Multiple domination models for placement of electric vehicle charging stations in road networks

Electric and hybrid vehicles play an increasing role in the road transport networks. Despite their advantages, they have a relatively limited cruising range in comparison to traditional diesel/petrol vehicles, and require significant battery charging time. We propose to model the facility location problem of the placement of charging stations in road networks as a multiple domination problem on reachability graphs. This model takes into consideration natural assumptions such as a threshold for remaining battery load, and provides some minimal choice for a travel direction to recharge the battery. Experimental evaluation and simulations for the proposed facility location model are presented in the case of real road networks corresponding to the cities of Boston and Dublin.Comment: 20 pages, 5 figures; Original version from March-April 201

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time

17-07 Phase-II: Community-Aware Charging Station Network Design for Electrified Vehicles in Urban Areas: \u3c/i\u3e Reducing Congestion, Emissions, Improving Accessibility, and Promoting Walking, Bicycling, and use of Public Transportation

A major challenge for achieving large-scale adoption of EVs is an accessible infrastructure for the communities. The societal benefits of large-scale adoption of EVs cannot be realized without adequate deployment of publicly accessible charging stations due to mutual dependence of EV sales and public infrastructure deployment. Such infrastructure deployment also presents a number of unique opportunities for promoting livability while helping to reduce the negative side-effects of transportation (e.g., congestion, emissions, and noise pollution). In this phase, we develop a modeling framework (MF) to consider various factors and their associated uncertainties for an optimal network design for electrified vehicles. The factors considered in the study include: state of charge, dwell time, Origin-Destination (OD) pair

A comprehensive study of key Electric Vehicle (EV) components, technologies, challenges, impacts, and future direction of development

Abstract: Electric vehicles (EV), including Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), Fuel Cell Electric Vehicle (FCEV), are becoming more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace internal combustion engine (ICE) vehicles in the near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system could face huge instabilities with enough EV penetration, but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of the smart grid concept. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emissions produced by the transportation sector. However, there are some major obstacles for EVs to overcome before totally replacing ICE vehicles. This paper is focused on reviewing all the useful data available on EV configurations, battery energy sources, electrical machines, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Power network and smart grids analysis from a graph theoretic perspective

The growing size and complexity of power systems has given raise to the use of complex network theory in their modelling, analysis, and synthesis. Though most of the previous studies in this area have focused on distributed control through well established protocols like synchronization and consensus, recently, a few fundamental concepts from graph theory have also been applied, for example in symmetry-based cluster synchronization. Among the existing notions of graph theory, graph symmetry is the focus of this proposal. However, there are other development around some concepts from complex network theory such as graph clustering in the study. In spite of the widespread applications of symmetry concepts in many real world complex networks, one can rarely find an article exploiting the symmetry in power systems. In addition, no study has been conducted in analysing controllability and robustness for a power network employing graph symmetry. It has been verified that graph symmetry promotes robustness but impedes controllability. A largely absent work, even in other fields outside power systems, is the simultaneous investigation of the symmetry effect on controllability and robustness. The thesis can be divided into two section. The first section, including Chapters 2-3, establishes the major theoretical development around the applications of graph symmetry in power networks. A few important topics in power systems and smart grids such as controllability and robustness are addressed using the symmetry concept. These topics are directed toward solving specific problems in complex power networks. The controllability analysis will lead to new algorithms elaborating current controllability benchmarks such as the maximum matching and the minimum dominant set. The resulting algorithms will optimize the number of required driver nodes indicated as FACTS devices in power networks. The second topic, robustness, will be tackled by the symmetry analysis of the network to investigate three aspects of network robustness: robustness of controllability, disturbance decoupling, and fault tolerance against failure in a network element. In the second section, including Chapters 4-8, in addition to theoretical development, a few novel applications are proposed for the theoretical development proposed in both sections one and two. In Chapter 4, an application for the proposed approaches is introduced and developed. The placement of flexible AC transmission systems (FACTS) is investigated where the cybersecurity of the associated data exchange under the wide area power networks is also considered. A new notion of security, i.e. moderated-k-symmetry, is introduced to leverage on the symmetry characteristics of the network to obscure the network data from the adversary perspective. In chapters 5-8, the use of graph theory, and in particular, graph symmetry and centrality, are adapted for the complex network of charging stations. In Chapter 5, the placement and sizing of charging stations (CSs) of the network of electric vehicles are addressed by proposing a novel complex network model of the charging stations. The problems of placement and sizing are then reformulated in a control framework and the impact of symmetry on the number and locations of charging stations is also investigated. These results are developed in Chapters 6-7 to robust placement and sizing of charging stations for the Tesla network of Sydney where the problem of extending the capacity having a set of pre-existing CSs are addressed. The role of centrality in placement of CSs is investigated in Chapter 8. Finally, concluding remarks and future works are presented in Chapter 9

