A Network Design Framework for Siting Electric Vehicle Charging Stations in an Urban Network with Demand Uncertainty PDF Download

Author: Jingzi Tan
Publisher:
ISBN:
Category :
Languages : en
Pages : 292

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Book Description
We consider a facility location problem with uncertainty flow customers' demands, which we refer to as stochastic flow capturing location allocation problem (SFCLAP). Potential applications include siting farmers' market, emergency shelters, convenience stores, advertising boards and so on. For this dissertation, electric vehicle charging stations siting with maximum accessibility at lowest cost would be studied. We start with placing charging stations under the assumptions of pre-determined demands and uniform candidate facilities. After this model fails to deal with different scenarios of customers' demands, a two stage flow capturing location allocation programming framework is constructed to incorporate demand uncertainty as SFCLAP. Several extensions are built for various situations, such as secondary coverage and viewing facility's capacity as variables. And then, more capacitated stochastic programming models are considered as systems optimal and user oriented optimal cases. Systems optimal models are introduced with variations which include outsourcing the overflow and alliance within the system. User oriented optimal models incorporate users' choices with system's objectives. After the introduction of various models, an approximation method for the boundary of the problem and also the exact solution method, the L-Shaped method, are presented. As the computation time in the user oriented case surges with the expansion of the network, scenario reduction method is introduced to get similar optimal results within a reasonable time. And then, several cases including testing with different number of scenarios and different sample generating methods are operated for model validation. In the last part, simulation method is operated on the authentic network of the state of Arizona to evaluate the performance of this proposed framework.

Author: Md Abdul Quddus
Publisher:
ISBN:
Category :
Languages : en
Pages : 217

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Book Description
This dissertation studies a framework in support electric vehicle (EV) charging station expansion and management decisions. In the first part of the dissertation, we present mathematical model for designing and managing electric vehicle charging stations, considering both long-term planning decisions and short-term hourly operational decisions (e.g., number of batteries charged, discharged through Battery-to-Grid (B2G), stored, Vehicle-to-Grid (V2G), renewable, grid power usage) over a pre-specified planning horizon and under stochastic power demand. The model captures the non-linear load congestion effect that increases exponentially as the electricity consumed by plugged-in EVs approaches the capacity of the charging station and linearizes it. The study proposes a hybrid decomposition algorithm that utilizes a Sample Average Approximation and an enhanced Progressive Hedging algorithm (PHA) inside a Constraint Generation algorithmic framework to efficiently solve the proposed optimization model. A case study based on a road network of Washington, D.C. is presented to visualize and validate the modeling results. Computational experiments demonstrate the effectiveness of the proposed algorithm in solving the problem in a practical amount of time. Finding of the study include that incorporating the load congestion factor encourages the opening of large-sized charging stations, increases the number of stored batteries, and that higher congestion costs call for a decrease in the opening of new charging stations. The second part of the dissertation is dedicated to investigate the performance of a collaborative decision model to optimize electricity flow among commercial buildings, electric vehicle charging stations, and power grid under power demand uncertainty. A two-stage stochastic programming model is proposed to incorporate energy sharing and collaborative decisions among network entities with the aim of overall energy network cost minimization. We use San Francisco, California as a testing ground to visualize and validate the modeling results. Computational experiments draw managerial insights into how different key input parameters (e.g., grid power unavailability, power collaboration restriction) affect the overall energy network design and cost. Finally, a novel disruption prevention model is proposed for designing and managing EV charging stations with respect to both long-term planning and short-term operational decisions, over a pre-determined planning horizon and under a stochastic power demand. Long-term planning decisions determine the type, location, and time of established charging stations, while short-term operational decisions manage power resource utilization. A non-linear term is introduced into the model to prevent the evolution of excessive temperature on a power line under stochastic exogenous factors such as outside temperature and air velocity. Since the research problem is NP-hard, a Sample Average Approximation method enhanced with a Scenario Decomposition algorithm on the basis of Lagrangian Decomposition scheme is proposed to obtain a good-quality solution within a reasonable computational time. As a testing ground, the road network of Washington, D.C. is considered to visualize and validate the modeling results. The results of the analysis provide a number of managerial insights to help decision makers achieving a more reliable and cost-effective electricity supply network.

