This thesis investigates the benefits of conducting a computational risk assessment to comprehensively explore the scenarios arising from the integration of road and power infrastructures with hybrid fleets of Electric Vehicles (EVs) and Internal Combustion Vehicles (ICVs). The assessment relies on the Simulation-Based Probabilistic Risk Assessment (SIMPRA) method that requires the development of the simulator, the scheduler, and the planner. The planner models the engineering knowledge of the system by means of an Event Sequence Diagram (ESD); the scheduler aims to adaptively guide the simulation through the ESD finding the failure scenarios, ultimately simulated with the simulator. The application of SIMPRA is exemplified on a road infrastructure in New York State, traveled by a blended fleet of EVs and ICVs with different EVs penetration levels, during accidental scenarios of different magnitudes; an IEEE 14 buses power infrastructure is integrated with the road infrastructure for satisfying the energy demand of the EVs. The results show the capability of SIMPRA in identifying the events that bear the largest vehicle travel time and vehicle delays, i.e., the events exposing most the road-power infrastructure to disruptions.
Questa tesi investiga i benefici derivanti dalla conduzione di una valutazione computazionale dei rischi per esplorare esaustivamente gli scenari derivanti dall'integrazione delle infrastrutture stradali ed energetiche con flotte ibride di veicoli elettrici (EVs) e veicoli a combustione interna (ICVs). La valutazione si basa sul metodo della Simulation-based Probabilistic Risk Assessment (SIMPRA), che richiede lo sviluppo di tre moduli: il simulatore, il programmatore e il pianificatore. Il pianificatore modella la conoscenza ingegneristica del sistema mediante un Event Sequence Diagram (ESD); il programmatore mira a guidare adattivamente la simulazione attraverso l' ESD trovando gli scenari di fallimento, ultimamente simulati con il simulatore. L'applicazione del SIMPRA è esemplificata su un'infrastruttura stradale nello stato di New York, percorsa da una flotta mista di EVs e ICVs con diversi livelli di penetrazione degli EVs, durante scenari accidentali di diverse intensità; un'infrastruttura energetica di 14 bus IEEE è integrata con l'infrastruttura stradale per soddisfare la domanda di energia degli EVs. I risultati mostrano la capacità del SIMPRA di identificare gli eventi che comportano il maggior tempo di percorrenza dei veicoli e ritardi dei veicoli, ossia gli eventi che espongono maggiormente l'infrastruttura stradale-energetica a criticità.
Simulation-based probabilistic risk assessment (SIMPRA) of integrated road-power infrastructures with hybrid fleets of EVs and ICVs
Casucci, Vittorio
2022/2023
Abstract
This thesis investigates the benefits of conducting a computational risk assessment to comprehensively explore the scenarios arising from the integration of road and power infrastructures with hybrid fleets of Electric Vehicles (EVs) and Internal Combustion Vehicles (ICVs). The assessment relies on the Simulation-Based Probabilistic Risk Assessment (SIMPRA) method that requires the development of the simulator, the scheduler, and the planner. The planner models the engineering knowledge of the system by means of an Event Sequence Diagram (ESD); the scheduler aims to adaptively guide the simulation through the ESD finding the failure scenarios, ultimately simulated with the simulator. The application of SIMPRA is exemplified on a road infrastructure in New York State, traveled by a blended fleet of EVs and ICVs with different EVs penetration levels, during accidental scenarios of different magnitudes; an IEEE 14 buses power infrastructure is integrated with the road infrastructure for satisfying the energy demand of the EVs. The results show the capability of SIMPRA in identifying the events that bear the largest vehicle travel time and vehicle delays, i.e., the events exposing most the road-power infrastructure to disruptions.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/218777