Planning of EV Charging Infrastructure in Distribution Grids: a Comparison of Options
Résumé
he growing population of electric vehicles (EVs) requires the development of suitable charging infrastructure to enable EV owners to recharge their vehicles. The simultaneous charging process of many EVs results in increased power flows, possibly leading to violations of the operational constraints of distribution grids. In this context, the EV charging infrastructure should be planned while cognizant of the capability and limitations of the underlying power grid. Failing to do so might engender high grid reinforcement costs of recurrent use of smart charging to curtail the recharging actions of the EVs, ultimately under-utilizing the developed recharging infrastructure.
This report discusses cost-optimal planning of EV charging infrastructure in power distribution grids. It is considered the perspective of an integrated grid operator/urban planner wishing to attain minimum capital investments to roll out the EV charging infrastructure in a given grid. More specifically, the objective of the problem is to identify the location, rating (including fast and slow charging options), and the number of chargers in the grid to satisfy the charging demand of a given population of EVs at the minimum capital cost and while respecting the distribution grid’s constraints.
The planning model developed as a part of this research is flexible and extensible, allowing a technoeconomic comparison among different charging options and chargers’ technologies. More specifically, the compared options are slow and fast chargers, single- and multi-port chargers (SPCs and MPCs, respectively), and flexibility of the EV owners in plugging and unplugging vehicles to and from chargers. Indeed, these options might result in different charging infrastructure requirements and configurations. For example, a fast charger costs more than a slow charger, but it shortens recharging time and, for the same operation time, might serve more vehicles, thus shortening payback times. MPCs (i.e., chargers with a centralized AC/DC power conversion stage and multiple ports allowing to arbitrage the charge among the connected vehicles) might lead to increasing flexibility. Finally, increased EV owners’ flexibility (forgetful owners vs cooperative owners) could improve the utilization factor of the available charging
infrastructure, improving cost efficiency.
Results show that MPCs and flexible EV owners can achieve significantly cheaper infrastructure costs than SPCs and forgetful owners. However, these differences tend to disappear with increasing values of the energy capacity of the EV batteries (from 16 kWh to 60 kWh). The reason for this result is that larger batteries require longer recharging times. These longer recharging times lead to saturating the utilization factor of the existing charging infrastructure, ultimately resulting in nearly optimal use of the chargers; in this context, the additional flexibility coming from MPCs and EVs’ owners falls unused, bringing no additional benefit to the planning problem.
Within the context of this project (that tackles charging infrastructure for autonomous EVs), MPC chargers have been considered because they can be seen as as a first autonomous automation layer that achieves more flexibility than conventional chargers thanks to the possibility of arbitraging power flows locally. This represents a fundamental first step toward the development of more sophisticated planning algorithms for autonomous driving EVs, explaining the relevance to this project. The content of this report is based on two submitted (at the time of writing) papers of these same authors.
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