scholarly journals Technical and economic calculation of a solar-powered charging station for electric vehicles

2021 ◽  
pp. 71-78
Author(s):  
Andrii Hnatov ◽  
Shchasiana Arhun ◽  
Hanna Hnatova ◽  
Pavlo Sokhin
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Internal Combustion Engines ◽  
Renewable Energy Sources ◽  
Economic Indicators ◽  
Energy Sources ◽  
Economic Calculation ◽  
Charging Station ◽  
Solar Powered ◽  
Technical And Economic Indicators

Problem. Development and implementation of green technologies is both an urgent and a cost-effective scientific and engineering task. Therefore, the issues related to the study of renewable energy sources, which are used as the main sources of energy for electric vehicles, are quite relevant and promising. At the same time, an equally important question is how profitable is building solar charging stations in terms of both ecology and economy. Goal. The aim is calculation and analysis of technical and economic indicators of a solar charging station for electric vehicles (EV). Methodology. The analytical methods of studying the development and application of the ways and devices to transform the energy of the sun into electricity are used, as well as the methods of experimental research and mathematical methods of processing and modulation of the received results; methods of calculating technical and economic indicators. Results. The review of the literature on the development of renewable energy sources, in particular, solar power plants, and the spread of electric vehicles with the gradual displacement (replacement) of traditional cars working on internal combustion engines with electric vehicles (BEV and PHEV) was made. The main parameters and technical characteristics of the solar-powered charging station (SPCS) were studied. For the analysis and calculation of technical and economic indicators of SPCS for EV it is offered to take a SPP with a capacity of 20 kW as a basis. The calculation of SPCS electricity generation both for own consumption and for power supply of EV and the sale of surplus electricity to the general network at the “green tariff” was carried out. Originality. The technical and economic calculation of SCS was made taking into account the rise of electricity prices in Kharkiv region (Ukraine). Practical value. According to the analysis of the obtained results, it can be said that the payback period of SPCS for EV is about 7.9 years. If we consider the constant increase in the cost of electricity (approximately 15% per year), we can expect the payback after 6.8 years of operation.

scholarly journals Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4240 ◽  
Author(s):  
Khairy Sayed ◽  
Ahmed G. Abo-Khalil ◽  
Ali S. Alghamdi
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Dc Microgrid ◽  
Charging Station ◽  
And Control ◽  
Ev Charging

This paper introduces an energy management and control method for DC microgrid supplying electric vehicles (EV) charging station. An Energy Management System (EMS) is developed to manage and control power flow from renewable energy sources to EVs through DC microgrid. An integrated approach for controlling DC microgrid based charging station powered by intermittent renewable energies. A wind turbine (WT) and solar photovoltaic (PV) arrays are integrated into the studied DC microgrid to replace energy from fossil fuel and decrease pollution from carbon emissions. Due to the intermittency of solar and wind generation, the output powers of PV and WT are not guaranteed. For this reason, the capacities of WT, solar PV panels, and the battery system are considered decision parameters to be optimized. The optimized design of the renewable energy system is done to ensure sufficient electricity supply to the EV charging station. Moreover, various renewable energy technologies for supplying EV charging stations to improve their performance are investigated. To evaluate the performance of the used control strategies, simulation is carried out in MATLAB/SIMULINK.

scholarly journals Development of A Solar Panel Auxiliary System in Order to Extend Range

2018 ◽  
Vol 9 (1) ◽  
pp. 235-238
Author(s):  
Tibor Tóth
Keyword(s):  
Renewable Energy ◽  
Solar Cells ◽  
Solar Cell ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Limited Range ◽  
Cell System ◽  
Energy Sources ◽  
Solar Powered ◽  
Leaf Model

Abstract The aim of this research is to find a solution that can contribute to the more widespread use of electric vehicles and, through development, promote the use of renewable energy sources. It aims to eliminate the disadvantages of electric vehicles, such as self-discharge, stationary charging and limited range. The focus is mainly a solar-powered solution, since small solar cells have already been implemented on the commercially available Nissan Leaf model to solve similar problems but with very little or no improvement. Encouraged by this attempt I have engineered a larger, more useful auxiliary solar cell system to improve the range of these vehicles.

scholarly journals Solar Charging Station for Electric Vehicles

2021 ◽  
pp. 316-325
Author(s):  
Bugatha Ram Vara Prasad ◽  
T. Deepthi ◽  
N. Satyavathi ◽  
V. Satish Varma ◽  
R. Hema Kumar
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Renewable Energy Resources ◽  
Promising Alternative ◽  
Charging Station ◽  
Smart Charging ◽  
Solar Powered

This paper describes design of solar powered charging station for charging of electric vehicle that solves the key downside of fuel and pollution. While EV charging has traditionally been grid-based, use of solar powered chargers has emerged as an interesting opportunity. As worlds resources are diminishing, government agencies and non-government organization are pushing greener solution through the use of renewable energy sources. In order to reduce the pollution through the motor vehicles, there is a large scope of increase in electric vehicles all over the world. To run the electric vehicle the fuel required is the electricity which can be storable through the use of solar energy. Electric vehicles that run on the Electric vehicle smart charging station which is the promising alternative and environmentally sustainable solution to meet up the energy crisis. This paper investigates the possibility of charging the battery of electric vehicles at a various working place like offices, colleges, hospitals, universities etc in India using solar energy. In this paper, the charging station successfully developed as desired features for electric vehicle from renewable energy resources with solar panel, solar charge controller, batteries storage and DC-DC converter. A laboratory-scale experimental prototype was also developed, and the performance of the proposed charging station was investigated.

scholarly journals Optimal Framework to Maximize the Workplace Charging Station Owner Profit while Compensating Electric Vehicles Users

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Soumia Ayyadi ◽  
Mohamed Maaroufi
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Distribution Functions ◽  
Sustainable Transportation ◽  
Mixed Integer ◽  
Energy Sources ◽  
User Behaviour ◽  
Charging Station ◽  
Workplace Charging

Electric vehicles (EVs) are one promising technology for an improved sustainable transportation sector, particularly when they are charged with electricity from renewable energy sources. However, the EV user behaviour uncertainties as well as the fluctuating generation of renewable energy sources make the interaction between these technologies challenging. In this work, a new approach to coordinate the charging process of multiple EVs parked at workplace charging station (WCS) equipped with Photovoltaic panels (PV) is proposed. Considering the PV incremental cost and the day-ahead electricity price (DAEP), an optimal framework is introduced to maximize the WCS owner profit while compensating the EV users for discharging their EVs’ battery. The EV user behaviour uncertainties are modeled by probability distribution functions, and the PV generation is forecasted by the backpropagation neural network model (BPNN). The optimization problem is solved by mixed-integer linear programming (MILP) while the Monte Carlo sampling methods have been applied to handle the EV user behaviour uncertainties. The results show that the proposed method increases the WCS owner profit and the EV user compensation by 54% and 50.7%, respectively, compared to uncoordinated charging. Moreover, the estimated WCS owner profit and the EV user compensation generated by coordinated charging are 1.72% and 1.35%, respectively, higher than the profits based on real user behaviour data.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohamad Nassereddine
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Power Network ◽  
Network Stability ◽  
Fast Charging ◽  
Electrical Loads ◽  
Charging Stations

AbstractRenewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

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