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Energy

Research in this area aligns with Portugal’s strategic commitment to decarbonizing its economy and ultimately achieving climate neutrality through reduction of all greenhouse gas emissions to net-zero. This transition requires large-scale deployment of renewable energy sources as well as systemic innovation across diverse components of the energy system, including storage, grids, electrification, efficiency and sustainable fuels. MPP is investigating deeper integration of technologies, markets, and industrial capabilities to meet multiple goals of resilience, affordability and sustainability.

Among the topics MPP is pursuing are renewable energy innovation, energy storage and other grid flexibility solutions, electrification of industry and mobility, energy efficiency in buildings and industrial processes, and energy system modeling. Supporting collaborative research across the entire energy system, projects in this area are aimed at speeding technology validation and industrial deployment, while informing strategic energy planning and policy.

Funded Projects

  • Calls: 2025 Call for Seed Grant Proposals

    Research Areas: Energy

    Abstract

    We propose to develop diodes and prototype solar cells using chalcogenide perovskite thin films. We will deposit BaZrS3 thin films, and BaZr(S,Se)3 alloys with tunable band gap, using previouslyestablished methods of molecular beam epitaxy. We will select contact materials, and will develop methods to deposit and evaluate the contact materials as thin films. We will form p-n heterojunction diodes and test their electrical performance. Finally, we will evaluate the photovoltage and solar-cell performance of the top-performing diodes. Our project will build on a new collaboration between MIT and the International Iberian Nanotechnology Laboratory (INL), leveraging world-leading expertise in chalcogenide perovskite deposition (MIT) and in scanning probe microscopy (INL). We will be the first to characterize and optimize chalcogenide perovskite thin-film diodes and photovoltaic performance, which will be a major advance in this growing research field.

    MIT PI
    Rafael Jaramillo, Associate Professor, Department of Materials Science and Engineering

    PT PI
    Sascha Sadewasser
    Principal Investigator, Laboratory for Nanostructured Solar Cells International Iberian Nanotechnology Laboratory (INL)

  • Calls: 2025 Call for Seed Grant Proposals

    Research Areas: Energy

    Abstract

    The motivation for this project is the recent Iberian blackout. We study it by modeling and simulating multi-country interconnected electric power grid affected by this event using modified publicly available data of European Union grid known as PECASE. We will then use extended AC Optimal Power Flow software to assess the most vulnerable parts of the grid, and, to, consequently, reconstruct the events which led to massive loss of electricity service. Of particular interest will be to understand the role of coordinating inter-countries power exchanges, notably between France and Spain for preventing system voltages from collapsing. In parallel, we will introduce adaptive power electronically switched control of intermittent resources for stabilizing voltage and frequency during such extreme events. The study will set a basis for general framework needed in other parts of the world for the same purposes, including US. Results will be demonstrated using Power Digital Twin at MIT.

    MIT PI
    Marija Ilic, Senior Research Scientist, Department of Electrical Engineering and Computer Science

    PT PI
    Pedro Carvalho Full Professor, IST Técnico Lisboa, Institute for Systems and Computer Engineering, Research and Development

  • Calls: 2025 Call for Seed Grant Proposals

    Research Areas: Energy

    Abstract

    Offshore wind energy leverages the high intensity and consistency of oceanic winds, playing a key role in the transition to renewable energy. As energy demands grow, larger turbines are needed to optimize power generation and reduce costs. However, upscaling introduces structural design and manufacturing challenges. Designing better wind turbines is therefore essential. A key challenge is the time-consuming nature of multiphysics simulations, involving interactions between wind, waves, and ocean currents, limiting exploration of design alternatives. While AI provides a promising way to help alleviate this challenge, most current AI-accelerated models lack the capability to capture multi-physics, leading to untrustworthy or structurally invalid designs. We propose a physics-guided generative design framework that combines Graph Neural Nets (GNNs) and diffusion models, trained on high-fidelity multiphysics simulation data and validated against experimental data from full-scale offshore structures, to design and evaluate offshore structures. This approach enables faster development, improved accuracy, and scalable digital twins for Portugal’s partners in the offshore wind sector.

    MIT PI
    Faez Ahmed, Associate Professor, Department of Mechanical Engineering

    PT PI
    Sérgio Tavares (University of Aveiro),
    Filipe Magalhães (University of Porto)