MobilElektrotechnik und MedientechnikTC FreyungZeitschriftenartikel
Raphaela Pagany, Anna Marquardt, Roland Zink
Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations
Sustainability, vol. 11, no. 8
2019
DOI: 10.3390/su11082301
Abstract anzeigen
In recent years, with the increased focus on climate protection, electric vehicles (EVs) have become a relevant alternative to conventional motorized vehicles. Even though the market share of EVs is still comparatively low, there are ongoing considerations for integrating EVs in transportation systems. Along with pushing EV sales numbers, the installation of charging infrastructure is necessary. This paper presents a user- and destination-based approach for locating charging stations (CSs) for EVs—the electric charging demand location (ECDL) model. With regard to the daily activities of potential EV users, potential positions for CSs are derived on a micro-location level in public and semipublic spaces using geographic information systems (GIS). Depending on the vehicle users’ dwell times and visiting frequencies at potential points of interest (POIs), the charging demand at such locations is calculated. The model is mainly based on a survey analyzing the average time spent per daily activity, regional data about driver and vehicle ownership numbers, and the georeferenced localization of regularly visited POIs. Optimal sites for parking and charging EVs within the POIs neighborhood are selected based on walking distance calculations, including spatial neighborhood effects, such as the density of POIs. In a case study in southeastern Germany, the model identifies concrete places with the highest overall demand for CSs, resulting in an extensive coverage of the electric energy demand while considering as many destinations within the acceptable walking distance threshold as possible.
MobilElektrotechnik und MedientechnikTC FreyungZeitschriftenartikel
Raphaela Pagany, Wolfgang Dorner
Do Crash Barriers and Fences Have an Impact on Wildlife-Vehicle Collisions? An Artificial Intelligence and GIS-Based Analysis
ISPRS Internation Journal of Geo-Information, vol. 8, no. 2
2019
DOI: 10.3390/ijgi8020066
Abstract anzeigen
Wildlife–vehicle collisions (WVCs) cause significant road mortality of wildlife and have led to the installation of protective measures along streets. Until now, it has been difficult to determine the impact of roadside infrastructure that might act as a barrier for animals. The main deficits are the lack of geodata for roadside infrastructure and georeferenced accidents recorded for a larger area. We analyzed 113 km of road network of the district Freyung-Grafenau, Germany, and 1571 WVCs, examining correlations between the appearance of WVCs, the presence or absence of roadside infrastructure, particularly crash barriers and fences, and the relevance of the blocking effect for individual species. To receive infrastructure data on a larger scale, we analyzed 5596 road inspection images with a neural network for barrier recognition and a GIS for a complete spatial inventory. This data was combined with the data of WVCs in GIS to evaluate the infrastructure’s impact on accidents. The results show that crash barriers have an effect on WVCs, as collisions are lower on roads with crash barriers. In particular, smaller animals have a lower collision share. The risk reduction at fenced sections could not be proven as fenced sections are only available at 3% of the analyzed roads. Thus, especially the fence dataset must be validated by a larger sample number. However, these preliminary results indicate that the combination of artificial intelligence and GIS may be used to analyze and better allocate protective barriers or to apply it in alternative measures, such as dynamic WVC risk-warning.
MobilElektrotechnik und MedientechnikTC FreyungZeitschriftenartikel
Luis Ramirez Camargo, Raphaela Pagany, Wolfgang Dorner
A review of spatial localization methodologies for the electric vehicle charging infrastructure
International Journal of Sustainable Transportation, pp. 1-17
2018
DOI: 10.1080/15568318.2018.1481243
Abstract anzeigen
With view to the high share of the transport sector in total energy consumption, e-mobility should play an important role within the transition of the energy systems. Policymakers in several countries consider electric vehicles (EV) as an alternative to fossil-fueled vehicles. In order to allow for the development of EV, the charging infrastructure has to be set up at locations with high charging potential, identified by means of various criteria such as demand density or trip length. Many methodologies for locating charging stations (CS) have been developed in the last few years. First, this paper presents a broad overview of publications in the domain of CS localization. A classification scheme is proposed regarding modeling theory and empirical application; further on, models are analyzed, distinguishing between users, route or destination centricity of the approaches and outcomes. In a second step, studies in the field of explicit spatial location planning are reviewed in more detail, that is, in terms of their target criteria and the specialization of underlying analytical processes. One divergence of these approaches lies in the varying level of spatial planning, which could be crucial depending on the planning requirements. It is striking that almost all CS locating concepts are proposed for urban areas. Other constraints, such as the lack of extensive empirical EV traffic data for a better understanding of the driving behavior, are identified. This paper provides an overview of the CS models, a classification approach especially considering the problem’s spatial dimension, and derives perspectives for further research.
