Electric vehicles are potential for electrifying traffic due to their effectiveness, environmental friendliness, and cleanliness Not only do electric cars (EVs) provide substantial loads for the electricity grid, but they are also essential to traffic flow. EVs can be used as a flexible resource for grid scheduling. User behaviour affects when EVs travel, and there is a clear bimodal pattern to this. EV usage is highest in the morning and evening, particularly for commuting between homes and places of employment. Their charging and travel patterns affect the road network as well as the electrical grid. In order to address the possible effects of the broad adoption of EVs on the power grid and the aggravation of traffic congestion, the article first builds a dynamic road network strategy. It accomplishes this by utilising road impedance methods, time-varying traffic data, and graph theory. The research's suggested approach can reduce the strain on the local power grid by achieving a more balanced spatiotemporal distribution of charging demand. The 7% safety barrier for power supply voltage loss brought on by an electric vehicle's charging behaviour can be reached using this technique.


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    Title :

    Real-time Traffic and Traffic Flow Prediction using Machine Learning Algorithm for Optimal Route Planning in Electric Vehicles


    Contributors:


    Publication date :

    2024-11-15


    Size :

    383506 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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