96 research outputs found

    Advances on Smart Cities and Smart Buildings

    Get PDF
    Modern cities are facing the challenge of combining competitiveness at the global city scale and sustainable urban development to become smart cities. A smart city is a high-tech, intensive and advanced city that connects people, information, and city elements using new technologies in order to create a sustainable, greener city; competitive and innovative commerce; and an increased quality of life. This Special Issue collects the recent advancements in smart cities and covers different topics and aspects

    Spatial-temporal domain charging optimization and charging scenario iteration for EV

    Get PDF
    Environmental problems have become increasingly serious around the world. With lower carbon emissions, Electric Vehicles (EVs) have been utilized on a large scale over the past few years. However, EVs are limited by battery capacity and require frequent charging. Currently, EVs suffer from long charging time and charging congestion. Therefore, EV charging optimization is vital to ensure drivers’ mobility. This study first presents a literature analysis of the current charging modes taxonomy to elucidate the advantages and disadvantages of different charging modes. In specific optimization, under plug-in charging mode, an Urgency First Charging (UFC) scheduling policy is proposed with collaborative optimization of the spatialtemporal domain. The UFC policy allows those EVs with charging urgency to get preempted charging services. As conventional plug-in charging mode is limited by the deployment of Charging Stations (CSs), this study further introduces and optimizes Vehicle-to-Vehicle (V2V) charging. This is aim to maximize the utilization of charging infrastructures and to balance the grid load. This proposed reservation-based V2V charging scheme optimizes pair matching of EVs based on minimized distance. Meanwhile, this V2V scheme allows more EVs get fully charged via minimized waiting time based parking lot allocation. Constrained by shortcomings (rigid location of CSs and slow charging power under V2V converters), a single charging mode can hardly meet a large number of parallel charging requests. Thus, this study further proposes a hybrid charging mode. This mode is to utilize the advantages of plug-in and V2V modes to alleviate the pressure on the grid. Finally, this study addresses the potential problems of EV charging with a view to further optimizing EV charging in subsequent studies

    Efficient operation of recharging infrastructure for the accommodation of electric vehicles: a demand driven approach

    Get PDF
    Large deployment and adoption of electric vehicles in the forthcoming years can have significant environmental impact, like mitigation of climate change and reduction of traffic-induced air pollutants. At the same time, it can strain power network operations, demanding effective load management strategies to deal with induced charging demand. One of the biggest challenges is the complexity that electric vehicle (EV) recharging adds to the power system and the inability of the existing grid to cope with the extra burden. Charging coordination should provide individual EV drivers with their requested energy amount and at the same time, it should optimise the allocation of charging events in order to avoid disruptions at the electricity distribution level. This problem could be solved with the introduction of an intermediate agent, known as the aggregator or the charging service provider (CSP). Considering out-of-home charging infrastructure, an additional role for the CSP would be to maximise revenue for parking operators. This thesis contributes to the wider literature of electro-mobility and its effects on power networks with the introduction of a choice-based revenue management method. This approach explicitly treats charging demand since it allows the integration of a decentralised control method with a discrete choice model that captures the preferences of EV drivers. The sensitivities to the joint charging/parking attributes that characterise the demand side have been estimated with EV-PLACE, an online administered stated preference survey. The choice-modelling framework assesses simultaneously out-of-home charging behaviour with scheduling and parking decisions. Also, survey participants are presented with objective probabilities for fluctuations in future prices so that their response to dynamic pricing is investigated. Empirical estimates provide insights into the value that individuals place to the various attributes of the services that are offered by the CSP. The optimisation of operations for recharging infrastructure is evaluated with SOCSim, a micro-simulation framework that is based on activity patterns of London residents. Sensitivity analyses are performed to examine the structural properties of the model and its benefits compared to an uncontrolled scenario are highlighted. The application proposed in this research is practice-ready and recommendations are given to CSPs for its full-scale implementation.Open Acces

    Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

    Get PDF
    Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

    Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

    Get PDF
    Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

    Contributions to sustainable urban transport : decision support for alternative mobility and logistics concepts

