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- Large-Scale Integration of Variable Renewable Energies in Electric Power Markets — Optimization Models, Options and ChallengesPublication . Bento, Pedro Miguel Rocha ; Mariano, Sílvio José Pinto SimõesElectrical Power Systems recognized as vast and complex entities, are the true ”engine” of contemporary societies. Currently, social and environmental concerns dominate the political agenda, notably highlighted by the Paris Agreement (2015), the EU’s Energy Roadmap 2050, and the UN’s 2030 Agenda for Sustainable Development. These initiatives stem from the detrimental impacts of persistent greenhouse gas emissions, requiring a significant contribution from these entities. This scenario foreshadows a substantial increase in renewable energy penetration, leading to increasingly decentralized and variable generation. Consequently, the Iberian Power Systems, as a leading adopter, faces additional and considerable transformations, requiring a reevaluation of otherwise outdated predicates and in more micro level, decisionmaking processes. Key areas demanding special attention include the future energy policy, which can only be effectively shaped after reviewing the evolution of the power generation structure within a market-integrated context, as well as the multitude of related options for providing system flexibility—a key enabler of this profound change. Moreover, a prevailing trend across nearly every field is the increasing reliance on data proliferation, machine learning models, and advanced optimization tools to address challenges that were once considered highly complex and less accessible. This is particularly evident in the context of electrical power systems design and operation, where such tools are now being applied to solve micro-level tasks with significant accuracy. As a result, to effectively integrate these tools, it is essential to first delve into the theoretical bedrock and practical intricacies — including the selection and tuning of hyperparameters, model architectures, and optimization strategies. This knowledge has become indispensable for modern power systems engineers, enabling them to better understand and tackle the micro-level challenges that often stem from broader energy policy decisions. In this context, the optimal power flow and short-term price forecasting problems — both of vital importance to electricity market participants — will serve as experimental test beds to rigorously evaluate and demonstrate the application of these data-driven methodologies.