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Apresentação

Centro de Sistemas de Energia

O centro é uma referência mundial na integração em larga escala de recursos distribuídos. As suas competências levaram à atribuição de papéis decisivos em projetos importantes da UE, assim como deram origem a contratos de desenvolvimento e consultadoria com empresas fabricantes de equipamentos e com empresas de geração, transmissão e distribuição de energia, autoridades reguladores, agências governamentais e investidores na Europa, América do Sul, Estados Unidos da América e África.

O CPES aborda as seguintes áreas principais de investigação: Tomada de Decisão, Otimização e Inteligência Computacional, Previsão, Análise Estática e Dinâmica de Redes de Energia, Confiabilidade, Eletrónica de Potência.

Uma parte do trabalho do CPES é desenvolvido no Laboratório de Redes Elétricas Inteligentes e Veículos Elétricos, que apoia a validação de importantes desenvolvimentos num contexto real.

Nos últimos anos, foram desenvolvidas várias iniciativas no planeamento e operação da rede elétrica, nomeadamente a integração da previsão dos recursos distribuídos e das ferramentas de otimização da rede que são incorporadas em diferentes camadas de tensão, explorando o conceito hierárquico de MicroGrid. Foram tomadas as iniciativas necessárias para a integração da inteligência computacional em algoritmos de controlo, comprovados em situações reais por vários projetos-piloto.   

Últimas Notícias
Sistemas de Energia

INESC TEC e New Mexico State University firmam protocolo de colaboração na área de Energia

Promover oportunidades de intercâmbio e colaboração científica é um dos grandes objetivos do acordo de cooperação entre o INESC TEC e a New Mexico State University (NMSU). A possibilidade de trabalhar conjuntamente surgiu da participação de uma docente da NMSU, Olga Lavrova, na primeira edição do INESC TEC International Visiting Researcher Programme – uma iniciativa que dá a oportunidade a investigadores de outros países de realizarem atividades de investigação no INESC TEC, até a um período máximo de três meses.

17 janeiro 2025

INESC TEC desenvolve sistema que permite estimar flexibilidade do consumo energético em supermercados

Os sistemas de refrigeração são responsáveis por uma fatia considerável do consumo energético no setor retalhista. O INESC TEC liderou o projeto europeu InterConnect e desenvolveu uma ferramenta que prevê o consumo destes sistemas de frio sob vários cenários, oferecendo uma fonte potencial de flexibilidade para o operador da rede de distribuição.  

09 janeiro 2025

Tecnologia INESC TEC põe gestão do consumo energético na palma da mão dos consumidores europeus

O INESC TEC desenvolveu um mecanismo que usa dados para transmitir recomendações voluntárias aos consumidores e, assim, reduzir ou aumentar consumos consoante a necessidade da rede. As sugestões chegam através de aplicações móveis e Portugal não ficou de fora.  

03 dezembro 2024

Sistemas de Energia

Enlit Europe: INESC TEC consolida presença no maior evento europeu de soluções para a energia

Três dias. 15 mil especialistas na área da energia. Mais de 700 expositores. Centenas de sessões e debates sobre digitalização, descentralização e descarbonização. Os números impressionam, mas o impacto gerado pela Enlit Europe é difícil de contabilizar. O INESC TEC voltou a marcar presença no maior palco mundial de energia e inovação tecnológica, para apresentar as suas soluções tecnológicas para o setor. Vamos descobrir?

05 novembro 2024

Ajudar a rede elétrica europeia a partir de casa? Sim, é possível – e esta solução do INESC TEC é prova disso

O projeto InterConnect levou o conceito de interoperabilidade para dentro de casa e deu a consumidores residenciais a possibilidade de contribuírem para uma rede elétrica mais resiliente. Uma ferramenta composta por um gestor de energia e por uma aplicação móvel tornou isso possível. O resultado? Mais participação, menos carga na rede em momentos de picoe “redução da intensidade do carbono produzido”.  

31 outubro 2024

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Projetos Selecionados

CampusREN2025

Formação Avançada para a REN CAMPUS REN2025

2025-2025

REATIVA_MINHO

Estudo de otimização de potência reativa do Parque Eólico do Alto Minho I

2024-2025

EnerTEF

Common European-scale Energy Artificial Intelligence Federated Testing and Experimentation Facility

2024-2027

Equipa
001

Laboratórios

Laboratório de Redes Elétricas Inteligentes e Veículos Elétricos

Publicações

CPES Publicações

Ler todas as publicações

2025

Location of grid forming converters when dealing with multi-class stability problems

Autores
Fernandes, F; Lopes, JP; Moreira, C;

Publicação
IET GENERATION TRANSMISSION & DISTRIBUTION

Abstract
This work proposes an innovative methodology for the optimal placement of grid-forming converters (GFM) in converter-dominated grids while accounting for multiple stability classes. A heuristic-based methodology is proposed to solve an optimisation problem whose objective function encompasses up to 4 stability indices obtained through the simulation of a shortlist of disturbances. The proposed methodology was employed in a modified version of the 39-bus test system, using DigSILENT Power Factory as the simulation engine. First, the GFM placement problem is solved individually for the different stability classes to highlight the underlying physical phenomena that explain the optimality of the solutions and evidence the need for a multi-class approach. Second, a multi-class approach that combines the different stability indices through linear scalarisation (weights), using the normalised distance of each index to its limit as a way to define its importance, is adopted. For all the proposed fitness function formulations, the method successfully converged to a balanced solution among the various stability classes, thereby enhancing overall system stability.

