EV-EcoSim: A grid-aware co-simulation platform for the design and optimization of electric vehicle charging infrastructure
IEEE Transactions on Smart Grid(2024)
摘要
To enable the electrification of transportation systems, it is important to
understand how technologies such as grid storage, solar photovoltaic systems,
and control strategies can aid the deployment of electric vehicle charging at
scale. In this work, we present EV-EcoSim, a co-simulation platform that
couples electric vehicle charging, battery systems, solar photovoltaic systems,
grid transformers, control strategies, and power distribution systems, to
perform cost quantification and analyze the impacts of electric vehicle
charging on the grid. This python-based platform can run a receding horizon
control scheme for real-time operation and a one-shot control scheme for
planning problems, with multi-timescale dynamics for different systems to
simulate realistic scenarios. We demonstrate the utility of EV-EcoSim through a
case study focused on economic evaluation of battery size to reduce electricity
costs while considering impacts of fast charging on the power distribution
grid. We present qualitative and quantitative evaluations on the battery size
in tabulated results. The tabulated results delineate the trade-offs between
candidate battery sizing solutions, providing comprehensive insights for
decision-making under uncertainty. Additionally, we demonstrate the
implications of the battery controller model fidelity on the system costs and
show that the fidelity of the battery controller can completely change
decisions made when planning an electric vehicle charging site.
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关键词
Battery storage,Control,Electric Vehicles,Fast charging,Modelling,Optimization,Simulation
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