Viability and Optimality of Electric Vehicle Fleet Schedules

Bodenschatz, Nicki; Berl, Andreas

doi:10.1109/acitt.2019.8779983

Cited by 5 publications

(1 citation statement)

References 19 publications

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“…To benefit from this, the fleet operator would need to have optimising measures in place to minimise their total cost of electricity use. There are various methods ranging from linear programming, dynamic programming to the application of machine learning techniques that have been discussed in the literature for vehicle charging optimisations [22][23][24][25][26][27][28][29][30][31][32][33]. In what follows, it is sufficient to use a linear optimisation technique, at this stage, for the cost minimisation of fleet charging at depots, and the objective function is given as:…”

Section: Price Based Charging Optimisationmentioning

confidence: 99%

Semi-Stochastic Load Model for Heavy Goods Electric Vehicles Depot Charging Considering the Potential for Demand Side Management

Shariati

Coker

Smith

et al. 2022

2022 International Conference on Communications, Information, Electronic and Energy Systems (CIEES)

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Research and development on the electrification of road vehicles have been dominated by light-duty passenger vehicles and vans. Recent developments in Electric Vehicle (EV) technology, however, are bringing attention to the electrification of heavy-duty vehicles and raising questions about fleet charging profiles and related implications for power networks. In this paper, a semi-stochastic model is developed for the simulation of Heavy Goods Electric Vehicle (HGEV) depots' charging demand profiles. The modelling of daily fleet charging profiles, managed and unmanaged, are addressed in this paper to investigate the characteristics of the typical load profile and the potential of the demand side management in response to price signals. Issues of charging constraint and optimal depot charging, from a power network perspective, have been applied to understanding how the fleet demand is met. The findings of this work pavs the way to study the impacts of heavy-duty vehicle electrification on the network and the maximum power demanded from the grid based on the charging strategies taken. Adoption of flexibility programs or network reinforcement plans around sites of fleet charging can be informed by this study -helping to mitigate the overall stress that the grid could face due to increasing future demands.

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