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.
2020, 2020 28th Mediterranean Conference on Control and Automation (MED), Pages 739-745
Decentralized Model Predictive Control of Plug-in Electric Vehicles Charging based on the Alternating Direction Method of Multipliers (04b Atto di convegno in volume)
Germana Roberto, Liberati Francesco, Di Giorgio Alessandro
Gruppo di ricerca: Networked Systems