scholarly journals Design and Analysis of a Solar-Powered Electric Vehicle Charging Station for Indian Cities

2021 ◽  
Vol 12 (3) ◽  
pp. 132
Author(s):  
Aanya Singh ◽  
Shubham Sanjay Shaha ◽  
Nikhil P G ◽  
Yendaluru Raja Sekhar ◽  
Shaik Saboor ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Energy Generation ◽  
Maximum Energy ◽  
Performance Ratio ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Battery Capacity ◽  
Solar Powered ◽  
Carbon Dioxide Co2 ◽  
Indian Cities

Due to depleting fossil fuel reserves coupled with a climate crisis, sustainability is gaining ground, and electric vehicles (EVs) are emerging to be the new face of this field. However, the idea of EVs will be genuinely sustainable only if they are charged using renewable energy. This paper presents results from the design of a solar-powered EV charging station for an Indian context. PVsyst 7.2 software has been used for the system design. The analysis, based on the number of cars charged annually, the monthly variation in energy generation, the investment cost, and the decrease in carbon dioxide (CO2) emissions using different module technologies for six Indian cities, has been deliberated. The results indicate that an off-grid 8.1 kWp system with two days of battery autonomy has the fewest unused energy losses, with a good performance ratio (PR). It can completely charge around 414 vehicles of 30 kWh battery capacity annually. This would help to reduce annual CO2 emissions by approximately 7950 kg. For cities near the equator, maximum energy is produced during March or January, and for cities near the Tropic of Cancer, energy production maximizes during May–June. The overall system has better energy generation and economy when monocrystalline modules are used.

scholarly journals Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model

Energies ◽  
2015 ◽  
Vol 8 (11) ◽  
pp. 13265-13283 ◽  
Author(s):  
Bin Ye ◽  
Jingjing Jiang ◽  
Lixin Miao ◽  
Peng Yang ◽  
Ji Li ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Feasibility Study ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Solar Powered

scholarly journals Renewable Energy Tracking and Optimization in a Hybrid Electric Vehicle Charging Station

2020 ◽  
Vol 11 (1) ◽  
pp. 245
Author(s):  
Andrija Petrusic ◽  
Aleksandar Janjic
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Multicriteria Optimization ◽  
Hybrid Electric Vehicle ◽  
Small Scale ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Battery Capacity ◽  
Hybrid Electric ◽  
Vehicle Charging

The increasing electric vehicle fleet requires an upgrade and expansion of the available charging infrastructure. The uncontrolled charging cycles greatly affect the electric grid, and for this reason, renewable energy sources and battery storage are getting incorporated into a hybrid charging station solution. Adding a renewable source and a battery to the charging station can help to “buffer” the power required from the grid, thus avoiding peaks and related grid constraints. To date, the origin of the energy coming from the battery has not been traced. In this paper, a solution of the hybrid electric vehicle charging station coupled with the small-scale photovoltaic system and battery energy storage is proposed to eliminate the adverse effects of uncontrolled electric vehicle charging, with the exact calculation of renewable energy share coming from energy stored in the battery. The methodology for the multicriteria optimization of the charging/discharging schedule of a battery and electric vehicle charging level is based on multi-attribute utility theory. The optimization criteria include the minimization of charging costs, maximization of renewable energy (from both the solar plant and the battery), and the minimization of battery degradation. The problem is solved using a genetic algorithm optimization procedure adapted to the multicriteria optimization function. The methodology is tested on an illustrative example, and it is proven that the decision-maker’s preferences greatly affects the choice of the optimal strategy and the optimal battery capacity.

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