scholarly journals Dynamic Pricing for Electric Vehicle Charging—A Literature Review

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3574 ◽  
Author(s):  
Steffen Limmer
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Dynamic Pricing ◽  
Complex Form ◽  
User Preferences ◽  
Energy Resources ◽  
Time Varying ◽  
Renewable Energy Resources ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Time-varying pricing is seen as an appropriate means for unlocking the potential flexibility from electric vehicle users. This in turn facilitates the future integration of electric vehicles and renewable energy resources into the power grid. The most complex form of time-varying pricing is dynamic pricing. Its application to electric vehicle charging is receiving growing attention and an increasing number of different approaches can be found in the literature. This work aims at providing an overview and a categorization of the existing work in this growing field of research. Furthermore, user studies and the modeling of user preferences via utility functions are discussed.

scholarly journals Analysis of Using Biogas Resources for Electric Vehicle Charging in Bangladesh: A Techno-Economic-Environmental Perspective

2020 ◽  
Vol 12 (7) ◽  
pp. 2579 ◽  
Author(s):  
Ashish Kumar Karmaker ◽  
Md. Alamgir Hossain ◽  
Nallapaneni Manoj Kumar ◽  
Vishnupriyan Jagadeesan ◽  
Arunkumar Jayakumar ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Alternative Energy ◽  
Energy Resources ◽  
Viability Analysis ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Alternative Energy Resources

The growing popularity of electric vehicles (EV) is creating an increasing burden on the power grid in Bangladesh due to massive energy consumption. Due to this uptake of variable energy consumption, environmental concerns, and scarcity of energy lead to investigate alternative energy resources that are readily available and environment friendly. Bangladesh has enormous potential in the field of renewable resources, such as biogas and biomass. Therefore, this paper proposes a design of a 20 kW electric vehicle charging station (EVCS) using biogas resources. A comprehensive viability analysis is also presented for the proposed EVCS from technological, economic, and environmental viewpoints using the HOMER (Hybrid Optimization of Multiple Energy Resources) model. The viability result shows that with the capacity of 15–20 EVs per day, the proposed EVCS will save monthly $16.31 and $29.46, respectively, for easy bike and auto-rickshaw type electric vehicles in Bangladesh compare to grid electricity charging. Furthermore, the proposed charging station can reduce 65.61% of CO2 emissions than a grid-based charging station.

scholarly journals Optimal Scheduling of Micro Grid for Plug-In Electrical Vehicle

2018 ◽  
Vol 7 (2.7) ◽  
pp. 558
Author(s):  
K Vijay Kumar ◽  
T Bharath Kumar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Optimal Schedule ◽  
Clean Energy ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Electric Vehicle Charging ◽  
Micro Grid ◽  
Vehicle Charging ◽  
Ev Charging

Owing to several advantages of Plug-in Electric Vehicles (PEVs) like less noise, emission less, good efficiency and the reduced cost has attention to the governments, researchers and manufactures in recent time. The Plug-in Electric Vehicle (PEV) plays a vital role in    replacement of conventional vehicles in future, because of penetration of renewable energy resources in conventional generation. The modernized of micro grid is happening due to usage of clean energy for EV charging. The cost of electric vehicle charging is challenging issue in the development of plug-in electric vehicle. The coordination between renewable generation and conventional generation is very much needed in near future. The dynamic nature of renewable energy resources causes frequent interrupts in electric vehicle charging. The problem of nonlinear power generation with renewable resources is overcome by electric vehicle battery storage system which   enables the EV battery to charge during low demand period and gets discharged into the micro grid during high demand periods. This paper developed an optimal schedule for stationary Plug-in Electric Vehicle charging in operation with micro grid. The obtained optimal schedule provides balance between active and reactive power in generation and load as well. The integration of renewable energy resources is achieved through solar, wind in Vehicle-2-Grid (V2G) approach which is used to safeguard to renewable energy resources by store additional energy produced during peak load period and feeding back to the micro grid during low load period. As a result the stable operation of the micro grid and EV charging with low cost is achieved in this paper. 

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

scholarly journals Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

2021 ◽  
Vol 13 (11) ◽  
pp. 6163
Author(s):  
Yongyi Huang ◽  
Atsushi Yona ◽  
Hiroshi Takahashi ◽  
Ashraf Mohamed Hemeida ◽  
Paras Mandal ◽  
...  
Keyword(s):  
Power Generation ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Mixed Integer ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Photovoltaic Power ◽  
Vehicle Charging ◽  
Charging Stations

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.

scholarly journals An Optimal Control Algorithm with Reduced DC-Bus Current Fluctuation for Multiple Charging Modes of Electric Vehicle Charging Station

2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Current Fluctuation ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Three Phase ◽  
Optimization Control ◽  
Dc Bus ◽  
Vehicle Charging

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.

scholarly journals Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2692 ◽  
Author(s):  
Juncheng Zhu ◽  
Zhile Yang ◽  
Monjur Mourshed ◽  
Yuanjun Guo ◽  
Yimin Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Comparative Study ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Load Forecasting ◽  
Learning Approaches ◽  
Short Term ◽  
Learning Methods ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Load forecasting is one of the major challenges of power system operation and is crucial to the effective scheduling for economic dispatch at multiple time scales. Numerous load forecasting methods have been proposed for household and commercial demand, as well as for loads at various nodes in a power grid. However, compared with conventional loads, the uncoordinated charging of the large penetration of plug-in electric vehicles is different in terms of periodicity and fluctuation, which renders current load forecasting techniques ineffective. Deep learning methods, empowered by unprecedented learning ability from extensive data, provide novel approaches for solving challenging forecasting tasks. This research proposes a comparative study of deep learning approaches to forecast the super-short-term stochastic charging load of plug-in electric vehicles. Several popular and novel deep-learning based methods have been utilized in establishing the forecasting models using minute-level real-world data of a plug-in electric vehicle charging station to compare the forecasting performance. Numerical results of twelve cases on various time steps show that deep learning methods obtain high accuracy in super-short-term plug-in electric load forecasting. Among the various deep learning approaches, the long-short-term memory method performs the best by reducing over 30% forecasting error compared with the conventional artificial neural network model.

Smart Electric Vehicle Charging

ITNOW ◽  
2019 ◽  
Vol 61 (4) ◽  
pp. 12-13
Author(s):  
Harry Leeks
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Pivotal Role ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Abstract What does IT have to do with the charging of electric vehicles? In this article, Harry Leeks, a graduate IT Analyst at National Grid, explains how IT plays a pivotal role in the electric vehicle charging market.

Study on the Harmonic Impact of Large Scale Electric Vehicles to Grid

2013 ◽  
Vol 443 ◽  
pp. 273-278 ◽  
Author(s):  
Ceng Ceng Hao ◽  
Yue Jin Tang ◽  
Jing Shi
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Large Scale ◽  
Flow Distribution ◽  
Electric Grid ◽  
Nonlinear Loads ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations ◽  
Harmonic Problem

Large scale electric vehicles integration into power grid, as nonlinear loads, will pose inevitable impacts on the operation of power system, one of which the harmonic problem will affect the power quality greatly. Firstly, the article analyzes the characteristics of harmonic caused by electric vehicle charging. And then, the harmonic flow distribution is analyzed based on the IEEE standard node systems. During transient analyses, the electric vehicle charging stations connected to electric grid are represented as harmonic sources. Results show that structure and voltage grade of electric grid, capacity and access points of electric vehicle charging load will have different effects on harmonic problem. At last, a few conclusions are given for connecting electric vehicles to electric grid.

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