European policymakers face pressing imperatives: decarbonizing electricity generation,ensuring system reliability, and safeguarding energy sovereignty. These challenges have renewed interest in nuclear deployments. This study supports reactor design decision-making in Europe by applying a Multi-Criteria Decision Analysis (MCDA) framework to evaluate mature and near-commercial technologies.Decision-support problems are inherently uncertain, stemming not only from uncertainties in input data but also from the subjectivity of preferences. To address these uncertain-ties, this thesis develops the Uncertainty Propagated MAVT (UP-MAVT) method, which systematically propagates all uncertain variables within a Multi Attribute Value Theory(MAVT) framework. This framework serves as a building block due to its mathematical simplicity and explicit structure, facilitating the integration of uncertainty across all components. The objective of UP-MAVT is to propagate uncertainties in input data,subjective information, and preferences to the final results, yielding more transparent decision support.The elicitation process combined well-established and state-of-the-art methods, with improvements introduced for uncertainty characterization in the former. To streamline the process, which was based on expert interviews, digital tools were developed to support elicitation through interactive graphical interfaces.The analysis adopts the perspective of governmental energy policy and planning agencies tasked with selecting a reactor design for mid-2030s deployment. It compares three traditional large reactors and three Small Modular Reactors (SMRs), repeating the assessment for four European countries with distinct energy requirements. Results reveal a consistent preference for traditional large reactors over emerging SMRs, regardless of national context. These findings underscore the challenges facing SMR adoption, primarily due to scepticism over their unproven operational track record.
I responsabili delle politiche energetiche europee devono affrontare sfide urgenti: ridurrele emissioni nella produzione di energia elettrica, garantire la stabilità della rete e assicurare l’indipendenza energetica. Queste esigenze hanno riacceso l’interesse verso l’energia nucleare. Questo studio offre un supporto alle decisioni sulla scelta dei reattori in Europa, applicando un metodo MCDA per valutare tecnologie già consolidate o in fase di commercializzazione. I processi decisionali sono per loro natura incerti, sia a causa dell’incertezza dei dati iniziali sia della soggettività delle preferenze. Per gestire queste incertezze, la tesi propone il metodo UP-MAVT, che analizza sistematicamente tutte le variabili incerte all’interno di un modello MAVT. Tale modello, grazie alla sua struttura chiara e matematicamente semplice, permette di integrare l’incertezza in ogni suo componente. L’obiettivo è propagare le incertezze fino ai risultati finali, rendendo il supporto decisionale più trasparente.Per raccogliere le preferenze degli esperti, sono stati combinati metodi tradizionali e innovativi, migliorando in particolare la valutazione dell’incertezza. Per semplificare il processo, basato su interviste a specialisti del settore, sono stati sviluppati strumenti digitali con interfacce interattive. Lo studio si pone dal punto di vista delle istituzioni pubbliche incaricate di pianificare le politiche energetiche e di selezionare un design di reattore da avviare a metà degli anni Trenta. L’analisi confronta tre reattori tradizionali di grande potenza e tre SMR, ripetendo la valutazione in quattro paesi europei con fabbisogni energetici diversi. I risultati mostrano una netta preferenza per i reattori tradizionali rispetto agli SMR, indipendentemente dal contesto nazionale. Questo orientamento riflette le difficoltà che gli SMR incontrano nel guadagnare fiducia, soprattutto per la mancanza di una comprovata esperienza operativa.
Evaluating nuclear reactor designs for deployment in Europe: a multi-criteria decision support framework with uncertainty propagation
Pagliuca, Simone
2025/2026
Abstract
European policymakers face pressing imperatives: decarbonizing electricity generation,ensuring system reliability, and safeguarding energy sovereignty. These challenges have renewed interest in nuclear deployments. This study supports reactor design decision-making in Europe by applying a Multi-Criteria Decision Analysis (MCDA) framework to evaluate mature and near-commercial technologies.Decision-support problems are inherently uncertain, stemming not only from uncertainties in input data but also from the subjectivity of preferences. To address these uncertain-ties, this thesis develops the Uncertainty Propagated MAVT (UP-MAVT) method, which systematically propagates all uncertain variables within a Multi Attribute Value Theory(MAVT) framework. This framework serves as a building block due to its mathematical simplicity and explicit structure, facilitating the integration of uncertainty across all components. The objective of UP-MAVT is to propagate uncertainties in input data,subjective information, and preferences to the final results, yielding more transparent decision support.The elicitation process combined well-established and state-of-the-art methods, with improvements introduced for uncertainty characterization in the former. To streamline the process, which was based on expert interviews, digital tools were developed to support elicitation through interactive graphical interfaces.The analysis adopts the perspective of governmental energy policy and planning agencies tasked with selecting a reactor design for mid-2030s deployment. It compares three traditional large reactors and three Small Modular Reactors (SMRs), repeating the assessment for four European countries with distinct energy requirements. Results reveal a consistent preference for traditional large reactors over emerging SMRs, regardless of national context. These findings underscore the challenges facing SMR adoption, primarily due to scepticism over their unproven operational track record.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/250657