Optimal allocation of electric vehicle charging stations in a highway network: Part 2. The Italian case study

2019 ◽  
Vol 26 ◽  
pp. 101015 ◽  
Author(s):  
Giuseppe Napoli ◽  
Antonio Polimeni ◽  
Salvatore Micari ◽  
Giorgio Dispenza ◽  
Vincenzo Antonucci
2020 ◽  
Vol 27 ◽  
pp. 101102 ◽  
Author(s):  
Giuseppe Napoli ◽  
Antonio Polimeni ◽  
Salvatore Micari ◽  
Laura Andaloro ◽  
Vincenzo Antonucci

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 196908-196919
Author(s):  
Emad Hadian ◽  
Hamidreza Akbari ◽  
Mehdi Farzinfar ◽  
Seyedamin Saeed

2021 ◽  
Vol 335 ◽  
pp. 02008
Author(s):  
Kameswara Satya Prakash Oruganti ◽  
Chockalingam Aravind Vaithilingam ◽  
Agileswari Ramasamy ◽  
Gowthamraj Rajendran

The solar carport is a significant technology-oriented infrastructural concept for facilitating electric vehicle charging stations (EVCS). The EVCS predominantly utilise the onsite solar photovoltaic energy for the charging of EVs. Moreover, EVCS can act as multipurpose CS to enable Grid to Vehicle (G2V) and Vehicle to Grid(V2G). Photovoltaic Electric vehicle charging station (PEVCS) can feed both EVs, traditional consumer loads, and can also feed power to the grid. Thus, enabling PEVCs across the various organisations and institutions can meet the local as well as dynamic demands incurred during charging of EVs. In this paper, a detailed economic and system analysis for the PEVCS is carried out using PVSyst and Helioscope for the area planning and shadow analysis. The normalised results of PEVCS is analysed along with the payback period and life cycle emissions are calculated for a virtual case study in Taylor’s University. At the end of the 25th year, based on the analysis, the overall payback and revenue for 25 years is 2,653.6 kMYR will be generated by selling energy at 0.58 MYR / kWh.


Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek

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.


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