    Get PDF
    Increasing transport activities in cities are a substantial driver for congestion and pollution, influencing urban populations’ health and quality of life. These effects are consequences of ongoing urbanization in combination with rising individual demand for mobility, goods, and services. With the goal of increased environmental sustainability in urban areas, city authorities and politics aim for reduced traffic and minimized transport emissions. To support more efficient and sustainable urban transport, this cumulative dissertation focuses on alternative transport concepts. For this purpose, scientific methods and models of the interdisciplinary information systems domain combined with elements of operations research, transportation, and logistics are developed and investigated in multiple research contributions. Different transport concepts are examined in terms of optimization and acceptance to provide decision support for relevant stakeholders. In more detail, the overarching topic of urban transport in this dissertation is divided into the complexes urban mobility (part A) in terms of passenger transport and urban logistics (part B) with a focus on the delivery of goods and services. Within part A, approaches to carsharing optimization are presented at various planning levels. Furthermore, the user acceptance of ridepooling is investigated. Part B outlines several optimization models for alternative urban parcel and e-grocery delivery concepts by proposing different network structures and transport vehicles. Conducted surveys on intentional use of urban logistics concepts give valuable hints to providers and decision makers. The introduced approaches with their corresponding results provide target-oriented support to facilitate decision making based on quantitative data. Due to the continuous growth of urban transport, the relevance of decision support in this regard, but also the understanding of the key drivers for people to use certain services will further increase in the future. By providing decision support for urban mobility as well as urban logistics concepts, this dissertation contributes to enhanced economic, social, and environmental sustainability in urban areas

    Critical evaluation of the battery electric vehicle for sustainable mobility

    Get PDF
    Can Battery Electric Vehicles replace conventional internal combustion engine vehicles for commuting purposes when exposed to a busy corporate activity within the city of Edinburgh?This thesis investigates the application of Battery Electric Vehicles (BEV) use in a commercial business environment in the city of Edinburgh, Scotland UK. The motivation behind this work is to determine if the Battery Electric Vehicle can replace conventional fossil fuel vehicles under real world drive cycles and the desire by many to combat the causes of climate change.Due to the nature of this work a significant part of the work will be underpinned by the quantitative methodology approach to the research. As the question indicates the research is supported by real live data coming from the vehicle both in proprietary data logging as well as reading and analysing the data coming from the vehicles own Electronic Control Unit (ECU).There will be mixed research methodology encompassing quantitative and qualitative research to obtain a complete response in respect to the management of the vehicle these methodologies will be the analysis of the measurable data as well as explorative, to gain the underlying reasons and motivations for choosing a battery electric vehicle as an option to the conventional vehicle for this type of application use

    New solution approaches for optimization problems with combinatorial aspects in logistics management

    Get PDF
    This dissertation comprises five papers, which have been published in scientific journals between 2019 and 2022. The papers consider logistic optimization problems from three different subjects with a focus on intra-logistics. All considered optimization problems have strong combinatorial aspects. To solve the considered problems, various solution approaches including different decomposition techniques are employed. Paper 1 investigates the optimization of the layout and storage assignment in warehouses with U-shaped order picking zones. The paper considers two objectives, namely minimizing the order picker's walking distance and physical strain during order picking. To solve the problem, a semantic decomposition approach is proposed, which solves the problem in polynomial time. In a computational study, both considered objectives are found to be mostly complementary. Moreover, suggestions for advantageous layout designs and storage assignments are derived. Paper 2 considers the problem of how to stow bins on tow trains in order to minimize the handling personnel's physical strain for loading and unloading. The problem is shown to be NP-hard and decomposed semantically. Utilising the decomposition, the problem is solved exactly with dynamic programming and heuristically with a greedy randomized adaptive search procedure. A consecutive computational study shows that both procedures perform well. Beyond that, it investigates the influence of the tow train wagons' design on the considered objective. Paper 3 is concerned with the problem of scheduling jobs with time windows on unrelated parallel machines, which is a NP-hard optimization problem that has applications, i.a., in berth allocation and truck dock scheduling. The paper presents an exact logic-based Benders decomposition procedure and a heuristic solution approach based on a set partitioning formulation of the problem. Moreover, three distinct objectives, namely minimizing the makespan, the maximum flow time, and the maximum lateness are considered. Both procedures exhibit good performances in the concluding computational study. Paper 4 addresses the problem of order picker routing in a U-shaped order picking zone with the objective of minimizing the covered walking distance. The problem is proven to be NP-hard. An exact logic-based Benders decomposition procedure as well as a heuristic dynamic programming approach are developed and shown to perform well in computational tests. Beyond that, the paper discusses different storage assignment policies and compares them in a numeric study. Paper 5 studies scheduling electrically powered tow trains in in-plant production logistics. The problem is regarded as an Electric Vehicle Scheduling Problem, where tow trains must be assigned to timetabled service trips. Since the tow trains' range is limited, charging breaks need to be scheduled in-between trips, which require detours and time. The objective consists in minimizing the required fleet size. The problem is shown to be NP-hard. To solve the problem, Paper 5 proposes a branch-and-check approach that is applicable for various charging technologies, including battery swapping and plug-in charging with nonlinear charge increase. In a computational study, the approach's practical applicability is demonstrated. Moreover, influences of the batteries' maximum capacity and employed charging technology are investigated

