Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits

Liu, Youbo; Xiang, Yue; Tan, Yangyang; Wang, Bin; Yang, Zhiyu

doi:10.1109/access.2018.2843810

Cited by 38 publications

(19 citation statements)

References 29 publications

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“…As a result, the grid receives full impact from the irregular charging/discharging loads of EVs, thus increasing the level of power quality (PQ) problems in the power distribution system. In [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], ECSs not using RE and ESSs were investigated. Based on the results presented in the reviewed papers, in some cases, only limited EVs can possibly be connected.…”

Section: Ecss Without Res and Esssmentioning

confidence: 99%

“…A more than 500% higher profit was observed using the proposed method compared to a common benchmark method. The design and configuration of ECSs were explored in [30][31][32][33][34][35][36][37][38]. I. S. Bayram et al [30] proposed two frameworks for the capacity planning of ECS networks with various charging technologies to satisfy multiclass customers with various charging needs.…”

Section: Ecss Without Res and Esssmentioning

confidence: 99%

“…In [34], stochastic models and the Monte Carlo method were used to simulate the behaviors of taxi and bus fleets in order to optimize the capacities of ECSs. Invertor and user's benefits were coordinated in [35] using a bi-level optimal allocation model which could be simplified into a single-layer optimization model with Karush-Kuhn-Tucker optimality conditions. S. Wang et al [36] modeled three types of ECSs and used a multi-objective evolutionary algorithm to optimize the planning of an ECS infrastructure.…”

Section: Ecss Without Res and Esssmentioning

confidence: 99%

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System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review

2019

Energies

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The optimal planning of electric vehicle (EV) charging stations (ECSs) with advanced control algorithms is very important to accelerate the development of EVs, which is a promising solution to reduce carbon emissions of conventional internal combustion engine vehicles (ICEVs). The large and fluctuant load currents of ECSs can bring negative impacts to both EV-related power converters and power distribution systems if the energy flow is not regulated properly. Recent review papers related to EVs found in open literature have mainly focused on the design of power converter-based chargers and power interfaces, analyses of power quality (PQ) issues, the development of wireless charging techniques, etc. There is currently no review paper that focuses on key technologies in various system configurations, optimal energy management and advanced control issues in practical applications. To compensate for this insufficiency and provide timely research directions, this paper reviews 143 previously published papers related to the aforementioned topics in recent literature including 17 EV-related review papers found in Institute of Electrical and Electronics Engineers (IEEE)/Institution of Engineering and Technology (IET) (IEEE/IET) Electronic Library (IEL) and ScienceDirect OnSite (SDOS) databases. In this paper, existing system configurations, related design methods, algorithms and key technologies for ECSs are systematically reviewed. Based on discussions given in the reviewed papers, the most popular ECS configuration is a hybrid system design that integrates renewable energy (RE)-based power generation (REBPG), various energy storage systems (ESSs), and utility grids. It is noteworthy that the addition of an ESS with properly designed control algorithms can simultaneously buffer the fast, fluctuant power demand during charging, smooth the intermittent power generation of REBPG, and increase the overall efficiency and operating flexibility of ECSs. In addition, verifying the significance of the flexibility and possible profits that portable ESSs provide in ECS networks is a potential research theme in ECS fields, in which the potential applications of portable ESSs in the grid-tied ECSs are numerous and could cover a full technical spectrum.

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Section: Ecss Without Res and Esssmentioning

confidence: 99%

Section: Ecss Without Res and Esssmentioning

confidence: 99%

Section: Ecss Without Res and Esssmentioning

confidence: 99%

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System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review

2019

Energies

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“…In [20,21] a multiobjective optimization problem is solved with the aim of minimizing power loss, voltage deviation, and cost to optimally allocate the EVCS in candidate buses. In [22] bi-level optimal allocation model is presented for allocating an EVCS with the aim of maximizing the coordinated benefits of the EVCS investor and EV owners, but the benefits of DSO is not considered. In [23] a multi-objective program is proposed, based on hybrid chicken swarm and teaching-learning-based optimization algorithm, to obtain the best EVCS placement.…”

Section: Introductionmentioning

confidence: 99%

“…However, the investment costs of constructing these resources and the intermittent behavior of such resources are serious challenges that have not been addressed. Importantly, the adopted program for charging/ discharging of EV's battery is one of the main components of EVCS allocation, which is not considered in some papers such as [20,22,23,[25][26][27]. On the other hand, this program has a significant impact on distribution network performance and operation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Electric Vehicle Charging Stations With Adopted Smart Charging/Discharging Schedule

et al. 2020

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Modeling and allocation of the Electric vehicles Charging Stations (EVCS) within the distribution network, as per the growing use of Electric vehicles (EVs) is a challenging task. In this paper, to manage the EVCS, first, with the aim of peak shaving, valley filling, and flattening the load curve of the network, the optimal planning of EV's charging/discharging is devised. In this regard, after modeling involving random variables, a novel hybrid method, based on the Multi Objective Particle Swarm Optimization (MOPSO) optimization algorithm and sequential Monte Carlo simulation is presented. The purpose of the presented optimal charge/discharge schedule is to control the rate and time of charging/ discharging of EVs. In the proposed model, various battery operation strategies, including Uncontrolled Charging Mode (UCM), Controlled Charging Mode (CCM), and Smart Charge/Discharge Mode (SCDM) are also considered. In the next step, in order to implement the charge/discharge schedule of the EVCS profitably, a new formulation is presented for the allocation of two EVCSs (administrative and residential EVCS). In the proposed formulation, various objective functions such as power loss reduction, reducing power purchases from the upstream network, reducing voltage deviation in buses, improving reliability is addressed. Moreover, to incentivize the owner to construct the EVCS with adopted charging/discharging schedule, the optimal profits sharing between Distribution System Operator (DSO) and EVCS owner is also performed. The proposed formulation is applied to a standard network (IEEE 69 buses) and encouraging results are achieved.

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Impact of Reliability Indices for Planning Charging Station Load in a Distribution Network

Archana

Rajeev

2022

Smart Grids and Microgrids

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Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits

Cited by 38 publications

References 29 publications

System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review

System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review

Optimal Allocation of Electric Vehicle Charging Stations With Adopted Smart Charging/Discharging Schedule

Impact of Reliability Indices for Planning Charging Station Load in a Distribution Network

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