Author: Sivaraman Palanisamy
Publisher: John Wiley & Sons
ISBN: 1119987768
Category : Technology & Engineering
Languages : en
Pages : 244

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Book Description
Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles Comprehensive resource describing fast-charging infrastructure in electric vehicles, including various subsystems involved in the power system architecture needed for fast-charging Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles presents various aspects of fast-charging infrastructure, including the location of fast-charging stations, revenue models and tariff structures, power electronic converters, power quality problems such as harmonics & supraharmonics, energy storage systems, and wireless-charging, electrical distribution infrastructures and planning. This book serves as a guide to learn recent advanced technologies with examples and case studies. It also considers problems that arise, and the mitigation methods involved, in fast-charging stations in global aspects and provides tools for analysis. Sample topics covered in Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles include: Selection of fast-charging stations, advanced power electronic converter topologies for EV fast-charging, wireless charging for plug-in HEV/EVs, and batteries for fast-charging infrastructure Standards for fast-charging infrastructure and power quality issues (analysis of harmonic injection and system resonance conditions due to large-scale penetration of EVs and supraharmonic injection) For professionals in electric vehicle technology, along with graduate and senior undergraduates, professors, and researchers in related fields, Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles is a useful, comprehensive, and accessible guide to gain an overview of the current state of the art.

Author: Fei Wu
Publisher:
ISBN:
Category :
Languages : en
Pages : 156

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Book Description
Electric vehicles hold great promise in improving transportation energy consumption efficiency. However, battery-related "range-anxiety" hampers large-scale EV adoption. To relieve range anxiety and accelerate wider EV adoption, two issues should be addressed. The first is how to develop and optimize the layout of a network of public EV charging stations to keep pace with increasing EV charging demand. Second, the strains of added EV charging loads on the electricity distribution infrastructure should be managed. This dissertation will address these two issues through new optimization models and simulations. Specifically, we formulate a stochastic flow-capturing charging station location model to solve the first issue and obtain an optimal charging station network layout. For the second issue, stochastic control models are created to schedule EV charging loads. This model assumes some flexibility to defer EV charging demands, to minimize distribution infrastructure investment and degradation costs. We expand this model to allow the charging station to participate ancillary service markets, either by modulating EV charging or by using distributed resources. The outcome of this dissertation will help EV infrastructure planners develop an adequate charging station network and facilitate wider EV adoption. It will also help system operators and energy planners better understand the challenges of vehicle-grid integration and prepare appropriate strategies to address these issues.

Author: Ukesh Chawal
Publisher:
ISBN:
Category : Battery charging stations (Electric vehicles)
Languages : en
Pages : 91

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Book Description
There has been a significant increase in the number of electric vehicles (EVs) mainly because of the need to have a greener living. Thus, ease of access to charging facilities is a prerequisite for large scale deployment for EV. The first component of this dissertation research seeks to formulate a deterministic mixed-integer linear programming (MILP) model to optimize the system of EV charging stations, the locations of the stations and the number of slots to be opened to maximize the profit based on the user-specified cost of opening a station. Despite giving the optimal solution, the drawback of MILP formulation is its extremely high computational time (as much as 5 days). The other limit of this deterministic model is that it does not take uncertainty in to consideration. The second component of this dissertation is to overcome the first drawback of the MILP model by implementing a two-stage framework developed by (Chawal et al. 2018), which integrates the first-stage system design problem and second-stage control problem of an EV charging stations using a design and analysis of computer experiments (DACE) based system design optimization approach. The first stage specifies the design of the system that maximizes expected profit. Profit incorporates costs for building stations and revenue evaluated by solving a system control problem in the second stage. The results obtained from the DACE based system design optimization approach, when compared to the MILP, provide near optimal solutions. Moreover, the computation time with the DACE approach is significantly lower, making it a more suitable option for practical use. The third component of this dissertation is to overcome the second drawback of the MILP model by introducing stochasticity in our model. A two-stage framework is developed to address the design of a system of electric vehicle (EV) charging stations. The first stage specifies the design of the system that maximizes expected profit. Profit incorporates costs for building stations and revenue evaluated by solving a system control problem in the second stage. The control problem is formulated as an infinite horizon, continuous-state stochastic dynamic programming problem. To reduce computational demands, a numerical solution is obtained using approximate dynamic programming (ADP) to approximate the optimal value function. To obtain a system design solution using our two-stage framework, we propose an approach based on DACE. DACE is employed in two ways. First, for the control problem, a DACE-based ADP method for continuous-state spaces is used. Second, we introduce a new DACE approach specifically for our two-stage EV charging stations system design problem. This second version of DACE is the focus of this paper. The "design" part of the DACE approach uses experimental design to organize a set of feasible first-stage system designs. For each of these system designs, the second-stage control problem is executed, and the corresponding expected revenue is obtained. The "analysis" part of the DACE approach uses the expected revenue data to build a metamodel that approximates the expected revenue as a function of the first-stage system design. Finally, this expected revenue approximation is employed in the profit objective of the first stage to enable a more computationally-efficient method to optimize the system design. To our knowledge, this is the only two-stage stochastic problem which uses infinite horizon dynamic programming approach to optimize the second stage dynamic control problem and the first stage system design problem. Moreover, when the designs obtained from our DACE approach and MILP design are solved using DACE-based ADP method (simulation), an improvement of approximately 8% is observed in the simulated profit obtained from ADP design compared to that of MILP design indicating that when uncertainty is considered, DACE ADP design provides the better solution.