Door to door: Future of the vehicle future of the city

International audienceLes véhicules écologiques et la communication numérique embarquée, à l’ère des flux intelligents et de l’Internet des objets, transforment l’architecture et la ville contemporaines. Door to door, Futur du véhicule, futur urbain, repense les situations urbaines, théorise et imagine les modèles futurs de développement, les nouveaux programmes architecturaux qui en découlent. Il propose et présente les « espaces de l’accès », l’extension-multiplication de l’accessibilité « porte-à-porte » sur six métropoles européennes, et la fonction réparatrice de ces nouveaux outils de « l’auto-mobilité » communicante, résolvant par leur usage les dysfonctionnements urbains.Le parking devient un programme d’avenir pour l’architecture, tandis que le Véhicule Ecologique Communicant (VEC), un outil bientôt automate, ni bruyant, ni sale, côtoie humains, nature et animaux dans les bâtiments – le partage des présences et des activités dans un « grand espace commun ». Le VEC est l’exemple le plus puissant de l’interaction entre la pratique des territoires urbanisés et les TIC. Il est le marqueur le plus incisif du retour du modèle des flux pour penser l’urbain, sous une forme cohérente avec la demande ou les injonctions de la société des échanges et du partage qui s’est mise en marche : la mobilité-accessibilité est redevenue le programme premier, la structure du futur. Que devient l’urbain lorsque l’accès en est le trait le plus dominant ? Les « pôles d’accessibilité et d’échange » sont des dispositifs de transformation de la vie urbaine, qu’ils reconfigurent pour plus de confort et d’efficacité.L’arrivée des nouveaux véhicules accélère ainsi l’interférence entre l’urbanisme des usages et des services et l’urbanisme spatial. A ce niveau, les véhicules sont équivalents à des bâtiments

Planning and Design for Intelligent and Secure Integration of Electric Vehicles into the Smart Grid

The transition to electric vehicles (EVs) is gaining momentum around the world and government initiatives to accelerate this transition range from major tax exemptions, lower insurance payments to convenient parking incentives at shopping malls. The major drivers for this acceleration are the rising awareness by the public for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies. EVs acceptance however is hindered by several challenges; among them is their shorter driving range, slower charging rates, and the ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. Governments of developed countries as well as major car manufacturers are taking solid steps to address these challenges and set ambitious goals to make EVs the major transportation mode within few years. Consequently, a significant number of EVs is going to connect to the existing smart grid and hence, the load pattern is expecting a paradigm shift. This immense load will challenge the generation, transmission and distribution sector of the grid along with being a potential cyber-physical attack platform. To attain a graceful EV penetration for curtailing GHG emission, along with the socioeconomic initiatives, an extensive research is required, especially to mitigate the range anxiety and ameliorate the load congestion on the grid. As a consequence, to reduce the range anxiety, we present a two-stage solution to provision and dimension a DC fast charging station (CS) network for the anticipated energy demand and that minimizes the deployment cost while ensuring a certain quality of experience for charging e.g., acceptable waiting times and shorter travel distances to charge. This solution also maintains the voltage stability by considering the distribution grid capacity, determining transformers’ rating to support peak demand of EV charging and adding a minimum number of voltage regulators based on the impact over the power distribution network. We propose, evaluate and compare two CS network expansion models to determine a cost-effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future EV charging and conventional load demands. Though an adequate fast charging network may assist to reduce the range anxiety and propel the EV market, catering this large number of EVs using fuel based conventional grid actually shifts the carbon footprint from the transportation sector to the power generation sector. As a consequence, green energy needs to be promoted for EV charging. However, the intermittent behavior of renewable energy (RE) generation challenges to maintain a RE based stand alone CS. In order to address this issue, we consider a photovoltaic(PV) powered station equipped with an energy storage system (ESS), which is assumed to be capable of assigning variable charging rates to different EVs to fulfill their demands inside their declared deadlines at minimum price. To ensure fairness, a charging rate dependent pricing mechanism is proposed to assure a higher price for enjoying a higher charging rate. The PV generation profile and future load request are forecasted at each time slot, to handle the respective uncertainties. Whatever, the energy source is green or not of a CS, a static CS cannot offer the flexibility to charge an EV at any place at any time especially for an emergency case. Fortunately, the bidirectional energy transferring capability between vehicles (i.e., vehicle to vehicle (V2V)) might be a solution to charge an EV at any place and at any time without leaning on a stationary CS. Hence, we assume a market where charging providers each has a number of charging trucks equipped with a larger battery and a fast charger to charge a number of EVs at some particular parking lots. We formulate an integer linear program (ILP) to maximize the number of served EVs by determining the optimal trajectory and schedule of each truck. Owing to its complexity, we implement Dantzig-Wolfe decomposition approach to solve this. However, to build a prolific EV charging ecosystem, all its entities (e.g., EVs, CSs and grid) have to be connected through a communication link and that unveils a new cyber physical attack surface. As a consequence, we exploit the abundance of Electric Vehicles (EVs) to target the stability of the power grid by presenting a realistic coordinated switching attack that initiates inter-area oscillations between different areas of the power grid and assess the dire consequences over the power system. Finally, a back propagation neural network (BPNN) technique is used in a proposed framework to detect such switching attacks before being executed

Sustainable Mobility and Transport

This Special Issue is dedicated to sustainable mobility and transport, with a special focus on technological advancements. Global transport systems are significant sources of air, land, and water emissions. A key motivator for this Special Issue was the diversity and complexity of mitigating transport emissions and industry adaptions towards increasingly stricter regulation. Originally, the Special Issue called for papers devoted to all forms of mobility and transports. The papers published in this Special Issue cover a wide range of topics, aiming to increase understanding of the impacts and effects of mobility and transport in working towards sustainability, where most studies place technological innovations at the heart of the matter. The goal of the Special Issue is to present research that focuses, on the one hand, on the challenges and obstacles on a system-level decision making of clean mobility, and on the other, on indirect effects caused by these changes