Risk-Aware Control Approach for Decision-Making System of a Shared EVs Aggregator

Abstract

This paper proposes a risk-aware control approach intended to generate the most profitable decisions for the manager of a public fleet of electric vehicles that can interact bidirectionally with the electrical network, providing different energy services to it. Specifically, the proposed control approach is intended to generate the best charging/discharging decisions for the fleet, including car-sharing uncertainties and the desired confidence level at which the fleet operator wants to cover these uncertainties. It considers a hierarchical control structure at whose first level an economic dynamic optimization is executed, and, at whose second level, a risk-aware reference tracking of the first-level references is performed. Using this a stochastic MPC controller at the second level, whose mathematical approach has as a novelty that it extends the current methodologies in the state of the art, allowing the inclusion of the linear time-varying behavior of the dynamic system, whose constraints are also time-varying, and whose uncertainties are additive-multiplicative with non-zero mean and non-unitary variance. Finally, the approach established is tested in a hypothetical car-sharing system located in Colombia.