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Stochastic reserve scheduling and smart charging of Plug-In Electric Vehicles in power networks with wind power generation


E. Tiniou

Master Thesis, FS13 (10186)

In this project we investigate the potential of exploiting Plug-in Electric Vehicles (PEVs) for reserve provision, through a direct control scheme for power networks with wind generation uncertainty. We aggregate the vehicle eet and represent it as a set of virtual storage units, which is incorporated in a stochastic reserve scheduling and smart PEV charging algorithm. The overall problem is formulated as a chance constrained optimization program and it is solved using a variant of the so called scenario approach, which guarantees constraint satisfaction with a given probability. The performance of our method in terms of operational cost and reliability is evaluated via Monte Carlo simulations. The obtained solution is nally distributed to the individual vehicles and the error due to the aggregation step is quanti ed.


Type of Publication:

(12)Diploma/Master Thesis

J. Lygeros

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2013:IFA_4624
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