2025

Multiobjective energy management of multi-source offshore parks assisted with hybrid battery and hydrogen/fuel-cell energy storage systems

Autores
Kazemi-Robati, E; Varotto, S; Silva, B; Temiz, I;

Publicação
APPLIED ENERGY

Abstract
With the recent advancements in the development of hybrid offshore parks and the expected large-scale implementation of them in the near future, it becomes paramount to investigate proper energy management strategies to improve the integrability of these parks into the power systems. This paper addresses a multiobjective energy management approach using a hybrid energy storage system comprising batteries and hydrogen/fuel-cell systems applied to multi-source wind-wave and wind-solar offshore parks to maximize the delivered energy while minimizing the variations of the power output. To find the solution of the optimization problem defined for energy management, a strategy is proposed based on the examination of a set of weighting factors to form the Pareto front while the problem associated with each of them is assessed in a mixed-integer linear programming framework. Subsequently, fuzzy decision making is applied to select the final solution among the ones existing in the Pareto front. The studies are implemented in different locations considering scenarios for electrical system limitation and the place of the storage units. According to the results, applying the proposed multiobjective framework successfully addresses the enhancement of energy delivery and the decrease in power output fluctuations in the hybrid offshore parks across all scenarios of electrical system limitation and combinational storage locations. Based on the results, in addition to the increase in delivered energy, a decrease in power variations by around 40 % up to over 80 % is observed in the studied cases.

2025

Budget-Constrained Collaborative Renewable Energy Forecasting Market

Autores
Goncalves, C; Bessa, J; Teixeira, T; Vinagre, J;

Publicação
IEEE Transactions on Sustainable Energy

Abstract
Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones. © 2010-2012 IEEE.

2025

Life cycle assessment comparison of electric and internal combustion vehicles: A review on the main challenges and opportunities

Autores
da Costa, VBF; Bitencourt, L; Dias, BH; Soares, T; Andrade, JVBD; Bonatto, BD;

Publicação
RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Abstract
A notable shift from an internal combustion engine vehicles (ICEVs) fleet to an electric vehicles (EVs) fleet is expected in the medium term due to increasing environmental concerns and technological breakthroughs. In this context, this paper conducts a systematic literature review on life cycle assessment (LCA) research of EVs compared to ICEVs based on highly impactful articles. Several essential aspects and characteristics were identified and discussed, such as the assumed EV types, scales, models, storage technologies, boundaries, lifetime, electricity consumption, driving cycles, combustion fuels, locations, impact assessment methods, and functional units. Furthermore, LCA results in seven environmental impact categories were gathered and evaluated in detail. The research indicates that, on average, battery electric vehicles are superior to ICEVs in terms of greenhouse gas (GHG) emissions (182.9 g CO2-eq/km versus 258.5 g CO2-eq/km), cumulative energy demand (3.2 MJ/km versus 4.1 MJ/km), fossil depletion (49.7 g oil-eq/km versus 84.4 g oil-eq/km), and photochemical oxidant formation (0.47 g NMVOC-eq/km versus 0.61 g NMVOC-eq/km) but are worse than ICEVs in terms of human toxicity (198.1 g 1,4-DCB-eq/km versus 64.8 g 1,4-DCB-eq/km), particulate matter formation (0.32 g PM10-eq/km versus 0.26 g PM10-eq/km), and metal depletion (69.3 g Fe-eq/km versus 19.0 g Fe-eq/km). Emerging technological developments are expected to tip the balance in favor of EVs further. Based on the conducted research, we propose to organize the factors that influence the vehicle life cycle into four groups: user specifications, vehicle specifications, local specifications, and multigroup specifications. Then, a set of improvement opportunities is provided for each of these groups. Therefore, the present paper can contribute to future research and be valuable for decision-makers, such as policymakers.

2025

Understanding wind Energy Economic externalities impacts: A systematic literature review

Autores
Ramalho, E; Lima, F; López-Maciel, M; Madaleno, M; Villar, J; Dias, MF; Botelho, A; Meireles, M; Robaina, M;

Publicação
RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Abstract
Electricity generation from wind energy is one of the main drivers of decarbonization in energy systems. However, installing wind farm facilities may have beneficial and harmful impacts on the habitat of living beings. This study reviews the literature based on economic analysis to identify the main externalities related to the installation of wind farms and the economic methodologies used to assess these externalities, filling an existent literature gap. A systematic literature review followed the Preferred Reporting Items on Systematic Reviews and Meta-analysis standards. A total of 33 studies were identified, most of them carried out in Europe. The studies cover 24 years, between 1998 and 2022. The externalities associated with wind electricity generation are classified into three categories: the impact on well-being, the impact of wind turbines, and the impacts of avoided externalities. Most studies (24 out of 33) determine economic values by stated preference methods through choice experiments, discrete choice experiments, and contingent valuation. Revealed preference methods were identified in 5 studies using hedonic pricing and travel cost techniques. The challenges and limitations of this analysis in terms of externalities identification and their assessment are also discussed, concluding that additional updated review studies are needed since the latest ones were published in 2016 and 2017. Moreover, it gives insights to policymakers and academics on a more complete approach they can use to evaluate the impacts of decarbonization, which, apart from the technological view, also considers and estimates the socio-economic and environmental perspectives.

Factos & Números

9Docentes do Ensino Superior

2020

60Artigos em revistas indexadas

2020

1Capítulos de livros

2020

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