Giovanni Sansavini

• ETH Zurich

The high volume of user-generated content in social networks and online platforms facilitates instant access to a substantial amount of data. However, users’ inability to validate and verify the content of online information exacerbates the spread of false and misleading information. Engagement with disinformation can result in inaccurate judgment...

Many data clustering applications must handle objects that cannot be represented as vector data. In this context, the bag-of-vectors representation can be leveraged to describe complex objects through discrete distributions, and the Wasserstein distance can effectively measure the dissimilarity between them. Additionally, kernel methods can be used...

The availability of real power distribution grid data is often restricted due to privacy concerns and the lack of digitized representations, limiting spatially-resolved assessments of these systems. This inaccessibility has motivated the development of methods for generating synthetic grids. However, existing methods face challenges such as computa...

The growth of European wind and solar power capacity is associated with increasing electricity curtailment to manage excess generation and ensure safe network operations. Instead, this surplus electricity could be used to produce hydrogen, thereby reducing the need for fossil-fueled hydrogen production in ammonia and refining industries. Based on h...

The energy transition is reshaping electricity systems, bringing new challenges, and emphasizing the need for strategic planning. Energy policies play a crucial role in guiding this transition. However, assessing their impacts often requires robust modeling involving multiple models and going beyond a single country's scope, analyzing international...

Transitioning to net-zero emissions in hard-to-abate industries is challenging due to limited electrification options. Here, we explore cost-optimal transition pathways for European hard-to-abate industries to achieve net-zero emissions by 2050, considering existing production capacities and focusing on the strategic use of biomass, low-carbon hydr...

Short-term planning of myopic decision-makers jeopardizes the long-term energy transition, especially since constraints in deploying clean energy technologies further inhibit their rapid scale-up. Here, we show that the European energy transition followed myopic decision-making in the past and investigate how policy-based tools can secure the energ...

The energy transition is driving the integration of large shares of intermittent power sources in the electric power grid. Therefore, addressing the AC optimal power flow (AC-OPF) effectively becomes increasingly essential. The AC-OPF, which is a fundamental optimization problem in power systems, must be solved more frequently to ensure the safe an...

Food production worldwide requires ammonia-based fertilizers, but their manufacture relies heavily on fossil fuels. Ammonia is typically made by combining nitrogen and hydrogen, with hydrogen produced from methane, a powerful greenhouse gas. The European ammonia industry alone produces 36 million tons of carbon dioxide per year, largely from genera...

Low-carbon hydrogen (H2) is envisioned to play a central role in decarbonizing European hard-to-abate industries, such as refineries, ammonia, methanol, steel, and cement. To enable its widespread use, H2 supply chain (HSC) infrastructure is required. Mature and economically viable low-carbon H2 production pathways include steam methane reforming (...

The increasing integration of low-carbon technologies, such as solar photovoltaics (PV) and heat pumps, impacts the operational margins of distribution grids. This paper quantifies the margins to voltage violation and line overloading by calculating the maximum grid loadability (MGL). We quantify this metric for 873 inferred Swiss medium-voltage gr...

Modeling to generate alternatives (MGA) is an increasingly popular method in energy system optimization. MGA explores the near-optimal space, namely, system alternatives whose costs are within a certain fraction of the globally optimal cost. Real-world stakeholders may prefer these alternatives due to intangible factors. Nonetheless, widespread MGA...

Power distribution grids host an increasing amount of distributed renewable generators, electric vehicles, and heat pumps worldwide. Distribution grids, however, were not designed with the goal of incorporating large shares of these technologies. These soaring challenges demand realistic grid models to assess the need for operation strategies and r...

Accurate real-time forecasts of atmospheric plume behavior are crucial for effective management of environmental release incidents. However, the computational demands of weather simulations and particle transport codes limit their applicability during emergencies. In this study, we employ a U-Net enhanced Fourier Neural Operator (U-FNO) to statisti...

