Reducing fossil fuel-based generation: Impact on wholesale electricity market prices in the North-Italy bidding zone

Decarbonisation policies aim at reducing fossil fuel based generation in favour of cleaner renewable energy sources. Changes in the generation mix to supply future electricity demand will require tools capable to emulate the bidding behaviour of new generation plants. Price forecasting tools lacking this feature and only based on historical data time series might soon become not satisfactory for this scope. This paper presents a methodology that, by considering hourly electricity generation offers (price, volumes) datasets, allows simulating future electricity wholesale’s prices. This is done by taking into account new generation units and the dismissing of old (coal-based) units according to the demand and generation forecasts in the European Ten Year Network Development Plan (TYNDP) 2030 scenarios. Machine learning, clustering and distribution sampling techniques are used in this work to finally estimate prices distribution in 2030 in the biggest bidding zone of the Italian market. The results suggest that the prices obtained in the different scenarios do converge to those estimated by the TYNDP. The approach used bypasses the need to have access to all the transactions of a given market. Probability distributions are in fact enough in the proposed methodology to achieve similar results to those based on full knowledge of transaction datasets

Local Market Mechanisms: how Local Markets can shape the Energy Transition

Europe has embarked on a journey towards a zero-emission system, with the power system at its core. From electricity generation to electric vehicles, the European power system must transform into an interconnected, intelligent network. To achieve this vision, active user participation is crucial, ensuring transparency, efficiency, and inclusivity. Thus, Europe has increasingly focused on the concept of markets in all their facets. This thesis seeks to answer the following questions: How can markets, often considered abstract and accessible only to high-level users, be integrated for end-users? How can market mechanisms be leveraged across various phases of the electrical system? Why is a market- driven approach essential for solving network congestions and even influencing planning? These questions shape the core of this research. The analysis unfolds in three layers, each aligned with milestones leading to 2050. The first explores how market mechanisms can be integrated into system operator development plans, enhancing system resilience in the face of changes. In this regard, this step addresses the question of how a market can be integrated into the development plans of a network and how network planning can account for uncertainties. Finally, the analysis highlights the importance of sector coupling in network planning, proposing a study in which various energy vectors lead to a multi-energy system. According to the roadmap to 2030, this layer demonstrates how markets can manage several components of the gas and electrical network. Finally, even though the robust optimisation increases the final cost in the market, it allows to cover the system operator from uncertainties. The second step delves into the concept of network congestion. While congestion management is primarily the domain of operators, it explores how technical and economic collaboration between operators and system users, via flexibility markets, can enhance resilience amid demand uncertainties and aggressive market behaviours. In addition to flexibility markets, other congestion markets are proposed, some radically different, like locational marginal pricing, and others more innovative, such as redispatching markets for distribution. Building upon the first analysis, this section addresses questions of how various energy vectors can be used not only to meet demand but also to manage the uncertainties associated with each resource. Consequently, this second part revisits the concept of sector coupling, demonstrating how various energy vectors can be managed through flexibility markets to resolve network congestion while simultaneously handling uncertainties related to different vectors. The results demonstrate the usefulness of the flexibility market in managing the sector coupling and the uncertainties related to several energy vectors. The third and most innovative step proposes energy and service markets for low-voltage users, employing distributed ledger technology. Since this step highlights topics that are currently too innovative to be realized, this third section offers a comparative study between centralised and decentralised markets using blockchain technology, highlighting which aspects of distributed ledger technology deserve attention and which aspects of low-voltage markets need revision. The results show that the blockchain technology is still in the early stage of its evolution, and several improvements are needed to fully apply this technology into real-world applications. To sum up, this thesis explores the evolving role of markets in the energy transition. Its insights are aimed at assisting system operators and network planners in effectively integrating market mechanisms at all levels of