Stochastic and Optimal Aggregation of Electric Vehicles in Smart Distribution Grids
Translated title
Stokastisk og Optimal Sammenlægning af Elbiler i Smart Distributionsnet
Author
Hu, Zheyuan
Term
4. term
Education
Publication year
2013
Submitted on
2013-05-30
Pages
110
Abstract
Denne afhandling undersøger, hvordan opladningen af mange elbiler kan koordineres (aggregeres) i et smart distributionsnet, dvs. det lokale elnet. Vi analyserer basisscenarier med elbiler for at finde driftsmæssige flaskehalse og vurdere, hvor godt nettet kan understøtte opladning. For at afspejle usikkerhed i virkeligheden modelleres kørsels- og ladeadfærd med en stokastisk (sandsynlighedsbaseret) tilgang. På baggrund af disse simulerede data optimeres ladeplaner for aggregerede elbiler, så de overholder nettets begrænsninger.
This thesis examines how to coordinate (aggregate) the charging of many electric vehicles (EVs) in a smart distribution grid, i.e., the local electricity network. We analyze baseline cases with EVs connected to identify operational bottlenecks and assess how well the grid can support EV charging. To reflect real-world uncertainty, we model drivers’ travel and charging behavior using a stochastic (probability-based) approach. Based on these simulated data, we optimize charging schedules for aggregated EVs that comply with grid constraints.
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