Author: Walter Leal Filho
Publisher: Springer
ISBN: 331913194X
Category : Technology & Engineering
Languages : en
Pages : 396

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Book Description
Focusing on technical, policy and social/societal practices and innovations for electrified transport for personal, public and freight purposes, this book provides a state-of-the-art overview of developments in e-mobility in Europe and the West Coast of the USA. It serves as a learning base for further implementing and commercially developing this field for the benefit of society, the environment and public health, as well as for economic development and private industry. A fast-growing, interdisciplinary sector, electric mobility links engineering, infrastructure, environment, transport and sustainable development. But despite the relevance of the topic, few publications have ever attempted to document or promote the wide range of electric mobility initiatives and projects taking place today. Addressing this need, this publication consists of case studies, reports on technological developments and examples of successful infrastructure installation in cities, which document current initiatives and serve as an inspiration for others.

Author: M. Hadi Amini
Publisher: Springer
ISBN: 3319744127
Category : Technology & Engineering
Languages : en
Pages : 290

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Book Description
This book focuses on the theory and application of interdependent networks. The contributors consider the influential networks including power and energy networks, transportation networks, and social networks. The first part of the book provides the next generation sustainability framework as well as a comprehensive introduction of smart cities with special emphasis on energy, communication, data analytics and transportation. The second part offers solutions to performance and security challenges of developing interdependent networks in terms of networked control systems, scalable computation platforms, and dynamic social networks. The third part examines the role of electric vehicles in the future of sustainable interdependent networks. The fourth and last part of this volume addresses the promises of control and management techniques for the future power grids.

Author: Ottorino Veneri
Publisher: Springer
ISBN: 3319436511
Category : Technology & Engineering
Languages : en
Pages : 323

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Book Description
This book outlines issues related to massive integration of electric and plug-in hybrid electric vehicles into power grids. Electricity is becoming the preferred energy vector for the next new generation of road vehicles. It is widely acknowledged that road vehicles based on full electric or hybrid drives can mitigate problems related to fossil fuel dependence. This book explains the emerging and understanding of storage systems for electric and plug-in hybrid vehicles. The recharging stations for these types of vehicles might represent a great advantage for the electric grid by facilitating integration of renewable and distributed energy production. This book presents a broad review from analyzing current literature to on-going research projects about the new power technologies related to the various charging architectures for electric and plug-in hybrid vehicles. Specifically focusing on DC fast charging operations, as well as, grid-connected power converters and the full range of energy storage systems. These key components are analyzed for distributed generation and charging system integration into micro-grids. The authors demonstrate that these storage systems represent effective interfaces for the control and management of renewable and sustainable distributed energy resources. New standards and applications are emerging from micro-grid pilot projects around the world and case studies demonstrate the convenience and feasibility of distributed energy management. The material in this unique volume discusses potential avenues for further research toward achieving more reliable, more secure and cleaner energy.

Author: Tran Van Hung
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 0

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Book Description
Electric vehicles have become a trend as a replacement to gasoline-powered vehicles and will be a sustainable substitution to conventional vehicles. As the number of electric vehicles in cities increases, the charging demand has surged. The optimal location of the charging station plays an important role in the electric vehicle transit system. This chapter discusses the planning of electric vehicle charging infrastructure for urban. The purpose of this work develops an electric vehicle fast-charging facility planning model by considering battery degradation and vehicle heterogeneity in driving range, and considering various influencing factors such as traffic conditions, user charging costs, daily travel, charging behavior, and distribution network constraints. This work identifies optimal fast-charging stations to minimize the total cost of the transit system for deploying fast-charging networks. Besides, this chapter also analyzes some optimization modeling approach for the fast charging location planning, and point out future research directions.

Author:
Publisher:
ISBN: 9789279580086
Category :
Languages : en
Pages : 36

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Book Description
A geospatial analysis of electric-vehicle charging infrastructure allocation within a city and a region, based on open source GIS tools, is described. A methodology was developed to provide optimal locations of electric vehicle infrastructure (charging stations) within a spatially extended region. Two different cases were identified: placement in a city network (urban road network) and in a regional or national network (rural roads and highways). For a city and a regional network, the methodology identifies high-potential areas for the installation of charging station. In contrast, for a highway network the methodology provides explicitly the suggested locations: the charging stations should preferably be placed in already built areas, gas stations or rest areas, to minimize additional investment costs. A pilot study was made for the city of Bolzano/Bozen (city road network) and the province of Alto Adige/Südtirol (rural and highway network). The municipality and the province gave positive feedback on the suggested locations.