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The deployment of EVs leads to a shift of the demand from transport to the power sector. This paper shows that in order to perform a realistic evaluation of the EVs integration impacts on a power system, the future developments in the increase of interconnection capacities should be taken into account. For this, three different charging scenarios are developed and tested using a North-Western Europe...
The driving patterns characterizing electric vehicles (EVs) are stochastic and, as a consequence, the electrical load due to EVs inherits their randomness. This paper presents a Monte Carlo procedure for the derivation of load due to EVs based on a fully stochastic method for modeling transportation patterns. Under the uncontrolled domestic charging scenario three variables are found to be crucial:...
This paper presents a Monte Carlo simulation approach for the modeling of the power demand of electric vehicles under the scenario of uncontrolled domestic charging. A detailed transportation dataset for the Netherlands is used to derive the stochastic characteristics of the behavior of vehicles. The stochastic variables are the start/end-time of each trip and the respective travelled distance while...
This paper presents the advantages of using wind speed time series models from ARMA-GARCH class. The models are found using good statistical practice and are able to capture the most important characteristics of the data like distribution, time dependence structure and periodicity in a satisfying manner. It is shown that the models offer several crucial advantages. The artificial wind speeds simulated...
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