The European ammonia industry emits 36 million tons of carbon dioxide annually, primarily from steam methane reforming (SMR) hydrogen production. These emissions can be mitigated by producing hydrogen via water electrolysis using dedicated renewables with grid backup. This study investigates the impact of decarbonization targets for hydrogen synthe...

Energy decisions can be framed as questions of justice, given energy systems’ impact on climate change and communities. Researchers and policymakers have recently begun investigating how quantifying justice with metrics could be used to support decision-making; however, the implications of justice on large-scale energy infrastructure design are not...

The equations governing gas flow dynamics are computationally challenging for energy network optimization. This paper proposes an efficient solution procedure to enable tractability for an hourly resolved yearly decision horizon. The solution procedure deploys linear and second-order cone gas flow models alternatively based on the length–diameter r...

This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency re...

While critical infrastructure systems are essential for cities, their increasing interdependencies can worsen risks from external shocks, leading to disproportionate impacts on the regional economy and communities. In this study, we propose a methodological framework to identify and evaluate cost-effective pathways for enhancing resilience in large...

p>Power distribution grids host an increasing amount of distributed renewable generators, electric vehicles, and heat pumps worldwide. Distribution grids, however, were not designed with the goal of incorporating large shares of these technologies. These soaring challenges demand accurate and realistic grid models to assess the need for operation s...

p>Power distribution grids host an increasing amount of distributed renewable generators, electric vehicles, and heat pumps worldwide. Distribution grids, however, were not designed with the goal of incorporating large shares of these technologies. These soaring challenges demand accurate and realistic grid models to assess the need for operation s...

This study presents an inter-comparison of three structurally different electricity system models (EXPANSE, Nexus-e, and OREES) with sub-national spatial resolution in Switzerland in 2035. We analyze technology and regional implications of three targets for electricity generation from new renewable sources (17 to 25 TWh/year from solar PV, wind, bi...

The deployment of advanced information and communication technologies necessitates considering new security threats, such as distributed denial of service attacks and malware, which can fault power generators and feeders and exacerbate power outages in distributed generation systems (DGS). Existing cyber-security studies fail to validate the attack...

Natural disasters significantly impact energy systems and dependent critical infrastructures, causing severe human and economic losses in modern society. Given the increasing effects of climate change on both the frequency and the severity of extreme weather events, energy systems must adapt to cope with this new and evolving risk environment. In t...

We note that Eq. (7) in the original paper is wrong, namely, it contains the turbomachinery diameter, D, at the denominator instead of at the numerator

The previous chapter has presented the insights of 100 practitioners about the causes of existing problems with internal risk transmission (answers to questions I–III are presented in Sect. 2.3). The same 100 practitioners were then asked the following questions about how to improve the quality and speed of risk communication within organizations.

In 2013–2015 two of the present authors conducted the study of tens of major accidents and incidents sought to identify the reasons that prevent the transmission of relevant, clear and accurate information about risks, both within an organization (intra-organizational) and between different organizations (inter-organizational). More than 30 recurri...

Compelling evidence from industrial working practice demonstrates that in many critical infrastructure companies, decision-makers find it difficult to get objective information about safety and technological risks.

At the end of 2021, the first author of this handbook began a pilot project for an industrial company that is a world leader in its field. By agreement with this company, the following information must remain confidential and not be disclosed to the general public: the company name, the nature of its operations, the countries where it operates, the...

The chemical industry is responsible for about 5% of global CO 2 emissions and is key to achieving net-zero targets. Decarbonizing this industry, nevertheless, faces particular challenges given the widespread use of carbon-rich raw materials, the need for high-temperature heat, and the complex global value chains. Multiple technology routes are now...

Following the disruption of Russian natural gas flows to Europe, we investigate the impact of collaborative and selfish behavior of European countries to tackle energy scarcity and supply electricity, heat, and industrial gas to end users. We study how the operation of the European energy system will need to adapt to the disruption and identify opt...

Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data regime. These models serve as digital twins to generate large quantities of data to train DNNs which would otherwise be difficult to obtain from the real-life system. How...

Energy system models suggest optimal investment pathways and guide policymakers in implementing the low-carbon energy transition. Although model accuracy greatly improved over the last decade, it is unclear whether the cost of capital (CoC) is well represented, despite the parameter’s strong influence on model outcomes. In this perspective, we revi...

Critical infrastructures are more exposed than ever to natural hazards in a changing climate. To understand and manage risk, failure cascades across large, real-world infrastructure networks, and their impact on people, must be captured. Bridging established methods in both infrastructure and risk modelling communities, we develop an open-source mo...

Cyber‐physical systems (CPSs) are monitored and controlled by a computing and communicating core. This cyber layer enables better management of the controlled subsystem, but it also introduces threats to the security and protection of CPSs, as demonstrated by recent cyberattacks. The resulting governance and policy emphasis on cybersecurity is refl...

Deep learning-based object detection is a powerful approach for detecting faulty insulators in power lines. This involves training an object detection model from scratch, or fine tuning a model that is pre-trained on benchmark computer vision datasets. This approach works well with a large number of insulator images, but can result in unreliable mo...

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 minim...

The book reviews existing research on the challenges of voice and silence in organizations. After a major disaster, when investigators are piecing together the story of what happened, a striking fact often emerges: before disaster struck, some people in the organization involved were aware of dangerous conditions that had the potential to escalate...

Overhead power transmission lines are repeatedly subject to environmental fluctuations that affect their insulation. Weakened insulation allows leakage current to increase over time eventually triggering the protection and thereby causing unplanned power line outages. Current advancements in sensor technologies, data analysis, and machine learning...

Industrial heat pumps, and specifically those using carbon dioxide (CO2) as a refrigerant, can play a key role in the de-carbonization of the heating and cooling sector, due to their low global warming potential, toxicity and flammability. However, challenges arise when dealing with the modeling and optimization of CO2 heat pumps under different op...

Most cascading failure analysis methods successfully capture cascading developments within one control zone, or region comprised of multiple control zones, controlled by a single transmission system operator (TSO). They neglect, however, the operations of multi‐zonal systems. To bridge this gap, the authors introduce the multi‐zonal method for casc...

Industrial heat pumps, and specifically those using carbon dioxide (CO2) as a refrigerant, can play a key role in the decarbonization of the heating and cooling sector, due to their low global warming potential, toxicity and flammability. However, challenges arise when dealing with the modeling and optimization of CO2 heat pumps under different ope...

We propose a Bayesian inference approach for static Origin-Destination (OD)-estimation in large-scale networked transit systems. The approach finds posterior distribution estimates of the OD-coefficients, which describe the relative proportions of passengers travelling between origin and destination locations, via a Hamiltonian Monte Carlo sampling...

We propose a contractual setup, the proxy storage power purchase agreement (PPA), to foster the deployment of energy storage technologies. We define a threshold price below which the PPA becomes financially attractive for PPA buyers. We compute the threshold price for several storage technologies and configurations, in seven European countries. Suc...

Post-accident mitigation and consequence analysis have been subjects of extensive research in the nuclear industry. Strict regulatory guidelines and radiation monitoring networks are usually in place to support the prompt implementation of protective actions (evacuation, sheltering, etc.) in case of emergency. However, the Fukushima Daiichi nuclear...

This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the s...

In a world where corporate sustainability commitments are increasing, and governments are starting to phase out of renewable energy subsidy schemes, renewable power purchase agreements (PPAs) can act as a substitute to the governmental support. The combination of renewable energy projects placed in multiple locations (multi-location) and based on d...

Energy systems are transitioning toward sustainable power generation largely due to new policies that are motivated by climate and renewable generation targets. This transition is felt throughout the entire economy and is affecting the long and short term operations of the energy system. In the last decade, the research community has made significa...

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 long time horizons with fine resolutions, and (ii) the prediction of out-of-sample electricity prices in futur...

Distribution System Operators are responsible for overseeing the connection of distributed energy sources, such as solar photovoltaic, to the low voltage electricity grid. While solar PV could contribute significantly to the decarbonization of the electricity supply, the technology's proliferation is not necessarily aligned with the business object...