Electric Vehicles Charging Control based on Future Internet Generic Enablers

In this paper a rationale for the deployment of Future Internet based applications in the field of Electric Vehicles (EVs) smart charging is presented. The focus is on the Connected Device Interface (CDI) Generic Enabler (GE) and the Network Information and Controller (NetIC) GE, which are recognized to have a potential impact on the charging control problem and the configuration of communications networks within reconfigurable clusters of charging points. The CDI GE can be used for capturing the driver feedback in terms of Quality of Experience (QoE) in those situations where the charging power is abruptly limited as a consequence of short term grid needs, like the shedding action asked by the Transmission System Operator to the Distribution System Operator aimed at clearing networks contingencies due to the loss of a transmission line or large wind power fluctuations. The NetIC GE can be used when a master Electric Vehicle Supply Equipment (EVSE) hosts the Load Area Controller, responsible for managing simultaneous charging sessions within a given Load Area (LA); the reconfiguration of distribution grid topology results in shift of EVSEs among LAs, then reallocation of slave EVSEs is needed. Involved actors, equipment, communications and processes are identified through the standardized framework provided by the Smart Grid Architecture Model (SGAM).Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

Distributed workload control for federated service discovery

The diffusion of the internet paradigm in each aspect of human life continuously fosters the widespread of new technologies and related services. In the Future Internet scenario, where 5G telecommunication facilities will interact with the internet of things world, analyzing in real time big amounts of data to feed a potential infinite set of services belonging to different administrative domains, the role of a federated service discovery will become crucial. In this paper the authors propose a distributed workload control algorithm to handle efficiently the service discovery requests, with the aim of minimizing the overall latencies experienced by the requesting user agents. The authors propose an algorithm based on the Wardrop equilibrium, which is a gametheoretical concept, applied to the federated service discovery domain. The proposed solution has been implemented and its performance has been assessed adopting different network topologies and metrics. An open source simulation environment has been created allowing other researchers to test the proposed solution

Decentralised Model Predictive Control of Electric Vehicles Charging

This paper presents a decentralised control strategy for the management of simultaneous charging sessions of electric vehicles. The proposed approach is based on the model predictive control methodology and the Lagrangian decomposition of the constrained optimization problem which is solved at each sampling time. This strategy allows the computation of the charging profiles in a decentralised way, with limited information exchange between the electric vehicles. The simulation results show the potential of the proposed approach in relation to the problem of shaving the aggregated power withdrawal from the electricity distribution grid, while still satisfying drivers’ preferences for charging

Decentralized Model Predictive Control of Plug-in Electric Vehicles Charging based on the Alternating Direction Method of Multipliers

This paper presents a decentralized Model Predictive Control (MPC) for Plug-in Electric Vehicles (PEVs) charging, in presence of both network and drivers' requirements. The open loop optimal control problem at the basis of MPC is modeled as a consesus with regularization optimization problem and solved by means of the decentralized Alternating Direction Method of Multipliers (ADMM). Simulations performed on a realistic test case show the potential of the proposed control approach and allow to provide a preliminary evaluation of the compatibility between the required computational effort and the application in real time charging control system

Electric vehicles charging load reprofiling

This paper presents a reference architecture and a control scheme for the aggregation and management of electric vehicle (EV) load at medium voltage level. The focus is put on the problem of EV load reprofiling, aimed at the procurement of active demand (AD) services to interested grid/market actors. The proposed approach achieves AD product composition always guaranteeing the respect of grid constraints as well as user constraints on the charging processes. Simulations are presented to illustrate the effectiveness of the proposed approach. © 2014 IEEE