    Green Logistics : Advanced Methods for Transport Logistics Management Systems Including Platooning and Alternative Fuel Powered Vehicles

    Get PDF
    Green Logistics has attracted increased attention from researchers during the last few years, due to the growing environmental awareness. Road Transport is a major factor in climate change and accounts for a large proportion of the total UK emissions, including Carbon Dioxide (COâ‚‚). With traffic and congestion levels growing, efficient routing combined with greener (more environmentally friendly) vehicles will be of great importance. The purpose of this thesis is two-fold: i) to provide an insight into Green Logistics and ways in which green technologies can be combined within the vehicle routing problem and ii) identifying new variants of the Vehicle Routing Problem (VRP) that can be applied to real-life instances; The Platooning Routing Problem with Changing Split Points, and the proposition of a Hyper-Realistic Electric Vehicle Energy Consumption model that can be applied to the E-VRP. A thorough COâ‚‚ experiment was also conducted on a rolling road, providing useful data that future research can use to further increase the accuracy of routing models. The platooning of vehicles proves to be an important technique that can lead to large decreases in fuel consumption and can be easily implemented in most transport systems; the process requires advanced and accurate computer systems that are only now becoming available to manufacturers. The Platooning model is designed and tested within this thesis and it is hoped to spark further interest in this crucial area of research. Extensions to the Platooning Problem include the addition of heterogeneous fleets and how they change the dynamics of the proposed problems, as well as further work on the placement of the critical splitting point. Allowing the consideration of using limited range Electric Vehicles (EVs) as well as Conventional Vehicles (CVs) and Alternative Fuel powered Vehicles (AFVs) can further increase the emission savings and are becoming progressively popular in today's society. We therefore have carried out extensive research around the area of AFV's including detailed battery specifics for EV's. The objective is to minimise the amount of emissions while satisfying the time window requirements of customers maintaining low overall financial costs. The resulting emissions are largely affected by the electricity fuel mix of the country, we found that the indirect EV emissions for a 30kwh EV can vary by as much as 33% throughout the day and as much as 68% throughout the year with different seasons. Various heuristic and metaheuristic solution techniques as well as several classical heuristics are implemented including the Clarke and Wright Savings heuristic algorithm (CWSA), the Sweep Algorithm and the Variable Neighbourhood Search (VNS) method. These heuristic and metaheuristic models are tested on the Christofides et al. datasets and we achieve solutions that are on average 1.67% and 8.5% deviated from the best-known solution for unrestricted route lengths and restricted max route length problems respectively. Following this a platooning model is generated and tested on various datasets, including a real-life example along the roads of the South East of the UK. Platooning proves to bring benefits to the VRP, with the extensions discussed in this thesis providing increased savings to emissions. On three of the dataset problems of the small and medium size problems a significant fuel saving of more than 1% was achieved. With future research and additional avenues explored Platooning can make a significant reduction to emissions and make an impact on improving air quality. The EV model proposed is designed to trigger further research on ultra-realistic energy models with the aim of being applied to a real-life organisation with various constraints including factors such as battery health, travel speed, vehicle load and transportation distance. This thesis provides useful insights into how important the aspect of environmental route planning is, providing advice on tangible and intangible benefits such as cost savings and a reduction in carbon emissions
    • …
    corecore