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Stochastic Modeling and Forecasting of Load Demand for Electric Bus Battery-Swap Station

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Electric-vehicle (EV) battery-swap stations (BSSs)
have become important infrastructures for the development of
EVs to extend their driving range. Due to the randomness of
batteries’ swapping and charging patterns, the load demand of
the BSS has a stochastic nature. It is necessary to investigate the
charging load characteristics of BSS to guide the coordinated
battery charging for mitigating the impact of disorderly charging
behaviors on the distribution network. Under the uncontrolled
swapping and charging scenario, four variables are essential: 1)
hourly number of EVs for battery swapping; 2) the charging start
time; 3) the travel distance; and 4) the charging duration. Taking
these factors into account, a novel model based on Monte Carlo
simulation is presented to estimate uncontrolled energy consumption of the BSS. Then, a generic nonparametric method for the
estimation of prediction uncertainty of charging load demand is
introduced. Adopting an actual typical BSS as an example, the
simulation results show that the proposed prediction methods of
the BSS charging load and probabilistic interval are suitable for
forecasting the horizon 24 h ahead.

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Ketersediaan

EJ20285

My Library

Tersedia

Informasi Detil

Judul Seri

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No. Panggil

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Penerbit

IEEE TRANSACTIONS ON POWER DELIVERY : ., 2014

Deskripsi Fisik

9 p.

Bahasa

English

ISBN/ISSN

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Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

online resource

Edisi

VOL. 29, NO. 4, AUGUST 2014

Subyek

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Info Detil Spesifik

Ejurnal

Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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