The spreading of battery electric vehicles (BEVs) is projected to influence the electricity system in the next years, potentially offering motivation for policies aimed at higher integration of renewable energy sources. Many Life Cycle Assessments (LCAs) regarding BEVs acknowledges the electricity generation process as one of the key drivers of LCA results. Dynamics related to the interaction between the electricity system and different additional BEVs fleet sizes could affect the electricity generation mix in a non-linear way. Also, the priority of dispatch in the market given to renewable sources could make the electricity mix vary across the months, due to seasonal variations in renewable production. The evaluation of potential environmental impacts related to the introduction in 2030 of an additional BEVs fleet in Italy calls for a consequential approach. This thesis shows how the fleet’s dimension can affect the marginal BEVs LCA impact indicators, due to the non-linear response of the electricity system to additional demands. The monthly variability within the impact indicators across the year is assessed, analysing the influence of different BEVs fleet sizes, too. Results show that Climate change indicator could present significant non-linearities, diverging of up to 40% from the reference scenario. Moreover, Minerals and metals monthly unitary impact indicator of electricity could vary up to 60% with respect to the yearly value. To appreciate the relevance of the variability associated to the use phase electricity, the yearly results are contextualised within a cradle-to-grave BEVs LCA. The variability in the related impact indicators is still relevant, showing that not considering such dynamics could lead, for the Climate change indicator, to an underestimation of up to 14 Mton of CO2eq emissions per year with respect to the reference scenario. The study could be replicated by using different energy system models or may be evaluated at various geographical scales. The provided framework could be coupled with comprehensive assessments of transport systems, in order to provide additional robustness to the support process to decision-makers.
Nei prossimi anni la diffusione di veicoli elettrici a batteria (BEVs) è destinata ad influenzare il sistema elettrico, incentivando politiche volte a una maggiore integrazione delle fonti rinnovabili. Molti studi riguardanti Life Cycle Assessments (LCAs) di BEVs riconosco il processo di produzione di energia elettrica come uno dei principali fattori che influenzano i risultati LCA. Le dinamiche relative all’interazione fra il sistema elettrico e flotte di BEVs di diverse taglie possono influenzare il mix elettrico in maniera non lineare. Inoltre, la priorità di dispacciamento di cui godono le fonti rinnovabili fa variare il mix elettrico lungo l’anno, principalmente a causa della variabilità nella produzione di tali fonti. La valutazione dei possibili impatti ambientali dovuti all’introduzione di una flotta di BEVs addizionale nel 2030 in Italia richiede un approccio di tipo consequenziale. La presente Tesi mostra come la dimensione di una flotta di BEVs possa influenzare gli impatti marginali LCA legati alla fase d’uso dei veicoli, per via della risposta non lineare del sistema elettrico. Inoltre, la variabilità mensile degli impatti potenziali lungo l’anno è valutata, analizzando anche l'influenza della taglia della flotta. I risultati, per quanto riguarda gli indicatori di impatto del Climate change, mostrano non-linearità significative e una variazione massima del 40% dallo scenario di reference. Inoltre, l’indicatore di impatto unitario della categoria Minerals and metals può variare lungo l’anno fino al 60%. Per valutare la rilevanza della variabilità associata alla fase d’uso, i risultati annuali sono contestualizzati all'interno di una LCA di tipo cradle-to-grave. Le variazioni nei relativi indicatori sono ancora rilevanti e mostrano che non considerare tali dinamiche non lineari può portare a sottostimare fino a 14 Mton di emissioni di CO2 l’anno. Il quadro metodologico fornito nello studio può essere replicato e raffinato da valutazioni più precise dei sistemi di trasporto, al fine di fornire maggiore solidità al processo di sostegno ai decision-makers
Uncertanties in battery electric vehicles (BEVs) LCA : correlation between LCI and the Italian electric system
Scaglia, Pietro
2019/2020
Abstract
The spreading of battery electric vehicles (BEVs) is projected to influence the electricity system in the next years, potentially offering motivation for policies aimed at higher integration of renewable energy sources. Many Life Cycle Assessments (LCAs) regarding BEVs acknowledges the electricity generation process as one of the key drivers of LCA results. Dynamics related to the interaction between the electricity system and different additional BEVs fleet sizes could affect the electricity generation mix in a non-linear way. Also, the priority of dispatch in the market given to renewable sources could make the electricity mix vary across the months, due to seasonal variations in renewable production. The evaluation of potential environmental impacts related to the introduction in 2030 of an additional BEVs fleet in Italy calls for a consequential approach. This thesis shows how the fleet’s dimension can affect the marginal BEVs LCA impact indicators, due to the non-linear response of the electricity system to additional demands. The monthly variability within the impact indicators across the year is assessed, analysing the influence of different BEVs fleet sizes, too. Results show that Climate change indicator could present significant non-linearities, diverging of up to 40% from the reference scenario. Moreover, Minerals and metals monthly unitary impact indicator of electricity could vary up to 60% with respect to the yearly value. To appreciate the relevance of the variability associated to the use phase electricity, the yearly results are contextualised within a cradle-to-grave BEVs LCA. The variability in the related impact indicators is still relevant, showing that not considering such dynamics could lead, for the Climate change indicator, to an underestimation of up to 14 Mton of CO2eq emissions per year with respect to the reference scenario. The study could be replicated by using different energy system models or may be evaluated at various geographical scales. The provided framework could be coupled with comprehensive assessments of transport systems, in order to provide additional robustness to the support process to decision-makers.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/169893