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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: orcid bw Ceschini A.;
    Ceschini A.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Ceschini A. in OpenAIRE
    Rosato A.; Succetti F.; orcid bw Araneo R.;
    Araneo R.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Araneo R. in OpenAIRE
    +1 Authors

    Classification of time series is a fundamental problem in energy distribution, especially to extract information about events that occurred during the observation period. In this paper, we propose a solution to the problem of identifying energy thefts by introducing a classification method based on convolutional neural networks. The input structure to the model is based on real data that have been certified by external authorities and regards thefts operated by the final user with physical intervention. The training of the neural network is done by means of yearly time series of monthly data, which pertain to different physical quantities relevant to the user profile. The proposed method has been experimentally tested and verified against acceptable test results in different conditions, even giving an indication on where in the sequence the theft has occurred.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1109/eeeic/...
    Conference object . 2022 . Peer-reviewed
    License: STM Policy #29
    Data sources: Crossref
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1109/eeeic/...
      Conference object . 2022 . Peer-reviewed
      License: STM Policy #29
      Data sources: Crossref
      addClaim
  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: orcid bw Ceschini A.;
    Ceschini A.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Ceschini A. in OpenAIRE
    Rosato A.; Succetti F.; orcid bw Araneo R.;
    Araneo R.
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Araneo R. in OpenAIRE
    +1 Authors

    Classification of time series is a fundamental problem in energy distribution, especially to extract information about events that occurred during the observation period. In this paper, we propose a solution to the problem of identifying energy thefts by introducing a classification method based on convolutional neural networks. The input structure to the model is based on real data that have been certified by external authorities and regards thefts operated by the final user with physical intervention. The training of the neural network is done by means of yearly time series of monthly data, which pertain to different physical quantities relevant to the user profile. The proposed method has been experimentally tested and verified against acceptable test results in different conditions, even giving an indication on where in the sequence the theft has occurred.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1109/eeeic/...
    Conference object . 2022 . Peer-reviewed
    License: STM Policy #29
    Data sources: Crossref
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1109/eeeic/...
      Conference object . 2022 . Peer-reviewed
      License: STM Policy #29
      Data sources: Crossref
      addClaim
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Stracqualursi E.;
    Stracqualursi E.
    ORCID
    Harvested from ORCID Public Data File

    Stracqualursi E. in OpenAIRE
    orcid Araneo R.;
    Araneo R.
    ORCID
    Harvested from ORCID Public Data File

    Araneo R. in OpenAIRE
    orcid Celozzi S.;
    Celozzi S.
    ORCID
    Harvested from ORCID Public Data File

    Celozzi S. in OpenAIRE

    Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Archivio della ricer...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
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    Energies
    Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Archivio della ricer...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2021 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2021
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Stracqualursi E.;
    Stracqualursi E.
    ORCID
    Harvested from ORCID Public Data File

    Stracqualursi E. in OpenAIRE
    orcid Araneo R.;
    Araneo R.
    ORCID
    Harvested from ORCID Public Data File

    Araneo R. in OpenAIRE
    orcid Celozzi S.;
    Celozzi S.
    ORCID
    Harvested from ORCID Public Data File

    Celozzi S. in OpenAIRE

    Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Archivio della ricer...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2021 . Peer-reviewed
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
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    Energies
    Article . 2021
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Archivio della ricer...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2021 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
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      Energies
      Article . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Fabrizio De Caro;
    Fabrizio De Caro
    ORCID
    Harvested from ORCID Public Data File

    Fabrizio De Caro in OpenAIRE
    orcid Amedeo Andreotti;
    Amedeo Andreotti
    ORCID
    Harvested from ORCID Public Data File

    Amedeo Andreotti in OpenAIRE
    orcid Rodolfo Araneo;
    Rodolfo Araneo
    ORCID
    Harvested from ORCID Public Data File

    Rodolfo Araneo in OpenAIRE
    orcid Massimo Panella;
    Massimo Panella
    ORCID
    Harvested from ORCID Public Data File

