This paper illustrates the principles of Model Predictive Control (MPC) applied to control the dispatch of power to Electric Vehicle (EV) chargers in a charging station. The MPC strategy aims to determine a control signal by following a day-ahead scheduling and minimizing an economic objective function. The strategy works in closed-loop architecture. The MPC calculates an optimal charging sequence at each time step of the prediction horizon, but it applies the control signal only for the first step of the sequence, following a receding horizon strategy. The results of the MPC strategy lead to track a dayahead scheduling by considering uncertainties on the EV arrival state of charge, and generation disturbances. The MPC strategy outcomes are compared with an open-loop strategy, with the target to apply the scheduled power.
Understanding Model Predictive Control for Electric Vehicle Charging Dispatch
Diaz C.;Ruiz Fredy;
2018-01-01
Abstract
This paper illustrates the principles of Model Predictive Control (MPC) applied to control the dispatch of power to Electric Vehicle (EV) chargers in a charging station. The MPC strategy aims to determine a control signal by following a day-ahead scheduling and minimizing an economic objective function. The strategy works in closed-loop architecture. The MPC calculates an optimal charging sequence at each time step of the prediction horizon, but it applies the control signal only for the first step of the sequence, following a receding horizon strategy. The results of the MPC strategy lead to track a dayahead scheduling by considering uncertainties on the EV arrival state of charge, and generation disturbances. The MPC strategy outcomes are compared with an open-loop strategy, with the target to apply the scheduled power.File | Dimensione | Formato | |
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