| Autor: |
Sattianadan, D., Umapathy, G., Karthik, S., Balaji, K. J., Narendran, M., Fernandez, S. George |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3037 Issue 1, p1-20, 20p |
| Abstrakt: |
Electric vehicles have changed the forum of transportation to a very large extent, the demand for EVs has seen an upfront rise due to a large number of reasons important among them being it is an eco-friendly way of transportation, which tries to minimize the amount of pollution caused due conventional petrol and diesel vehicles. Upon this increase in EVs among the consumers the need for the installation of public charging infrastructure has also gained momentum. While designing the EV charging station, an important parameter that gains traction among investors is the economic feasibility of designing and operating the charging station. The project aims to optimize the economic part while designing an EV CS considering the net present value that comprises various parameters like initial investment, maintenance replacement cost, etc. Some of the economic factors tend to be static (like the cost of land, initial investment, etc) and some are time-varying factors (like operational cost). While considering the economic parameters it is also necessary to counterbalance the electric demand for which renewable sources of energy plays a major role, as they tend to enhance the economic factor of EV CS. The main objective of the problem is to maximize the profit by maximizing the net present value using optimized solar energy and power from the grid. To maximize the net present value, a soft computing technique is being invoked, and here teacher and learner based algorithm is being used. The optimization algorithm tries to find the best solution for maximizing the economic part while designing EV CS, which would encourage an increase in the number of EV CS in the near future. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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