    Massimo Panella in OpenAIRE
    +3 Authors

    The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications. In this context, the research for scalable and flexible methodologies aimed at supporting rapid decisions in a data rich, but information limited environment represents a relevant issue to address. To this aim, this paper investigates the role of Knowledge Discovery from massive Datasets in smart grid computing, exploring its various application fields by considering the power system stakeholder available data and knowledge extraction needs. In particular, the aim of this paper is dual. In the first part, the authors summarize the most recent activities developed in this field by the Task Force on “Enabling Paradigms for High-Performance Computing in Wide Area Monitoring Protective and Control Systems” of the IEEE PSOPE Technologies and Innovation Subcommittee. Differently, in the second part, the authors propose the development of a data-driven forecasting methodology, which is modeled by considering the fundamental principles of Knowledge Discovery Process data workflow. Furthermore, the described methodology is applied to solve the load forecasting problem for a complex user case, in order to emphasize the potential role of knowledge discovery in supporting post processing analysis in data-rich environments, as feedback for the improvement of the forecasting performances.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
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    Energies
    Article . 2020 . Peer-reviewed
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    Energies
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Energies
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      Energies
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    Authors: orcid Fabrizio De Caro;
    Fabrizio De Caro
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    Fabrizio De Caro in OpenAIRE
    orcid Amedeo Andreotti;
    Amedeo Andreotti
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    Amedeo Andreotti in OpenAIRE
    orcid Rodolfo Araneo;
    Rodolfo Araneo
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    Rodolfo Araneo in OpenAIRE
    orcid Massimo Panella;
    Massimo Panella
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    Massimo Panella in OpenAIRE
    +3 Authors

    The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications. In this context, the research for scalable and flexible methodologies aimed at supporting rapid decisions in a data rich, but information limited environment represents a relevant issue to address. To this aim, this paper investigates the role of Knowledge Discovery from massive Datasets in smart grid computing, exploring its various application fields by considering the power system stakeholder available data and knowledge extraction needs. In particular, the aim of this paper is dual. In the first part, the authors summarize the most recent activities developed in this field by the Task Force on “Enabling Paradigms for High-Performance Computing in Wide Area Monitoring Protective and Control Systems” of the IEEE PSOPE Technologies and Innovation Subcommittee. Differently, in the second part, the authors propose the development of a data-driven forecasting methodology, which is modeled by considering the fundamental principles of Knowledge Discovery Process data workflow. Furthermore, the described methodology is applied to solve the load forecasting problem for a complex user case, in order to emphasize the potential role of knowledge discovery in supporting post processing analysis in data-rich environments, as feedback for the improvement of the forecasting performances.

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    Energies
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    Energies
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    Energies
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      Energies
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      Energies
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    Authors: orcid bw ARANEO, Rodolfo;
    ARANEO, Rodolfo
    ORCID
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    ARANEO, Rodolfo in OpenAIRE
    G. GUIDA; orcid bw MARADEI, Francescaromana;
    MARADEI, Francescaromana
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    MARADEI, Francescaromana in OpenAIRE
    orcid bw CELOZZI, Salvatore;
    CELOZZI, Salvatore
    ORCID
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    CELOZZI, Salvatore in OpenAIRE

    Actual interconnects are analysed and simulated by means of equivalent Spice-like circuits accounting for both dielectric and conductive losses. New analytical expressions are proposed for the effective permittivity allowing fast and accurate propagation sensitivity analysis with respect to parametric variations of configuration and materials. Accuracy of equivalent circuits is tested against analytical models, while the model of the effective permittivity is compared with numerical results.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.2...arrow_drop_down
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    https://doi.org/10.23919/emc.2...
    Conference object . 2004 . Peer-reviewed
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    Authors: orcid bw ARANEO, Rodolfo;
    ARANEO, Rodolfo
    ORCID
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    ARANEO, Rodolfo in OpenAIRE
    G. GUIDA; orcid bw MARADEI, Francescaromana;
    MARADEI, Francescaromana
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    MARADEI, Francescaromana in OpenAIRE
    orcid bw CELOZZI, Salvatore;
    CELOZZI, Salvatore
    ORCID
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    CELOZZI, Salvatore in OpenAIRE

    Actual interconnects are analysed and simulated by means of equivalent Spice-like circuits accounting for both dielectric and conductive losses. New analytical expressions are proposed for the effective permittivity allowing fast and accurate propagation sensitivity analysis with respect to parametric variations of configuration and materials. Accuracy of equivalent circuits is tested against analytical models, while the model of the effective permittivity is compared with numerical results.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.2...arrow_drop_down
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    https://doi.org/10.23919/emc.2...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Antonello Rosato;
    Antonello Rosato
    ORCID
    Harvested from ORCID Public Data File

    Antonello Rosato in OpenAIRE
    orcid Massimo Panella;
    Massimo Panella
    ORCID
    Harvested from ORCID Public Data File

    Massimo Panella in OpenAIRE
    orcid bw Rodolfo Araneo;
    Rodolfo Araneo
    ORCID
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    orcid Amedeo Andreotti;
    Amedeo Andreotti
    ORCID
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    Amedeo Andreotti in OpenAIRE

    In the modern scenario of smart-grids, the concept of virtual power plant (VPP) is undoubtedly a cornerstone for the smooth integration of renewable energy sources into existing energy systems with a high penetration level. A VPP is the aggregation of decentralized medium-scale power sources, including photovoltaic and wind power plants, combined heat and power units, as well as demand-responsive loads and storage systems, with a twofold objective. On one hand, VPP relieves the stability and dispatchability problems on the external smart grid since it can be operated on an individual basis, appearing as a single system on the whole. On the other hand, VPP improves flexibility coming from all the networked units and enable traders to enhance forecasting and trading programs of renewable energies. This paper proposes a novel distributed decentralized prediction method for the management of VPPs. The novelty of the proposed technique is to effectively combine the concepts of neural networks and machine learning with a distributed architecture that is suitable for the aggregation purposes of the VPP.

