Selection of Charging Station Technology to Support the Adoption of Electric Vehicles in Indonesia with the AHP-TOPSIS Method

Author(s):  
Andri D. Setiawan ◽  
Akhmad Hidayatno ◽  
Bramanda Dwi Putra ◽  
Irvanu Rahman
2013 ◽  
Vol 291-294 ◽  
pp. 2362-2365
Author(s):  
Bo Ye ◽  
Zhang Zhou He ◽  
Guo Meng Huang ◽  
Xue Song He ◽  
Hui Quan Li

With the development of electric vehicle industry, it is necessary to construct more electric vehicle charging stations to promote the popularization of electric vehicles. As photovoltaic generation owns flexible installing, convenient power supplying, and environmental protecting characteristics, it is suitable for providing power for electric vehicle charging stations and reducing a network loads. After analyzed electric vehicle charging demand, this paper proposed the designing concept of the electric system for the photovoltaic generation mix charging station, which was based on the battery charging and discharging characteristics as well as its usage. Then, the paper provided a selection of electric equipments for the charging station and an electric wiring diagram after designing the electric system. This study and design may help for promoting construction of electric vehicle charging stations, and development and popularization of electric vehicles.


Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6120
Author(s):  
Nikolaos Milas ◽  
Dimitris Mourtzis ◽  
Emmanuel Tatakis

During the last decade, the technologies related to electric vehicles (EVs) have captured both scientific and industrial interest. Specifically, the subject of the smart charging of EVs has gained significant attention, as it facilitates the managed charging of EVs to reduce disturbances to the power grid. Despite the presence of an extended literature on the topic, the implementation of a framework that allows flexibility in the definition of the decision-making objectives, along with user-defined criteria is still a challenge. Towards addressing this challenge, a framework for the smart charging of EVs is presented in this paper. The framework consists of a heuristic algorithm that facilitates the charge scheduling within a charging station (CS), and the analytic hierarchy process (AHP) to support the driver of the EV selecting the most appropriate charging station based on their needs of transportation and personal preferences. The communications are facilitated by the Open Platform Communications–Unified Architecture (OPC–UA) standard. For the selection of the scheduling algorithm, the genetic algorithm and particle swarm optimisation have been evaluated, where the latter had better performance. The performance of the charge scheduling is evaluated, in various charging tasks, compared to the exhaustive search for small problems.


Systems ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Mahdi Boucetta ◽  
Niamat Ullah Ibne Hossain ◽  
Raed Jaradat ◽  
Charles Keating ◽  
Siham Tazzit ◽  
...  

Exponential technological-based growth in industrialization and urbanization, and the ease of mobility that modern motorization offers have significantly transformed social structures and living standards. As a result, electric vehicles (EVs) have gained widespread popularity as a mode of sustainable transport. The increasing demand for of electric vehicles (EVs) has reduced the some of the environmental issues and urban space requirements for parking and road usage. The current body of EV literature is replete with different optimization and empirical approaches pertaining to the design and analysis of the EV ecosystem; however, probing the EV ecosystem from a management perspective has not been analyzed. To address this gap, this paper develops a systems-based framework to offer rigorous design and analysis of the EV ecosystem, with a focus on charging station location problems. The study framework includes: (1) examination of the EV charging station location problem through the lens of a systems perspective; (2) a systems view of EV ecosystem structure; and (3) development of a reference model for EV charging stations by adopting the viable system model. The paper concludes with the methodological implications and utility of the reference model to offer managerial insights for practitioners and stakeholders.


2021 ◽  
Vol 13 (11) ◽  
pp. 6163
Author(s):  
Yongyi Huang ◽  
Atsushi Yona ◽  
Hiroshi Takahashi ◽  
Ashraf Mohamed Hemeida ◽  
Paras Mandal ◽  
...  

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.


2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.


Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.


Machines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 124
Author(s):  
Dantam Rao ◽  
Madhan Bagianathan

Currently, permanent-magnet-type traction motors drive most electric vehicles. However, the potential demagnetization of magnets in these motors limits the performance of an electric vehicle. It is well known that during severe duty, the magnets are demagnetized if they operate beyond a ‘knee point’ in the B(H) curve. We show herein that the classic knee point definition can degrade a magnet by up to 4 grades. To prevent consequent excessive loss in performance, this paper defines the knee point k as the point of intersection of the B(H) curve and a parallel line that limits the reduction in its residual flux density to 1%. We show that operating above such a knee point will not be demagnetizing the magnets. It will also prevent a magnet from degenerating to a lower grade. The flux density at such a knee point, termed demag flux density, characterizes the onset of demagnetization. It rightly reflects the value of a magnet, so can be used as a basis to price the magnets. Including such knee points in the purchase specifications also helps avoid the penalty of getting the performance of a low-grade magnet out of a high-grade magnet. It also facilitates an accurate demagnetization analysis of traction motors in the worst-case conditions.


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