In this paper we consider the problem of controlling a service area hosting stations for the provisioning of the electric vehicles fast charging service, having the support of an electric energy storage system and local power production from renewables. Key aspects motivating the work are the hard temporal constraint imposed by drivers requiring the fast charging service and the impact high aggregated power withdrawal has on the economic viability of the investment for the service area operator; consequently key control requirements include a congestion level driven tracking of the charging power demand and the flattening of power flow at the point of connection of the service area to the electricity grid, while keeping stable ESS operation. These opposing control objectives, together with the uncertain nature of the power demand and production, brings to the formulation of a stochastic model predictive control problem, based on a continuous/finite-time optimal control problem, for which the explicit form of solution is determined. Simulations are presented to validate the proposed approach.
Optimal Control of a Grid-connected Service Area for Plug-in Electric Vehicles Fast Charging under uncertain Power Demand / De Santis, Emanuele; Liberati, Francesco; Di Giorgio, Alessandro. - (2022), pp. 49-55. (Intervento presentato al convegno 2022 30th Mediterranean Conference on Control and Automation (MED) tenutosi a Vouliagmeni (Greece)) [10.1109/MED54222.2022.9837148].
Optimal Control of a Grid-connected Service Area for Plug-in Electric Vehicles Fast Charging under uncertain Power Demand
De Santis, Emanuele
;Liberati, Francesco;Di Giorgio, Alessandro
2022
Abstract
In this paper we consider the problem of controlling a service area hosting stations for the provisioning of the electric vehicles fast charging service, having the support of an electric energy storage system and local power production from renewables. Key aspects motivating the work are the hard temporal constraint imposed by drivers requiring the fast charging service and the impact high aggregated power withdrawal has on the economic viability of the investment for the service area operator; consequently key control requirements include a congestion level driven tracking of the charging power demand and the flattening of power flow at the point of connection of the service area to the electricity grid, while keeping stable ESS operation. These opposing control objectives, together with the uncertain nature of the power demand and production, brings to the formulation of a stochastic model predictive control problem, based on a continuous/finite-time optimal control problem, for which the explicit form of solution is determined. Simulations are presented to validate the proposed approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.