Model-Predictive Energy Management for the Integration of Plug-In-Hybrid Electric Vehicles into Building Energy Systems 2013-01-1443
In current research projects such as "Vehicle to Grid"
(V2G), "Vehicle to Building" (V2B) or "Vehicle to
Home" (V2H), plug-in vehicles are integrated into stationary
energy systems. V2B or V2H therefore stands for intelligent
networking between vehicles and buildings. However, in these
projects the objective is mostly from a pure electric point of
view, to smooth the load profile on a household level by optimized
charging and discharging of electric vehicles. In the present paper
a small energy system of this kind, consisting of a building and a
vehicle, is investigated from a holistic point of view. Thermal as
well as electrical system components are taken into account and
there is a focus on reduction of overall energy consumption and CO₂
A predictive energy management is presented that coordinates the
integration of a plug-in hybrid electric vehicle into the energy
systems of a building. System operation is optimized in terms of
energy consumption and CO₂ emissions. A model predictive approach
is applied to the charging phases of a plug-in hybrid electric
vehicle as well as on the energy system of a building with
integrated energy generation by a cogeneration unit and a
photovoltaic system. In the present paper the energy-saving
potential for different mobility scenarios that can be achieved
through a holistic, integrative energy management is shown. The
overall primary energy demand of the energy system as described is
examined with a simulation model.
The energy management contains, in a similar way to an MPC
(Model Predictive Control) system, a model of the system dynamics.
With this model, prediction of the energy process is conducted,
based on a weather forecast and future mobility patterns. The
future development of all relevant variables is thus predicted.
Based on this, optimization of the operational management takes
place. As part of this prediction process the best operation
strategy for the manipulation of flexible system components is
determined and selected.
The energy management system optimizes and coordinates the use
of components and the energy flows within the coupled energy system
and involves the entire "well-to-wheel" chain for an
ecological system operation.
Citation: Brendle, B., Hamacher, T., Lienkamp, M., Wilhelm, C. et al., "Model-Predictive Energy Management for the Integration of Plug-In-Hybrid Electric Vehicles into Building Energy Systems," SAE Technical Paper 2013-01-1443, 2013, https://doi.org/10.4271/2013-01-1443. Download Citation
Bernhard Brendle, Thomas Hamacher, Markus Lienkamp, Christian Wilhelm, Jens Papajewski, Peter Gebhard, Alexander Riedel, Vincent Benda
Technische Universitaet Muenchen, Audi AG