/ign/main/index.do . Accessed April 2010Open Geospatial Consortium, Inc (2012) Open GIS Specification Model, http://www.opengeospatial.org/Openshaw S, Turton I (1996) A parallel Kohonen algorithm for the classification of large spatial datasets. Comput Geosci 22:1019–1026Perpiñá C, Alfonso D, Pérez-Navarro A (2007) BIODER project: biomass distributed energy resources assessment and logistic strategies for sitting biomass plants in the Valencia province (Spain), 17th European Biomass Conference and Exhibition Proceedings, Hamburg, Germany, pp. 387–393Perpiñá C et al (2008) Methodology based on Geographic Information Systems for biomass logistics and transport optimization. Renew Energ 34:555–565Shen Z et al (2007) Distributed computing model for processing remotely sensed images based on grid computing. Inf Sci 177:504–518Spanish Ministry of Agriculture, fisheries and food (2009). http://www.magrama.gob.es/es/ . Accessed March 2009Spanish Ministry of Environment (2008). http://www.magrama.gob.es/es/ . Accessed May 2008University of California. List of BOINC projects. http://boinc.berkeley.edu/projects.phpXiao N, Fu W (2003) SDPG: Spatial data processing grid. J Comput Sci Technol 18:523–53

Towards a service-oriented e-infrastructure for multidisciplinary environmental research

Research e-infrastructures are considered to have generic and thematic parts. The generic part provids high-speed networks, grid (large-scale distributed computing) and database systems (digital repositories and data transfer systems) applicable to all research commnities irrespective of discipline. Thematic parts are specific deployments of e-infrastructures to support diverse virtual research communities. The needs of a virtual community of multidisciplinary envronmental researchers are yet to be investigated. We envisage and argue for an e-infrastructure that will enable environmental researchers to develop environmental models and software entirely out of existing components through loose coupling of diverse digital resources based on the service-oriented achitecture. We discuss four specific aspects for consideration for a future e-infrastructure: 1) provision of digital resources (data, models & tools) as web services, 2) dealing with stateless and non-transactional nature of web services using workflow management systems, 3) enabling web servce discovery, composition and orchestration through semantic registries, and 4) creating synergy with existing grid infrastructures

