The transition to a decarbonized energy system necessitates an advanced integration of renewable energy sources (RES) across multiple sectors, including electricity, gas, and heating. In this context, electricity generation is shifting from centralized fossil-fuel-based plants to decentralized renewable sources, such as wind and solar, which are inherently variable and require enhanced flexibility in both markets and networks. Meanwhile, the gas sector is evolving with the introduction of green hydrogen as a low-carbon alternative, requiring new infrastructure and operational strategies. The heat sector, traditionally dominated by monopolistic structures, is also experiencing a shift toward decentralized renewable heat sources and electrification through technologies like heat pumps. These transformations highlight the need for an efficient sector coupling, where interactions between electricity, gas, and heat markets are optimized to enhance overall system flexibility and resilience. However, current market structures and network operations often lack proper coordination, leading to inefficiencies that hinder the effective integration of RES.

The dissertation consists of six interrelated publications that address different aspects of multi-energy system coordination. The first two papers focus on improving probabilistic forecasting methods, developing multivariate techniques to predict renewable energy generation and grid congestion more accurately. The third and fourth papers introduce novel modeling approaches, with an emphasis on optimizing cross-sectoral energy flows and integrating decentralized flexibility options such as demand-side management via residential heat pumps. The final two papers propose distributed market-clearing frameworks, first for multi-energy systems with multiple market participants and then for systems with multiple market participants and network operators. These works collectively contribute to a deeper understanding of how advanced forecasting, efficient modeling, and improved market mechanisms can enhance the coordination between markets and networks, ultimately facilitating the large-scale integration of RES.

Among its key contributions, the findings of this research highlight (i) the advantages of probabilistic forecasting in quantifying uncertainties for operational decision-making, (ii) the importance of modeling cross-sectoral flexibility by accurately capturing energy flows and network operations, and (iii) the value of distributed market-clearing frameworks in enhancing multi-energy system coordination while ensuring market efficiency and confidentiality. By combining methodological advancements with practical applications, this dissertation provides valuable insights for policymakers, system operators, and market participants aiming to enhance the resilience and efficiency of future energy systems.