DigitalTC FreyungZeitschriftenartikel
F. Oloo, Raphaela Pagany, G. Kothencz
Multi-dimensionality of Uncertainty in Big Geospatial Sensor Data
GI Forum - Journal of Geographic Information Science, no. Issue 1, pp. 3-15
2018
DOI: 10.1553/giscience2018_01_s3
Abstract anzeigen
Developments in sensor technology have contributed immensely to the growth of big geospatial sensor data. Moreover, advances in telecommunications have made it possible to use in-situ sensors to capture and transfer data about the environment in near real-time. The combination of various sensor types within a predefined geographic space and the possibility of making measurements at high temporal resolution contributes to a better understanding of our environment while also generating big geospatial sensor data. Big data from multi-sensor networks, particularly those that capture dynamic characteristics of the environment, have not been spared the challenges that face other types of big data. Specifically, the quality of data and the propagation of uncertainty through the multi-sensor data processing workflows have remained a major concern in the big geospatial sensor data research community. Attempts to document, quantify and communicate the uncertainty associated with sensor data and related sensor network outputs have been made mainly in the context of individual projects. This paper aims to document the state-of-art in defining uncertainty with regard to multi-sensor geospatial data. In particular, we analyse the current literature to outline different types of uncertainty, and document methods for handling uncertainty in the different stages of multi-sensor geospatial data collection, processing and delivery.
MobilTC FreyungBeitrag (Sammelband oder Tagungsband)
Raphaela Pagany, Anna Marquardt, Roland Zink
OSM-basierte Standortmodellierung von Ladesäulen für Elektromobilität am Beispiel des Bayerischen Waldes
Tagungsband der FOSSGISS 2017: Anwenderkonferenz für Freie und Open Source Software für Geoinformationssysteme (Universität Passau; 22.-25.03.2017)
2017
DigitalTC FreyungBeitrag (Sammelband oder Tagungsband)
Raphaela Pagany, Wolfgang Dorner
Spatiotemporal Analysis for Wildlife-Vehicle Collision Based on Accident Statistics of the County Straubing-Bogen in Lower Bavaria
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic), vol. Volume XLI-B8
2016
NachhaltigTC FreyungZeitschriftenartikel
Luis Ramirez Camargo, Raphaela Pagany, Wolfgang Dorner, K. Escalante, S. Belmonte, N. Sarmiento Babieri, J. Franco
Technical, Economical and Social Assessment of Photovoltaics in the Frame of the Net-Metering Law for the Province of Salta, Argentina
Energies, vol. 9, no. 3 (Article number 133)
2016
DOI: 10.3390/en9030133
Abstract anzeigen
Central and Northern Argentinean regions possess a high potential for the generation of solar energy. The realization of this potential is an alternative to alleviate the strong dependence on imports of fossil energy and to reduce the CO2 emissions of the country. However, the adoption of photovoltaics (PV) is still in an incipient state. It is undermined by a context of heavily subsidized electricity prices, high equipment and installation costs and a lack of information, training and experience in handling PV technology. This paper presents a techno-economical assessment of the application of the recently enacted net-metering law for promoting renewable energies (RE) in the Province of Salta (Northwest Argentina) for the case of PV. The assessment shows under which conditions and for which types of consumers it is profitable to adopt PV in the context of the law. This analysis is supported by a participatory planning approach as a study of stakeholders’ attitudes towards RE, intentions to adopt PV and their knowledge about the law. The results of this study and the economical analysis serve to provide recommendations aimed at increasing the level of PV adoption in the province.
Elektrotechnik und MedientechnikZeitschriftenartikel
Raphaela Pagany, F. Diepold, Roland Zink
Bürger diskutieren Standorte – 3D-Visualisierung am Beispiel Windenergie
gis.BUSINESS - Das Magazin für Geoinformation, no. 3, pp. 32-35
2012
Abstract anzeigen
Mit der zunehmenden Bedeutung von Windenergie für die zukünftige Energieversorgung stellt sich in vielen Regionen die Frage, wo sich die optimalen Standorte dafür befinden. Neben der ökonomischen Rentabilität und der ökologischen Verträglichkeit sollten die Windkraftstandorte auch sozialen Belangen genügen. Ein wesentlicher Aspekt der gesellschaftlichen Akzeptanz ist dabei die visuelle Beeinträchtigung des Landschaftsbildes durch eine bzw. mehrere Windkraftanlage(n). Hierzu bediente man sich bisher häufig Fotomontagen um mögliche Auswirkungen aufzuzeigen. Obwohl Geographische Informationssysteme (GIS) bei der Suche nach geeigneten Standorten in Wissenschaft und Praxis bereits vielfach und erfolgreich eingesetzt werden, wird ihr Potenzial bei der 3D-Visualisierung und der Möglichkeit, Bürger mittels GIS aktiv in den Planungsprozess zu integrieren, weitestgehend vernachlässigt. Der Beitrag zeigt anhand einer Standortsuche für Windkraft Wege auf, mittels denen sich GIS und 3D-Visualisierung gewinnbringend in Bürgerbeteiligungsprozesse integrieren lassen.
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