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Apresentação

Sistemas de Energia

O Centro de Sistemas de Energia (CPES) é uma referência mundial na integração em larga escala de produção de energia elétrica de base renovável no sistema elétrico.


Investigamos e desenvolvemos soluções avançadas que permitem a monitorização, o controlo a otimização e a previsão da produção e do consumo de energia elétrica e sistemas multi-energia. Apoiamos a descarbonização do sistema energético, na eletrificação da sociedade e na integração em larga escala de fontes renováveis, tornando as redes elétricas mais flexíveis, inteligentes e resilientes.


O resultado do nosso trabalho de investigação inclui modelos, metodologias, hardware e software (muito dos qual em código aberto) para diferentes atores do sector energético, nomeadamente cidadãos, comunidades, prestadores de serviços operadores do sistema de energia, reguladores, decisores políticos e organismos governamentais.


Dispomos de um Laboratório de Redes Elétricas Inteligentes e Veículos Elétricos – o X-Energy Lab (link) – onde validamos avanços tecnológicos num contexto real, assegurando que as nossas soluções têm impacto no setor energético.


As nossas competências garantem-nos, por isso, um lugar de destaque em projetos financiados nacionais e internacionais para a transição energética, e apoio direto a agentes relevantes do setor elétrico através de prestações de serviços.

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Publicações

CPES Publicações

Ler todas as publicações

2026

Coordinated Operation and Flexibility Management of Medium and Low Voltage Grids

Autores
Affonso, CM; Bessa, RJ; Gouveia, CS;

Publicação
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Abstract
The connection of distributed energy resources in distribution system have been increasing significantly, requiring new approaches as market-based flexibility solutions. This paper proposes the coordinated operation of on-load tap changer and flexibility services traded in a local market for voltage regulation in medium and low voltage grid. The wider action of on-load tap changer is used to restore voltages at the medium voltage feeder based on sensitivity coefficients. If voltage violations persist, flexibilities are traded in a local energy market with a cost-effective approach, where flexibility costs are minimized, and are activated according to their effectiveness indicated by sensitivity coefficients. Sensitivity coefficients are obtained in the medium voltage using an analytical approach that can be applied to multi-phase unbalanced systems, and in the low voltage using a data-driven approach due to their limited observability. Results show the proposed approach can be an effective solution to regulate voltages, combining the wider action of on-load tap changer with local flexibility, avoiding unnecessary tap changes and requesting a small volume of flexibility services.

2026

Evolving power system operator rules for real-time congestion management

Autores
Moaidi, F; Bessa, J;

Publicação
Energy and AI

Abstract
The growing integration of renewable energy sources and the widespread electrification of the energy demand have significantly reduced the capacity margin of the electrical grid. This demands a more flexible approach to grid operation, for instance, combining real-time topology optimization and redispatching. Traditional expert-driven decision-making rules may become insufficient to manage the increasing complexity of real-time grid operations and derive remedial actions under the N-1 contingency. This work proposes a novel hybrid AI framework for power grid topology control that integrates genetic network programming (GNP), reinforcement learning, and decision trees. A new variant of GNP is introduced that is capable of evolving the decision-making rules by learning from data in a reinforcement learning framework. The graph-based evolutionary structure of GNP and decision trees enables transparent, traceable reasoning. The proposed method outperforms both a baseline expert system and a state-of-the-art deep reinforcement learning agent on the IEEE 118-bus system, achieving up to an 28% improvement in a key performance metric used in the Learning to Run a Power Network (L2RPN) competition. © 2025

2026

Industrial Application of High-Temperature Heat and Electricity Storage for Process Efficiency and Power-to-Heat-to-Power Grid Integration

Autores
Coelho A.; Silva R.; Soares F.J.; Gouveia C.; Mendes A.; Silva J.V.; Freitas J.P.;

Publicação
Lecture Notes in Energy

Abstract
This chapter explores the potential of thermal energy storage (TES) systems towards the decarbonization of industry and energy networks, considering its coordinated management with electrochemical energy storage and renewable energy sources (RES). It covers various TES technologies, including sensible heat storage (SHS), latent heat storage (LHS), and thermochemical energy storage (TCS), each offering unique benefits and facing specific challenges. The integration of TES into industrial parks is highlighted, showing how these systems can optimize energy manage-ment and reduce reliance on external sources. A district heating use case also demonstrates the economic and environmental advantages of a multi-energy management strategy over single-energy approaches. Overall, TES technologies are presented as a promising pathway to greater energy effi-ciency and sustainability in industrial processes.

2026

Advanced Switched Reluctance Motor Control Methodologies for Electric Drive Applications

Autores
Touati, Z; Araújo, RE; Khedher, A;

Publicação
Studies in Systems, Decision and Control

Abstract
Switched Reluctance Motors (SRMs) are becoming increasingly popular for various applications, including automotive applications. However, challenges such as torque ripple and vibration persist, limiting their performance. This chapter investigates the application of intelligent control strategies, particularly fuzzy logic, to mitigate these issues. Fuzzy logic modeling does not require an accurate mathematical model which is very difficult to obtain from a SRM because of its inherit nonlinearities. In this work a Fuzzy Logic Controller (FLC) applied to the speed control of an SRM, highlighting the advantages of FL over traditional methods in terms of flexibility and performance. A comparison is made between the FLC, a Sliding Mode Control (SMC), and a Proportional Integral (PI) controller. Simulation results using MATLAB/Simulink show that the FLC substantially reduces torque ripple, offering better overall performance in terms of smoothness and robustness under varying operational conditions. The findings demonstrate that FLC offers a more effective solution than conventional approaches for SRM applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

2026

Optimized Switched Reluctance Generator Operation in Wind Energy Applications

Autores
Touati, Z; Araújo, RE; Khedher, A;

Publicação
Studies in Systems, Decision and Control

Abstract
Switched reluctance generators (SRG) are one of the machines with huge potential in wind power generation due to their reliability and robust design. However, the inherent characteristics of SRGs lead to significant challenges in achieving high efficiency and low output current and torque ripple simultaneously. The performance of SRGs is hindered by conflicting requirements. To address these issues, this chapter presents an optimization control strategy aimed at improving the static performance of SRGs. The chapter discusses the application of the Particle Swarm Optimization (PSO) technique to optimize the commutation angles, specifically the turn-on (?on) and turn-off (?off) angles, for an 8/6 SRG. The proposed strategy consists of two main steps. First, a Maximum Power Point Tracking (MPPT) algorithm is implemented to maximize power output at varying rotor speeds, combined with a direct power control method to regulate the power generated by the SRG. Second, a multi-objective function is developed to evaluate the SRG performance, considering key factors such as power output, output current ripple, and torque ripple. The simulation results indicate that implementing optimized turn-on and turn-off angles leads to a reduction in torque ripple from -1.78 Nm using the conventional technique to -0.66 Nm with the proposed method, corresponding to an impressive 63% decrease. Furthermore, the optimization strategy effectively maximizes the efficiency of the system employing an MPPT approach, ensuring optimal energy conversion under varying operating conditions. Future research directions include experimental validation of the proposed control system on real hardware to assess its practical feasibility and performance under real-world operating conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.