Self-Organized Dynamics of Power Grids: Smart Grids, Fluctuations and Cascades

Climate change is one of the most pressing issues of our time and mitigating it requires a reduction of CO2 emissions. A big step towards achieving this goal is increasing the share of renewable energy sources, as the energy sector currently contributes 35% to all greenhouse gas emissions. However, integrating these renewable energy sources challenges the current power system in two major ways. Firstly, renewable generation consists of more spatially distributed and smaller power plants than conventional generation by nuclear or coal plants, questioning the established hierarchical structures and demanding a new grid design. Restructuring becomes necessary because wind and solar plants have to be placed at favorable sites, e.g., close to coasts in the case of wind. Secondly, renewables do not provide a deterministic and controllable power output but introduce power fluctuations that have to be controlled adequately. Many solutions to these challenges are build on the concept of smart grids, which require an extensive information technology (IT) infrastructure communicating between consumers and generators to coordinate efficient actions. However, an intertwined power and IT system raises great privacy and security concerns. Is it possible to forgo a large IT infrastructure in future power grids and instead operate them purely based on local information? How would such a decentrally organized system work? What is the impact of fluctuation on short time scales on the dynamical stability? Which grid topologies are robust against random failures or targeted attacks? This thesis aims to establish a framework of such a self-organized dynamics of a power grid, analyzing its benefits and limitations with respect to fluctuations and discrete events. Instead of a centrally monitored and controlled smart grid, we propose the concept of Decentral Smart Grid Control, translating local power grid frequency information into actions to stabilize the grid. This is not limited to power generators but applies equally to consumers, naturally introducing a demand response. We analyze the dynamical stability properties of this framework using linear stability methods as well as applying numerical simulations to determine the size of the basin of attraction. To do so, we investigate general stability effects and sample network motifs to find that this self-organized grid dynamics is stable for large parameter regimes. However, when the actors of the power grid react to a frequency signal, this reaction has to be sufficiently fast since reaction delays are shown to destabilize the grid. We derive expressions for a maximum delay, which always desynchronizes the system based on a rebound effect, and for destabilizing delays based on resonance effects. These resonance instabilities are cured when the frequency signal is averaged over a few seconds (low-pass filter). Overall, we propose an alternative smart grid model without any IT infrastructure and analyze its stable operating space. Furthermore, we analyze the impact of fluctuations on the power grid. First, we determine the escape time of the grid, i.e., the time until the grid desynchronizes when subject to stochastic perturbations. We simulate these events and derive an analytical expression using Kramer's method, obtaining the scaling of the escape time as a function of the grid inertia, transmitted power, damping etc. Thereby, we identify weak links in networks, which have to be enhanced to guarantee a stable operation. Second, we collect power grid frequency measurements from different regions across the world and evaluate their statistical properties. Distributions are found to be heavy-tailed so that large disturbances are more common than predicted by Gaussian statistics. We model the grid dynamics using a stochastic differential equation to derive the scaling of the fluctuations based on power grid parameters, identifying effective damping as essential in reducing fluctuation risks. This damping may be provided by increased demand control as proposed by Decentral Smart Grid Control. Finally, we investigate discrete events, in particular the failure of a single transmission line, as a complementary form of disturbances. An initial failure of a transmission line leads to additional load on other lines, potentially overloading them and thereby causing secondary outages. Hence, a cascade of failures is induced that propagated through the network, resulting in a large-scale blackout. We investigate these cascades in a combined dynamical and event-driven framework, which includes transient dynamics, in contrast to the often used steady state analysis that only solves static flows in the grid while neglecting any dynamics. Concluding, we identify critical lines, prone to cause cascades when failing, and observe a nearly constant speed of the propagation of the cascade in an appropriate metric. Overall, we investigate the self-organized dynamics of power grids, demonstrating its benefits and limitations. We provide tools to improve current grid operation and outline a smart grid solution that is not reliant on IT. Thereby, we support establishing a 100% renewable energy system

Exposure modelling of transmission towers using street-level imagery and a deep learning object detection model

Exposure modelling is a vital component of disaster risk assessments, providing geospatial information of assets at risk and their characteristics. Detailed information about exposure bring benefits to the spatial representation of a rapidly changing environment and allows decision makers to establish better policies aimed at reducing disaster risk. This work proposes and demonstrates a methodology aimed at linking together volunteered geographic information from OpenStreetMap (OSM), street-level imagery from Google Street View (GSV) and deep learning object detection models into the automated creation of exposure datasets of power grid transmission towers, an asset particularly vulnerable to strong wind among other perils. The methodology is implemented through a start-to-end pipeline that starting from the locations of transmission towers derived from the power grid layer of OSMs world infrastructure, can assign relevant features of the tower based on the identification and classification returned from an object detection model over street-level imagery of the tower, obtained from GSV. The initial outcomes yielded promising results towards the establishment of the exposure dataset. For the identification task, the YOLOv5 model returned a mean average precision (mAP) of 83.57% at intersection over union (IoU) of 50%. For the classification problem, although predictive performance varies significantly among tower types, we show that high values of mAP can be achieved when there is a sufficiently high number of good quality images with which to train the model. (c) 2022, National Technical University of Athens. All rights reserved

Towards a foundation for holistic power system validation and testing

Renewable energy sources and further electrificationof energy consumption are key enablers for decreasing green-house gas emissions, but also introduce increased complexitywithin the electric power system. The increased availability ofautomation, information and communication technology, andintelligent solutions for system operation have transformed thepower system into a smart grid. In order to support thedevelopment process of smart grid solutions on the system level,testing has to be done in a holistic manner, covering the multi-domain aspect of such complex systems. This paper introducesthe concept of holistic power system testing and discuss first stepstowards a corresponding methodology that is being developed inthe European ERIGrid research infrastructure project.Comment: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA