arXiv subjects

Alice Di Bella

Publications and source records attributed to Alice Di Bella.

6 recordsLinked to original sources

arXiv2026

EU-ETS under attack? The impact of carbon price suppression on the decarbonization of the power sector

European countries are debating policies to mitigate the increased energy costs caused by renewed geopolitical tensions, while pursuing decarbonization and electrification. A notable example is Italy's 2026 Decreto Bollette package, which proposes to remove the carbon price equivalent from the bids of certain gas-driven power plants to wholesale electricity markets, among other provisions. We use this as a case study to assess the long-term implications of suppressing the carbon price signal in the electricity market for investment, emissions, and consumer costs. We employ a stylized Italian power system using MARLEY, a multi-agent reinforcement learning framework focused on long-term electricity market assessments. In this framework, we test this policy across configurations with varying levels of support for green investment, resource adequacy, and flexibility. Results show that partial suppression of the carbon price signal yields short-term cost reductions but only a minor long-term effect on total system costs, as the deferred emissions are ultimately repaid by consumers. CO$_2$ emissions rise across most configurations since suppressing the price signal erodes incentives for renewable and storage investment. Only the most ambitious configurations for supporting green investment avoid this outcome, but they do so by marginalizing the wholesale price signal itself, thereby requiring a commitment to a hybrid market paradigm that is in contradiction with the rationale of the proposed price intervention.

econ.GN↗

arXiv2025

Assessing Long-Term Electricity Market Design for Ambitious Decarbonization Targets using Multi-Agent Reinforcement Learning

Electricity systems are key to transforming today's society into a carbon-free economy. Long-term electricity market mechanisms, including auctions, support schemes, and other policy instruments, are critical in shaping the electricity generation mix. In light of the need for more advanced tools to support policymakers and other stakeholders in designing, testing, and evaluating long-term markets, this work presents a multi-agent reinforcement learning model capable of capturing the key features of decarbonizing energy systems. Profit-maximizing generation companies make investment decisions in the wholesale electricity market, responding to system needs, competitive dynamics, and policy signals. The model employs independent proximal policy optimization, which was selected for suitability to the decentralized and competitive environment. Nevertheless, given the inherent challenges of independent learning in multi-agent settings, an extensive hyperparameter search ensures that decentralized training yields market outcomes consistent with competitive behavior. The model is applied to a stylized version of the Italian electricity system and tested under varying levels of competition, market designs, and policy scenarios. Results highlight the critical role of market design for decarbonizing the electricity sector and avoiding price volatility. The proposed framework allows assessing long-term electricity markets in which multiple policy and market mechanisms interact simultaneously, with market participants responding and adapting to decarbonization pathways.

cs.LG↗

arXiv2025

Pursuing decarbonization and competitiveness: a narrow corridor for European green industrial transformation

This study analyzes how Europe can decarbonize its industrial sector while remaining competitive. Using the open-source model PyPSA-Eur, it examines key energy- and emission-intensive industries, including steel, cement, methanol, ammonia, and high-value chemicals. Two development paths are explored: a continued decline in industrial activity and a reindustrialization driven by competitiveness policies. The analysis assesses cost gaps between European green products and lower-cost imports, and evaluates strategies such as intra-European relocation, selective imports of green intermediates, and targeted subsidies. Results show that deep industrial decarbonization is technically feasible, led by electrification, but competitiveness depends strongly on policy choices. Imports of green intermediates can lower costs while preserving jobs and production, whereas broad subsidies are economically unsustainable. Effective policy should focus support on sectors like ammonia and steel finishing while maintaining current production levels.

physics.soc-ph↗

arXiv2024

Ensuring resilience to extreme weather events increases the ambition of mitigation scenarios on solar power and storage uptake: a study on the Italian power system

This study explores compounding impacts of climate change on power system's load and generation, emphasising the need to integrate adaptation and mitigation strategies into investment planning. We combine existing and novel empirical evidence to model impacts on: i) air-conditioning demand; ii) thermal power outages; iii) hydro-power generation shortages. Using a power dispatch and capacity expansion model, we analyse the Italian power system's response to these climate impacts in 2030, integrating mitigation targets and optimising for cost-efficiency at an hourly resolution. We outline different meteorological scenarios to explore the impacts of both average climatic changes and the intensification of extreme weather events. We find that addressing extreme weather in power system planning will require an extra 5-8 GW of photovoltaic (PV) capacity, on top of the 50 GW of the additional solar PV capacity required by the mitigation target alone. Despite the higher initial investments, we find that the adoption of renewable technologies, especially PV, alleviates the power system's vulnerability to climate change and extreme weather events. Furthermore, enhancing short-term storage with lithium-ion batteries is crucial to counterbalance the reduced availability of dispatchable hydro generation.

physics.soc-ph↗

arXiv2023

Power system investment optimization to identify carbon neutrality scenarios for Italy

In 2021, the European Commission has adopted the Fit-for-55 policy package, legally binding European countries to reduce their CO2 emissions by 55% with respect to 1990, a first step to achieve carbon neutrality in 2050. In this context, it is crucial to help national policymakers to choose the most appropriate technologies to achieve these goals and energy system modelling can be a valuable tool. This article presents a model of the Italian power system realized employing the open energy modelling framework Oemof. A Linear Programming Optimization is implemented to evaluate how to minimise system costs at decreasing CO2 emissions in 2030. The developed tool is applied to evaluate different research questions: i) pathway towards full decarbonization and power self-sufficiency of the electricity sector in Italy, ii) relevance of flexibility assets in power grids: li-ion batteries, hydrogen storage and transmission lines reinforcement. A 55% CO2 emissions reduction for the actual Italian power sector can be achieved through an increase of 30% of the total annual system cost. Full decarbonization can be reached with four times today's annual costs, which could be lowered with sector coupling and considering more technologies.

physics.soc-ph↗

arXiv2022

Demand-side policies for power generation in response to the energy crisis: a model analysis for Italy

In order to mitigate the impacts of the energy crise, the European Union has proposed various measures. For the power sector a directive prescribes a shift of 5% of the demand in 10% of the peak hours, plus a voluntary 10% overall demand reduction. Here we use a power system model to quantify the implications of this policy for the Italian power sector, as it stands today and under the transformation required to meet the climate goals of the Fit-for-55. We find that policymakers would need to incentivize electricity consumption in the middle of the day while discouraging it in the early morning and late afternoon. We also highlight the benefits of the decarbonization strategy in the context of uncertain gas prices: for a gas price at or above 50 euro/MWh, power generation through gas is reduced by more than one third, approaching what needed to comply with the Fit-for-55. Finally, we quantify the value of demand side management strategies to curb fossil resource consumption and to reduce curtailed electricity under a high renewable scenario.

physics.soc-ph↗