Advanced control for large-scale integration of Power-to-X microgrids in power systems (ATLAS)
ABSTRACT
The ATLAS project is conceived to address the challenges posed by the optimization and control of Power Systems with a high penetration of renewable energy. ATLAS aims to maximize the application of the microgrid concept as the cornerstone of the energy transition, advancing the state of the art in microgrids by not only using classical battery energy storage systems (ESS) but also hybrid electrical ESS in hydrogen, batteries, and supercapacitors. Additionally, it incorporates Power-to-X systems and combined heat, cooling, electricity, and hydrogen generation, which will enhance the flexibility and resilience characteristics of future electrical grids in a zero-emissions scenario. The project primarily focuses on creating a digital platform capable of jointly optimizing a large number of microgrids, which is the main objective and impact of the project. The research lines proposed by ATLAS aim to generate knowledge that, through the interdisciplinarity between the fields of electrical engineering and automatic control, addresses the open research problems that a massive deployment of microgrids would entail, such as: 1) Development of algorithms based on distributed model predictive control techniques that allow the optimization of a large number of interacting microgrids simultaneously, resolving the resulting computational cost; 2) Development of stochastic model predictive control techniques that enable the integration of a high number of probabilistic scenarios into the microgrid control problem; 3) Development of nonlinear model predictive control techniques to introduce nonlinear processes inherent to the degradation mechanisms in response to transients in storage systems, seeking complementarity between technologies; 4) Development of nonlinear predictive control algorithms to integrate efficiency curves in hybrid storage systems, generating the concept of maximum efficiency point tracking in hybrid ESS; 5) Development of energy management systems that, combining predictive control techniques, allow the optimization of microgrids based on the hydrogen vector with multiple business models, including integration into electricity markets, refueling of electric and hydrogen vehicles, as well as commercialization of hydrogen-derived products in the chemical industry. Given the project's evident multidisciplinarity, the developed control techniques can serve as a basis for other scientific research involving a large number of interconnected systems, control of systems with uncertainty, or the incorporation of nonlinear control techniques with low computational cost. Similarly, the project also seeks the development of advanced models that allow quantifying the impact of exposure to fluctuating power profiles on the lifetime of ESS.
PROJECT TEAM
Main Researchers
Dr. Félix García Torres
Dr. Jorge E. Jiménez Hornero
Research Team
Dr. Francisco J. Vázquez Serrano
Dr. José Ramón González Jiménez
Dr. Francisco Javier Jiménez Romero
Dr. Jorge Ruiz Calviño
Dr. David Bullejos Martín
Dr. Francisco Ramón Lara Raya
Javier Tobajas Blanco
Work Team
Dr. Alessandra Parisio
Dr. Josep María Guerrero Zapata
Álvaro Sánchez Sánchez de Puerta
Mª Carmen López Luna
FUNDING
Funder: Ministry of Science, Innovation and Universities of Spain/AEI /10.13039/501100011033/FEDER, UE
Grant Number: PID2024-159933OB-I00
Duration: from 09-2025 to 08-2028
Awards
- ATLAS
- Ministerio de Ciencia, Innovación y Universidades