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Τhe multiobjective analysis of the users charging behaviour of the electric vehicle in the city of Chania.

Rouvalis Nikolaos

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Summary

This thesis is a case study of Beijing's research on the city of Chania and investigates the effect of electric vehicle (EV) charging behaviour on grid load. A stochastic nonlinear programming model is used, consisting of Monte Carlo simulation, probability density functions (PDFs) , overall maximized Y and a heuristic search algorithm for optimal parameter configuration. From the analysis of historical movement data, the probability density functions are fitted to generate the models of movement patterns. Monte Carlo simulation is adopted to simulate the movement and charging of EVs at a large scale using the probability density functions and considering the different charging behaviors, the battery characteristics of EVs and charging stations, and the scale of EVs. The simulations produced results, of large scale EVs movement and charging under different charging strategies, for future growth in electricity load demand, charging costs and ensuring mobility from EVs use, informing both electricity suppliers and EV users of this transition so that they can prepare appropriately. Comparing the evaluation indicators of the four different charging strategies, the multi-target charging strategy is more appropriate than the single-target strategies. Importantly, it ensures the accuracy of load demand forecasting, and compared to other models, it identifies the optimal periods for autonomous charging behaviors, without having a direct communication relationship between the grid and the EV. This thesis can be an encouragement for further research in the field of electric vehicles (EVs) through the use of Monte Carlo simulations to analyze different types of EVs and periods (e.g. outages), as well as their connection modes to the real grid. In addition, it is proposed to conduct further research on the statistical analysis of EV access to distributed grid nodes in order to generate insights on how to implement the proposed methods in local distribution networks. This analysis can provide insights into the advantages and limitations of access and use of EVs in different types of networks, offering guidelines for optimizing the implementation of EVs in everyday transportation.

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