Ingeniería Electrónica

URI permanente para esta comunidadhttps://hdl.handle.net/11441/11356

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Examinando Ingeniería Electrónica por Agencia financiadora "European Research Council (ERC)"

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  • Miniatura
    Acceso AbiertoArtículo
    High Technology Readiness Level Techniques for Brushless Direct Current Motors Failures Detection: A Systematic Review
    (MDPI, 2020-04) Fico, Vito Mario; Martín Prats, María de los Ángeles; Ierardi, Carmelina; Universidad de Sevilla. Departamento de Ingeniería Electrónica; European Research Council (ERC)
    Many papers related to this topic can be found in the bibliography; however, just a modest percentage of the introduced techniques are developed to a Technology Readiness Level (TRL) sufficiently high to be implementable in industrial applications. This paper is focused precisely on the review of this specific topic. The investigation on the state of the art has been carried out as a systematic review, a very rigorous and reliable standardised scientific methodology, and tries to collect the articles which are closer to a possible implementation. This selection has been carefully done with the definition of a series of rules, drawn to represent the adequate level of readiness of fault detection techniques which the various articles propose.
  • Miniatura
    Acceso AbiertoArtículo
    Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence
    (MDPI, 2021-06) García Santacruz, Carlos; Galván García-Pérez, Luis; Carrasco Solís, Juan Manuel; Galván Díez, Eduardo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; European Research Council (ERC)
    Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.