Electric vehicles (EVs) are a promising solution to urban environmental challenges, but their unplanned growth could strain both the road and electric networks. To address this issue, this paper ...introduces the Combined Model of Road Transport and Electric Distribution Network (CoRTED), a framework for strategically deploying EV charging stations considering the dynamics of both networks. The CoRTED model minimizes EV user travel costs, power loss, and voltage deviation. The model employs a bi-level optimization approach with PSO-DS algorithm for station deployment and combined convex optimization (CCO) for traffic network equilibrium. Grid economic operation is formulated as AC OPF and solved using a primal-dual interior point method. Validation is performed using a modified Nguyen-Dupius RTN and IEEE 33 bus EDN, demonstrating CoRTED's effectiveness in integrated network planning for EV infrastructure. Due to the increase in power demand by EVs, the loss and voltage deviation are increased to 4.679 MW and 24.23%, respectively. The proposed model reduces the losses and voltage deviation by 4.487 MW and 1.24%. Also, the total travel cost on the traffic network is reduced by 1.9% as the charging costs at each charging station are reduced.
•Minimum number of fast-charging stations along the highway network are identified.•An flow-refueling location model (FRLM) is applied.•The model uses a comprehensive flow dataset of the European ...highway network.•The operation of fast-charging stations is going to be highly profitable.•The workload is widely unequally distributed between these charging stations.
For a successful market take-up of plug-in electric vehicles, fast-charging stations along the highway network play a significant role. This paper provides results from a first study on estimating the minimum number of fast-charging stations along the European highway network of selected countries (i.e., France, Germany, the Benelux countries, Switzerland, Austria, Denmark, the Czech Republic, and Poland) and gives an estimate on their future profitability. The combination of a comprehensive dataset of passenger car trips in Europe and an efficient arc-cover-path-cover flow-refueling location model allows generating results for such a comprehensive transnational highway network for the first time. Besides the minimum number of required fast-charging stations which results from the applied flow-refueling location model (FRLM), an estimation of their profitability as well as some country-specific results are also identified. According to these results the operation of fast-charging stations along the highway will be attractive in 2030 because the number of customers per day and their willingness to pay for a charge is high compared to inner-city charging stations. Their location-specific workloads as well as revenues differ significantly and a careful selection of locations is decisive for their economic operation.
The placement of electric vehicle charging stations (EVCSs), which encourages the rapid development of electric vehicles (EVs), should be considered from not only operational perspective such as ...minimizing installation costs, but also user perspective so that their strategic and competitive charging behaviors can be reflected. This paper proposes a methodological framework to consider crowdedness and individual preferences of electric vehicle users (EVUs) in the selection of locations for fast-charging stations. The electric vehicle charging station placement problem (EVCSPP) is solved via a decentralized game theoretical decision-making algorithm and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means clustering algorithm. The proposed algorithm, referred to as <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-GRAPE, determines the locations of charging stations to maximize the sum of utilities of EVUs. In particular, we analytically present that 50% of suboptimality of the solution can be at least guaranteed, which is about 17% better than the existing game theoretical based framework. We show a few variants to describe the utility functions that may capture the difference in preferences of EVUs. Finally, we demonstrate the viability of the decision framework via three real-world data-based experiments. The results of the experiments, including a comparison with a baseline method are then discussed.
Charging infrastructure planning has a strategic impact on promoting the use of electric vehicles (EVs) and other alternative fuel vehicles. Importantly, decision makers need to answer the question ...on the number and location of charging stations in a way to satisfy customer recharging demand and meet certain restrictions imposed by real-life considerations. In this context, we consider the charging station location problem (CSLP), which belongs to the category of facility location problems and seeks to optimize the locations of charging stations. A growing body of literature has developed on this subject in recent years. Various approaches have been proposed to model the problem taking into account different features, constraints, decisions and performance measures as well as the dynamic and stochastic components inherent to the problem. Moreover, efficiently solving CSLP, particularly when applied to real-life case-studies, might be challenging in practice. Considerable effort has thus been made by researchers to develop innovative solution methods based on exact or heuristic approaches to obtain good quality solutions within short computation times. Therefore, we provide in this paper a comprehensive review on the literature relevant to CSLP, with a particular focus on modeling and solving the problem. We analyze the literature from different perspectives including demand representation, demand coverage approaches, objective functions, side constraints, decision variables, model structure as well as time dependency and uncertainty on the problem parameters. We also present various ways of classifying existing works, which allows readers to capture different aspects of the problem that researchers have tended to focus on and identify opportunities for further developments. We believe our work could be helpful to researchers by providing an overview of the CSLP literature and suggesting perspectives for future research in the field.
•We provide a comprehensive review on the charging station location problem.•We carry out a detailed analysis of the main modeling features of the problem.•We review methods used in the literature to efficiently solve the problem.•We propose different ways of classification of the literature.•We identify future research perspectives in the field.
Hydrogen energy storage system (HESS) has attracted tremendous interest due to its low emissions and high storage efficiency. In this article, the HESS is considered as an essential tool in ...hydrogen-integrated transportation and power systems to alleviate EV charging demand forecast error in a fast-charging station (FCS) and to solve voltage deviation problem due to the huge uptake of fast chargers on the utility grid. First, the wavelet transform (WT) method and long short-term memory (LSTM) neural network are combined to precisely predict the nonstationary traffic flow (TF). Then, a queueing theory-based model is developed to convert the predicted TF to the expected EV charging demand in FCS by considering charging service limitations and driver behaviors. Third, the charging demand prediction error is used to schedule the components in a HESS by considering their inherent properties and operational limits. As a result, the HESS configuration can be determined by analyzing the tradeoff between the investment cost and the monetary penalty due to charging demand forecast error and voltage deviation. The proposed solution is validated through a case study with mathematical justifications and simulation results.
