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Sobre

Sobre

Clara Gouveia é mestre e doutorada em Engenharia Eletrotécnica e de Computadores pela Faculdade de Engenharia da Universidade do Porto, em 2008 e 2015 respetivamente. É membro do Centro de Sistemas de Energia do INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, onde desempenha funções de Investigadora Sénior. É atualmente responsável de área EMS/DMS e automação de redes, tendo a seu cargo a definição de linhas estratégicas de atuação e angariação de financiamento a nível nacional e europeu. Integra ainda o Conselho Científico do INESC TEC. Desde 2015 que desempenha funções de gestão de projetos de investigação e consultoria envolvendo empresas relevantes no sector nacional e internacional. O seu trabalho é dedicado à especificação, desenvolvimento e validação de soluções de gestão de energia tendo em conta a integração de recursos distribuídos (armazenamento de energia, produção dispersa, carga controlável e veículos elétricos) assim como soluções para a digitalização da rede de distribuição. Conta ainda com publicações em revistas científicas internacionais, livros e atas de conferências internacionais.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Clara Sofia Gouveia
  • Cluster

    Energia
  • Cargo

    Responsável de Área
  • Desde

    01 julho 2011
031
Publicações

2023

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

Autores
Rocha, R; Silva, R; Mello, J; Faria, S; Retorta, F; Gouveia, C; Villar, J;

Publicação
ENERGIES

Abstract
This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer's individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers' energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer's new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

2023

Flexibility Modeling and Trading in Renewable Energy Communities

Autores
Agrela, J; Rezende, I; Soares, T; Gouveia, C; Silva, R; Villar, J;

Publicação
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
This work presents an approach to the flexibility of energy consumption in Renewable Energy Communities (RECs). A two-stage model for quantifying the flexibility provided by the domestic energy resources operation and its negotiation in a market platform is proposed. In stage 1, the optimal consumption of each prosumer is determined, as well as the respective technical flexibility of their resources, namely the maximum and minimum resource operation limits. In stage 2, this technical flexibility is offered in a local flexibility-only market structure, in which both the DSO and the prosumers can present their flexibility needs and requirements. The flexibility selling and buying bids of the prosumers participating in the market are priced based on their base tariff, which is the energy cost of the prosumers corresponding to their optimal schedule of the first stage when no flexibility is provided. Therefore, providing flexibility is an incentive to reduce their energy bill or increase their utility, encouraging their participation in the local flexibility market.

2023

Operation and simulation of a renewable energy community based on a local post-delivery pool market

Autores
Tavares, T; Mello, J; Silva, R; Moreno, A; Garcia, A; Pacheco, J; Pereira, C; Amorim, M; Gouveia, C; Villar, J;

Publicação
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
This paper presents an innovative digital platform for managing energy communities with self-consumption and energy trading in a local electricity market. Its architecture is based on micro-services, such as the energy transaction service, the settlement service to compute the financial compensations among community members for the energy transacted, or a resource sizing service. This approach enables the platform to be more efficient and scalable, making easier to incorporate new functionalities while maintaining a secure community and energy transactions management. The transactions and settlement procedures, adapted to the Portuguese regulation, are described, and the results of the platform operating a post-delivery pool market are presented and analyzed. This paper contributes to the understanding and improvement of renewable energy communities' business models and management, offering insights for policymakers, researchers, and practitioners in the field.

2022

A Multiobjective Approach for the Optimal Placement of Protection and Control Devices in Distribution Networks With Microgrids

Autores
REIZ, C; DE LIMA, TD; LEITE, JB; JAVADI, MS; GOUVEIA, CS;

Publicação
IEEE ACCESS

Abstract
Protection and control systems represent an essential part of distribution networks by ensuring the physical integrity of components and by improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized loads by transferring loads to neighboring feeders. The integration of distributed generation has the potential to enhance the continuity of energy services through islanding operation during outage conditions. In this context, this study presents a multi-objective optimization approach for sizing and allocating protection and control devices in distribution networks with microgrids supplied by renewable energy sources. Reclosers, fuses, remote-controlled switches, and directional relays are considered in the formulation. Demand and generation uncertainties define the islanding operation and the load transfer possibilities. A non-dominated sorting genetic algorithm is applied in the solution of the allocation problem considering two conflicting objectives: cost of energy not supplied and equipment cost. The compromise programming is then performed to achieve the best solution from the Pareto front. The results show interesting setups for the protection system and viability of islanding operation.

2022

Data-Driven Anomaly Detection and Event Log Profiling of SCADA Alarms

Autores
Andrade, JR; Rocha, C; Silva, R; Viana, JP; Bessa, RJ; Gouveia, C; Almeida, B; Santos, RJ; Louro, M; Santos, PM; Ribeiro, AF;

Publicação
IEEE ACCESS

Abstract
Network human operators' decision-making during grid outages requires significant attention and the ability to perceive real-time feedback from multiple information sources to minimize the number of control actions required to restore service, while maintaining the system and people safety. Data-driven event and alarm management have the potential to reduce human operator cognitive burden. However, the high complexity of events, the data semantics, and the large variety of equipment and technologies are key barriers for the application of Artificial Intelligence (AI) to raw SCADA data. In this context, this paper proposes a methodology to convert a large volume of alarm events into data mining terminology, creating the conditions for the application of modern AI techniques to alarm data. Moreover, this work also proposes two novel data-driven applications based on SCADA data: (i) identification of anomalous behaviors regarding the performance of the protection relays of primary substations, during circuit breaker tripping alarms in High Voltage (HV) and Medium Voltage (MV) lines; (ii) unsupervised learning to cluster similar events in HV line panels, classify new event logs based on the obtained clusters and membership grade with a control parameter that helps to identify rare events. Important aspects associated with data handling and pre-processing are also covered. The results for real data from a Distribution System Operator (DSO) showed: (i) that the proposed method can detect unexpected relay pickup events, e.g., one substation with nearly 41% of the circuit breaker alarms had an 'atypical' event in their context (revealed an overlooked problem on the electrification of a protection relay); (ii) capability to automatically detect and group issues into specific clusters, e.g., SF6 low-pressure alarms and blocks with abnormal profiles caused by event time-delay problems.

Teses
supervisionadas

2020

Mapeamento automático da topologia de redes inteligentes de baixa tensão

Autor
João Afonso da Silva Picão

Instituição
UP-FEUP