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Določitev vpliva električnih vozil na distribucijsko omrežje s pomočjo Monte Carlo simulacij
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Novak, Nejc
(
Author
),
ID
Blažič, Boštjan
(
Mentor
)
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Abstract
V magistrski nalogi je opisana simulacija distribucijskega omrežja z Monte Carlo metodo, katero smo uporabili zaradi stohastične narave bremen in nepredvidljivosti polnjenja električnih vozil. Moči bremen za vsak posamezen interval smo predstavili z verjetnostnimi funkcijami. Podobno smo storili tudi za čas začetka polnjenja EV in dolžino polnjenja EV. V vsakem koraku Monte Carlo simulacije smo določili čas začetka in dolžino polnjenja vsakega posameznega EV iz verjetnostnih funkcij. Generirali smo naključno število in določili moči bremen v tistem koraku za vsak posamezen interval. Prebrali smo moč polnjenja EV za posamezen časovni interval ter izvedli izračun pretokov moči. Rezultat simulacije sta bili verjetnostni funkciji napetosti in pretok moči.
Language:
Slovenian
Keywords:
distribucijska omrežja
,
Monte Carlo simulacija
,
gostota verjetnosti
,
polnjenje EV
,
vpliv polnjenja EV na omrežje
Work type:
Master's thesis/paper
Organization:
FE - Faculty of Electrical Engineering
Year:
2019
PID:
20.500.12556/RUL-108772
Publication date in RUL:
22.07.2019
Views:
2324
Downloads:
298
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NOVAK, Nejc, 2019,
Določitev vpliva električnih vozil na distribucijsko omrežje s pomočjo Monte Carlo simulacij
[online]. Master’s thesis. [Accessed 13 June 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=108772
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Title:
Determination of the impact of electric vehicles on a distribution network using Monte Carlo simulations
Abstract:
The Master thesis proposes a simulation of the distribution system with Monte Carlo method. We used this method because of the stochastic nature of loads and unpredictability of EV charging. The power of loads of every time interval was presented with probability functions. EV’s charging start time and charging time was also presented with PDF. In every Monte Carlo step, we determined the charging start time and charging time for every EV from PDF. We created a random number and determined the power of loads in that step for every time interval. We read the power of EV charging and ran the power flow calculation. As a result of the simulation, we got probability functions of voltages at the nodes and power flow across the transformer.
Keywords:
distribution system
,
Monte Carlo simulation
,
probability density function
,
EV charging
,
impact of EV charging
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