Electric vehicles (EVs) are considered as the leading-edge form of mobility. However, the integration of electric vehicles with charging stations is a contentious issue. Managing the available grid ...power and bus voltage regulation is addressed through renewable energy. This work proposes a grid-connected photovoltaic (PV)-powered EV charging station with converter control technique. The controller unit is interfaced with the renewable energy source, bidirectional converter, and local energy storage unit (ESU). The bidirectional converter provides a regulated output with a fuzzy logic controller (FLC) during charging and discharging. The fuzzy control is implemented to maintain a decentralized power distribution between the microgrid DC-link and ESU. The PV coupled to the DC microgrid of the charging station is variable in nature. Hence, the microgrid-based charging is examined under a range of realistic scenarios, including low, total PV power output and different state of charge (SOC) levels of ESU. In order to accomplish the effective charging of EV, a decentralized energy management system is created to control the energy flow among the PV system, the battery, and the grid. The proposed controller’s effectiveness is validated using a simulation have been analyzed using MATLAB under various microgrid situations. Additionally, the experimental results are validated under various modes of operation.
The battery swapping mode (BSM) for an electric vehicle (EV) is an efficient way of replenishing energy. However, there have been perceived operation-related issues related large-scale deployment of ...the BSM. However, previous reviews have failed to examine the mathematical methods of the operation optimization process, which are highlighted in this work. The paper aims to provide a complete and systematic overview of the operation optimization approaches for EV battery swapping and charging stations. This work addresses the current operation mode of battery swapping networks and examines the optimization objectives, constraints, and mathematical programming methods. The paper highlights the motivations of different ownership models for establishing different objectives and discusses the merits and drawbacks of approaches in previous studies for different application scenarios. For the possible focus of future work, the paper details opportunities and challenges of dynamic service pricing, battery-to-grid scheduling, and behavior scheduling. This review aids future research of battery charging and swapping station operation and vehicle scheduling, and provides a systematic and theoretical reference for model selection.
•Features and applications of mainstream battery swapping networks are outlined. .•Discussing the motivation, approach and ownership of the optimization objective. .•Providing a critical examination of the optimization approach.•Opportunities and challenges for BSCS to achieve better operations.
The concept of smart city strives for greener technology to reduce carbon emission to ameliorate the global warming. Following this footprint, the transportation sector is experiencing a paradigm ...shift and the transition to electric vehicles (EVs) has prodigious plausibility in reducing carbon emission. However, the anticipated EV penetration is hindered by several challenges, among them are their shorter driving range, slower charging rate and the lack of ubiquitous availability of charging locations, which collectively contribute to range anxieties for EVs' drivers. Meanwhile, the expected immense EV load onto the power distribution network may degrade the voltage stability. 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 time and shorter travel distance 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. We also propose two heuristic methods and compare our solution with them. Finally, a custom built Python-based discrete event simulator is developed to test our outcomes.
Electric Vehicles (EVs) can effectively mitigate global warming issues while ensuring energy security, when compared with conventional fuel-based vehicles. Therefore, proper planning and development ...of charging infrastructure are essential to promote EVs. This paper proposes a multi-objective formulation to determine fast charging stations' optimal placement and sizing on intra-city corridors in a coupled transportation and Electrical Power Distribution Network (EPDN). The proposed formulation does a distance-based mapping between all transportation and EPDN nodes for precisely observing the impact of EV charging on EPDN. The proposed planning simultaneously considers the objectives and constraints of the transportation network and EPDN while satisfying the EV charging requirements. The EV charging demand, utilized in planning, is predicted using the Random Forest technique while considering the day type, hourly weather, and traffic flow that affect the forecasting accuracy. The improved Particle Swarm Optimization with Constriction Factor solves the proposed formulation for a 30-node EPDN coupled with a 25-node transportation network. The analysis of various cases, including varying initial State-Of-Charge of EVs and percentage growth of EVs per year, proves the efficacy and robustness of the proposed work. Note to Practitioners-The planned deployment of charging infrastructure is critical to facilitate EVs' adoption and sustainable growth of EV industries. Since, EV charging stations couple transportation network and EPDN, the planning strategy should consider requirements of both networks. For satisfactory driving experience of EV users, the planning should also consider driving range constraints and charging requirements of EV users. Several works on charging infrastructure planning have been carried out. However, several aspects relevant to EV users, transportation networks, EPDN, and determining EV charging demand have been overlooked in existing literature (as evidenced through <xref rid="table1" ref-type="table">Table I ). These aspects must be considered simultaneously while planning charging stations. Hence, this work proposes a planning strategy for optimal placement and sizing of fast EV charging stations in a metropolitan city connecting multiple suburbs while considering several aspects of transportation networks and EPDNs. The proposed strategy can be utilized by utilities for efficient deployment of charging infrastructure on metropolitan city intra-city corridors. It establishes a distance-based mapping between all transportation and EPDN nodes for observing the impact of EV charging on EPDN. The determination of EV charging demand is a crucial step in the planning, which is determined by forecasting hourly traffic flow while considering several key attributes. The proposed approach achieves the EPDN objectives of reducing power loss, voltage deviation, and total charging stations' establishment cost, and transportation network objectives of maximising captured traffic flow while satisfying driving range constraints and charging requirements of EVs. Therefore, the focus is to utilize the existing grid infrastructure optimally while achieving the objectives and satisfying constraints of EV users, transportation network, and EPDN. Relevant case studies demonstrate the efficacy and robustness of proposed approach. The uncertainties in EVs' injections and arrival/departure times will be considered in our future work.
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