Power and Energy Systems

About the Domain

Our research in the Power & Energy Systems domain focuses on supporting the decarbonisation of society - a central goal of the European Union - through the integration of renewable energy sources, energy storage, and improved energy efficiency. At INESC TEC, we are committed to designing sustainable, efficient, and resilient energy systems that meet future needs while reducing carbon emissions.

In this domain, we introduce several competences that enables us to develop integrated solutions for the efficient, flexible, and sustainable management of energy, supporting the transition to smarter and decarbonised energy systems. Some of these areas of expertise include:

Power system operation and planning

Smart Grids

Electricity Markets

Multi-energy Systems

Research Challenges

The Power and Energy Systems scientific domain envisions supporting society’s full and enduring decarbonisation, adopting a multidisciplinary strategy acting across the whole energy value chain and planning and operating it across multiple energy carriers, infrastructures, and users in an integrated, interconnected, and digitalised energy ecosystem. This will be anchored on combining model-based and data-driven methods for optimising and controlling energy systems while proposing novel policy and regulatory solutions. A laboratory infrastructure for smart grids and electric vehicles (x-energy) enhances the research and innovation capabilities of the scientific domain by providing technological support for the development and validation of theoretical concepts. Research outcomes include concepts, models, methodologies, and tools addressing the decision problems of citizens, communities, multi-utilities, system operators, regulators, policymakers, and government bodies, tackling four major challenges:

Main Achievements

We have actively contributed to the development of smarter, more collaborative, and sustainable energy systems. Our achievements range from secure data sharing to the optimisation of flexible energy resource participation in markets, with a direct impact on the energy transition and the operation of energy communities.

Safe energy data sharing

We developed an innovative protocol based on federated learning to improve renewable production forecasting, while respecting the privacy of data and energy assets with different owners. This method overcomes the limitations of traditional machine learning models. We proposed a market mechanism that encourages data sharing by assigning monetary value based on its contribution to the business. Publications here, here, here. Patent pending WO/2022/090580.

New models for local markets and flexible resource management

We created an innovative post-delivery peer-to-peer market model that generates supply and demand curves from real measurements and interacts with flexibility markets. We developed coordination methods with grid management, considering constraints. Simultaneously, we applied a predictive control algorithm to the operation of communities with energy storage, validated in a real pilot. Publications here, here, and here.

Aggregation of multi-energy flexible resources

We developed distributed optimisation methods for aggregators to participate simultaneously in electricity, gas, and carbon markets without explicit knowledge of grid constraints. We proposed a stochastic optimisation approach to handle forecasting uncertainties, offering more robust and diversified bidding strategies. These solutions led to the creation of two open-source tools. Learn more here, here, and here.