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    IEEE Transactions on Industry Applications
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    IEEE Transactions on Industry Applications
    Article . 2019 . Peer-reviewed
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    Authors: orcid Antonello Rosato;
    Antonello Rosato
    ORCID
    Harvested from ORCID Public Data File

    Antonello Rosato in OpenAIRE
    orcid Massimo Panella;
    Massimo Panella
    ORCID
    Harvested from ORCID Public Data File

    Massimo Panella in OpenAIRE
    orcid bw Rodolfo Araneo;
    Rodolfo Araneo
    ORCID
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    Rodolfo Araneo in OpenAIRE
    orcid Amedeo Andreotti;
    Amedeo Andreotti
    ORCID
    Harvested from ORCID Public Data File

    Amedeo Andreotti in OpenAIRE

    In the modern scenario of smart-grids, the concept of virtual power plant (VPP) is undoubtedly a cornerstone for the smooth integration of renewable energy sources into existing energy systems with a high penetration level. A VPP is the aggregation of decentralized medium-scale power sources, including photovoltaic and wind power plants, combined heat and power units, as well as demand-responsive loads and storage systems, with a twofold objective. On one hand, VPP relieves the stability and dispatchability problems on the external smart grid since it can be operated on an individual basis, appearing as a single system on the whole. On the other hand, VPP improves flexibility coming from all the networked units and enable traders to enhance forecasting and trading programs of renewable energies. This paper proposes a novel distributed decentralized prediction method for the management of VPPs. The novelty of the proposed technique is to effectively combine the concepts of neural networks and machine learning with a distributed architecture that is suitable for the aggregation purposes of the VPP.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IEEE Transactions on...arrow_drop_down
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    IEEE Transactions on Industry Applications
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    IEEE Transactions on Industry Applications
    Article . 2019 . Peer-reviewed
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    Authors: orcid bw Araneo R.;
    Araneo R.
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    orcid bw Celozzi S.;
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    Faria J. B.; Andreotti A.; +1 Authors

    We investigate the improvement of the lightning performance of overhead distribution lines by additional ground wires placed beneath phase conductors. We adopt a time-domain method based on the matrix formalism of multiconductor (MTL) transmission lines that allows for the computation of overvoltages across insulator strings, when direct lightning hits a tower or a ground wire.

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    Authors: orcid bw Araneo R.;
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    orcid bw Celozzi S.;
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    Faria J. B.; Andreotti A.; +1 Authors

    We investigate the improvement of the lightning performance of overhead distribution lines by additional ground wires placed beneath phase conductors. We adopt a time-domain method based on the matrix formalism of multiconductor (MTL) transmission lines that allows for the computation of overvoltages across insulator strings, when direct lightning hits a tower or a ground wire.

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    Authors: orcid bw Gianfranco Di Lorenzo;
    Gianfranco Di Lorenzo
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    orcid Erika Stracqualursi;
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    Over the past decade, decarbonization and environmental issues have taken a key role in worldwide politics [...]

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    Energies
    Article . 2022 . Peer-reviewed
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    Authors: orcid bw Gianfranco Di Lorenzo;
    Gianfranco Di Lorenzo
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    orcid Erika Stracqualursi;
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    orcid Rodolfo ARANEO;
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    Over the past decade, decarbonization and environmental issues have taken a key role in worldwide politics [...]

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    Energies
    Article . 2022 . Peer-reviewed
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: orcid bw Cristina Moscatiello;
    Cristina Moscatiello
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    orcid Riccardo Loggia;
    Riccardo Loggia
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    orcid bw Gianfranco di Lorenzo;
    Gianfranco di Lorenzo
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    orcid Alessandro Lorenzo Palma;
    Alessandro Lorenzo Palma
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    Alessandro Lorenzo Palma in OpenAIRE
    +6 Authors

