Title :
Aggregate modeling and control of plug-in electric vehicles for renewable power tracking
Author :
Ebrahimi, B. ; Mohammadpour, Javad
Author_Institution :
Coll. of Eng., Univ. of Georgia, Athens, GA, USA
Abstract :
A robust strategy is proposed in this paper to control the aggregate charging power of plug-in electric vehicles (PEVs). The charging flexibility of PEVs provides the intermittent renewable power sources with control authority to cope with load fluctuations caused by the variation of grid-connected PEVs population and their instantaneous power demand. In this paper, we consider an aggregate model of PEVs power in the form of a partial differential equation (PDE). A sliding mode control is then developed for the derived PDE load model with no discretization in the spatial domain. The developed sliding mode controller operates on the real-time measurable imbalance between source and demand power. To evaluate the closed-loop response and demonstrate the controller´s robustness against PEVs population variations, a Monte Carlo simulation is performed for real driving conditions and using renewable power data.
Keywords :
Monte Carlo methods; closed loop systems; electric vehicles; partial differential equations; power grids; power system control; variable structure systems; Monte Carlo simulation; PDE; aggregate charging power; aggregate control; aggregate modeling; closed-loop response; grid-connected PEV; instantaneous power demand; intermittent renewable power sources; load fluctuations; partial differential equation; plug-in electric vehicles; renewable power tracking; robust strategy; sliding mode control; spatial domain; Aggregates; Load modeling; Mathematical model; Sociology; Statistics; Switches; Wind power generation; Automotive; Control applications; Power systems;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859169