Tesi etd-09132024-104928 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
LOIACONO, LUCA DOMENICO
URN
etd-09132024-104928
Titolo
Detection of Undeclared EV Charging Events to Counteract the Off-shoring of Emissions
Dipartimento
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Corso di studi
INGEGNERIA GESTIONALE
Relatori
relatore Prof. Crisostomi, Emanuele
supervisore Prof. Shorten, Robert
supervisore Prof. Quinn, Anthony
supervisore Prof. Shorten, Robert
supervisore Prof. Quinn, Anthony
Parole chiave
- Bayesian hypothesis testing.
- Electric vehicle (EV)
- Global positioning system (GPS)
- Green energy certification
- Incentivization scheme
- Off-shoring
- SUMO
- Undeclared EV charging
Data inizio appello
02/10/2024
Consultabilità
Non consultabile
Data di rilascio
02/10/2094
Riassunto
The green potential of electric vehicles (EVs) can only be realized if they are charged using energy from renewable sources. However, for economic or logistical reasons, EV owners may avoid certified green charging stations and choose conventional ones that use non-renewable energy, leading to "off-shoring" emissions to regions with lax regulations. To address this, a detection mechanism is proposed for undeclared charging events outside certified stations. The method uses a Bayesian algorithm that analyses GPS data to evaluate energy usage. By identifying discrepancies in expected energy consumption, the algorithm detects undeclared charging events, helping ensure EVs are charged with renewable energy and supporting sustainable transportation practices.
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