Browsing by Author "Rahman, Shahriar"

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    Finding Optimal Locations for Electric Vehicle Charging Stations Based on Genetic Algorithm
    (Department of Electrical and Electronic Engineering(EEE), Islamic University of Technology(IUT),, 2022-05-30) Nihal, Nafis Sadik; Rahman, Shahriar; Rahman, Md Atiqur
    In this day and age, environment is the main concern. And to achieve a sustainable future regarding technology, electric vehicle can be a major gateway to reduce carbon emission. In Bangladesh, electric vehicle is not prominent when it comes to transportation. There are a lot of reasons behind this. But the most important one that needs to be solves is the lack of efficient charging stations infrastructure. A charging station infrastructure provides a quintessential service which is charging in between destinations. And for that purpose, they have to be located in such a way so that, the EVs can be charged in an efficient manner. This is where the necessity of optimal locations arises. The objective of this research is pretty simple. This research offers the best locations among other important location where a charging station should be built. Recent statistics shows us that Dhaka, the capital of Bangladesh, has become the most polluted city in the world. And it is very important to reduce carbon emission in this city where EVs can be of great help. In order to solve this problem, this research takes Banani, an important part of Dhaka city as a location in order to completer the thesis. Depending on the relevant information provided, this paper first tries to build a model which calculates the distance cost .Based on that, an objective function is formulated which takes distance cost minimization as its primary concern. An optimization algorithm is used to find the best and optimum locations. The algorithm is genetic algorithm which finds the fittest solution according to the objective function and the constraints provided. This solution solves the distance cost minimization problem under the constraints of the capacity of the charging stations and the location from where the EV flow will start. Finally, after finding the results, we have crosschecked them by changing the number of vehicles, the capacity of the locations and the number of charging stations itself to have a good idea on how this research actually served its purpose.