Giovanni Sansavini


Last Name

Sansavini

First Name

Giovanni

ORCID

0000-0002-8801-9667

Organisational unit

09452 - Sansavini, Giovanni / Sansavini, Giovanni

Search Results

Publications 1 - 10 of 262
  • Resilience analysis of cyber‐physical systems: A review of models and methods
    Item type: Journal Article
    Cassottana, Beatrice; Roomi, Muhammad M.; Mashima, Daisuke; et al. (2023)
    Risk Analysis
    Cyber-physical systems (CPSs) are monitored and controlled by a computing andcommunicating core. This cyber layer enables better management of the controlledsubsystem, but it also introduces threats to the security and protection of CPSs, asdemonstrated by recent cyberattacks. The resulting governance and policy emphasison cybersecurity is reflected in the academia by a vast body of literature. In this arti-cle, we systematize existing knowledge on CPS analysis. Specifically, we focus onthe quantitative assessment of CPSs before and after the occurrence of a disruption.Through the systematic analysis of the models and methods adopted in the literature,we develop a CPS resilience assessment framework consisting of three steps, namely,(1) CPS description, (2) disruption scenario identification, and (3) resilience strategyselection. For each step of the framework, we suggest established methods for CPSanalysis and suggest four criteria for method selection. The framework proposes a stan-dardized workflow to assess the resilience of CPSs before and after the occurrence of adisruption. The application of the proposed framework is exemplified with reference toa power substation and associated communication network.The case study shows thatthe proposed framework supports resilience decision making by quantifying the effectsof the implementation of resilience strategies.
  • Multi-level Informed Optimization for Design under Uncertainties
    Item type: Other Conference Item
    Ampellio, Enrico; Gabrielli, Paolo; Gjorgiev, Blazhe; et al. (2024)
  • Data-driven modeling for long-term electricity price forecasting
    Item type: Journal Article
    Gabrielli, Paolo; Wüthrich, Moritz; Blume, Steffen; et al. (2022)
    Energy
    Estimating the financial viability of renewable energy investments requires the availability of long-term, finely-resolved electricity prices over the investment lifespan. This entails, however, two major challenges: (i) the combination of extensive time horizons and fine time resolutions, and (ii) the prediction of out-of-sample electricity prices in future energy and market scenarios, or shifts in pricing regime, that were not observed in the past. This paper tackles such challenges by proposing a data-driven model for the long-term prediction of electricity market prices that is based on Fourier analysis. The electricity price is decomposed into components leading to its base evolution, which are described through the amplitudes of the main frequencies of the Fourier series, and components leading to high price volatility, which are described by the residual frequencies. The former are predicted via a regression model that uses as input annual values of relevant energy and market quantities, such as electricity generation, prices and demands. The proposed method shows capable of (i) predicting the most relevant dynamics of the electricity price; (ii) generalization by capturing the market mechanisms of previously unseen electricity markets. These findings support the relevance and validity of data-driven, finely-resolved, long-term predictions and highlight the potential for hybrid data-driven and market-based models.
  • Emergence of Antifragility by Optimum Postdisruption Restoration Planning of Infrastructure Networks
    Item type: Journal Article
    Fang, Yiping; Sansavini, Giovanni (2017)
    Journal of Infrastructure Systems
  • Optimization and assessment of carbon capture, transport and storage supply chains for industrial sectors: The cost of resilience
    Item type: Journal Article
    Gabrielli, Paolo; Campos, Jordi; Becattini, Viola; et al. (2022)
    International Journal of Greenhouse Gas Control
    This study investigates the optimal design of carbon capture, transport and storage (CCTS) supply chains for decarbonizing industrial emitters. It builds upon previous analyses, which determine the cost-optimal design of CCTS supply chains while complying with specified emissions reduction scenarios, and determines optimal designs in terms of minimum cost and maximum resilience. The resilience of a supply chain is defined as its ability to permanently store the captured CO2 during the time horizon of interest, and it is quantified in terms of expected amount of carbon not stored under a fixed number of possible simultaneous failures. A mixed-integer linear program is developed to design CCTS supply chains that ensure a specified level of resilience while minimizing total system costs and CO2 emissions. The model is illustrated by determining the optimal decarbonization strategy in terms of costs and level of resilience for the Swiss waste-to-energy sector from 2025 to 2050. Overall, resilience is achieved with a cost increase with respect to the cost-optimal solution ranging from about 5% (backup truck connections to minimize the cost of the supply chain) to about 70% (backup pipeline connections to minimize the emissions of the supply chain) when the storage site is in the North Sea. When the storage site is available in Switzerland, the cost increase is much reduced and ranges from about 1% to 10% with respect to the cost-optimal solution.
  • Resilience of carbon capture, transport, and storage infrastructure: Trade-offs between cost and emissions
    Item type: Other Conference Item
    Burger, Johannes; Shu, David Yang; Bardow, André; et al. (2024)
  • Trading off vulnerability and recoverability in network resilience
    Item type: Other Conference Item
    Barker, Kash; Sansavini, Giovanni (2017)
  • Restorative Capacity Optimization for Complex Infrastructure Networks
    Item type: Journal Article
    Morshedlou, Nazanin; Barker, Kash; Sansavini, Giovanni (2019)
    IEEE Systems Journal
  • Funplex: A Modified Simplex Algorithm to Efficiently Explore Near-Optimal Spaces
    Item type: Other Conference Item
    Brodnicke, Linda; Funke, Christoph; Lombardi, Francesco; et al. (2024)
    2024 INFORMS Annual Meeting - Program Book
  • Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities
    Item type: Journal Article
    Sun, Li; Stojadinovic, Bozidar; Sansavini, Giovanni (2019)
    Risk Analysis
Publications 1 - 10 of 262