    In recent years the development of LVDC distribution networks is under consideration. DC electrical distributions offer several advantages compared to AC ones in many applications, in particular in the presence of energy storage systems and distributed generation like high efficacy, flexibility and simple integration of renewables. The DC distribution allows to integrate in a more efficient “microgrid” different sources with DC/DC converters. The paper proposes an innovative model of microgrid configuration for aggregations of end-users able to share the power produced by common generators and energy services named by the authors Power Sharing Model (PSM) using a DC bus that connects in a one way approach, the common generators to the end-users. The paper investigates on the different suggested configurations of the PSM, with the converter characteristics and controls. A simplified case study is analyzed to test the performance of the sharing model and the stability of the control in different scenarios. The paper compares the PSM based on a LVDC grid with existing approaches of virtual aggregations, and it highlights the main differences between the currently existing methods and our new LVDC microgrid approach. The suggested PSM appears more efficient, convenient and flexible than the existing virtual models, because users physically self-consume and share the energy locally generated.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
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    IEEE Transactions on Industry Applications
    Article . 2023 . Peer-reviewed
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    Authors: orcid bw Cristina Moscatiello;
    Cristina Moscatiello
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    Cristina Moscatiello in OpenAIRE
    orcid Riccardo Loggia;
    Riccardo Loggia
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    Riccardo Loggia in OpenAIRE
    orcid bw Gianfranco di Lorenzo;
    Gianfranco di Lorenzo
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    Gianfranco di Lorenzo in OpenAIRE
    orcid Alessandro Lorenzo Palma;
    Alessandro Lorenzo Palma
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    Alessandro Lorenzo Palma in OpenAIRE
    +6 Authors

    In recent years the development of LVDC distribution networks is under consideration. DC electrical distributions offer several advantages compared to AC ones in many applications, in particular in the presence of energy storage systems and distributed generation like high efficacy, flexibility and simple integration of renewables. The DC distribution allows to integrate in a more efficient “microgrid” different sources with DC/DC converters. The paper proposes an innovative model of microgrid configuration for aggregations of end-users able to share the power produced by common generators and energy services named by the authors Power Sharing Model (PSM) using a DC bus that connects in a one way approach, the common generators to the end-users. The paper investigates on the different suggested configurations of the PSM, with the converter characteristics and controls. A simplified case study is analyzed to test the performance of the sharing model and the stability of the control in different scenarios. The paper compares the PSM based on a LVDC grid with existing approaches of virtual aggregations, and it highlights the main differences between the currently existing methods and our new LVDC microgrid approach. The suggested PSM appears more efficient, convenient and flexible than the existing virtual models, because users physically self-consume and share the energy locally generated.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
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    IEEE Transactions on Industry Applications
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    Authors: orcid Antonello Rosato;
    Antonello Rosato
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    orcid Rodolfo Araneo;
    Rodolfo Araneo
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    orcid Amedeo Andreotti;
    Amedeo Andreotti
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    orcid Federico Succetti;
    Federico Succetti
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    +1 Authors

    Here, we propose a new deep learning scheme to solve the energy time series prediction problem. The model implementation is based on the use of Long Short-Term Memory networks and Convolutional Neural Networks. These techniques are combined in such a fashion that inter-dependencies among several different time series can be exploited and used for forecasting purposes by filtering and joining their samples. The resulting learning scheme can be summarized as a superposition of network layers, resulting in a stacked deep neural architecture. We proved the accuracy and robustness of the proposed approach by testing it on real-world energy problems.

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    Energies
    Article . 2021 . Peer-reviewed
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      Energies
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      Energies
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    Authors: orcid Antonello Rosato;
    Antonello Rosato
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    orcid Rodolfo Araneo;
    Rodolfo Araneo
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    orcid Amedeo Andreotti;
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    orcid Federico Succetti;
    Federico Succetti
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    Here, we propose a new deep learning scheme to solve the energy time series prediction problem. The model implementation is based on the use of Long Short-Term Memory networks and Convolutional Neural Networks. These techniques are combined in such a fashion that inter-dependencies among several different time series can be exploited and used for forecasting purposes by filtering and joining their samples. The resulting learning scheme can be summarized as a superposition of network layers, resulting in a stacked deep neural architecture. We proved the accuracy and robustness of the proposed approach by testing it on real-world energy problems.

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    Energies
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    Energies
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      Energies
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    Authors: orcid bw Di Lorenzo G.;
    Di Lorenzo G.
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    orcid bw Rotondo S.;
    Rotondo S.
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    Abstract The paper proposes an innovative power-sharing model, i.e., a power-system architecture for aggregation of users able to share the power produced by common generators and energy services. The model is suitable for both multi-tenant buildings and groups of multiple buildings and it is applicable for both existing and new buildings. It is scalable for larger systems and suitable for an easier integration with storage systems. The novel principle of the model is that the energy produced by common generators can be shared among the end-users in a unidirectional way, so that each user remains passive towards the distributor, except a single active user that assumes the role of balance node. This key feature allows for easily implementing the model in all the residential and tertiary multi-units buildings in full compliance with national regulations, with the adoption of power sharing contracts as well. This paper discusses the feasibility of the model through a dynamic Matlab/Simulink model, which is used to show its effectiveness in several case studies. The significance of this work consists of approaching the energy sharing in buildings with a completely new strategy, based on an innovative system architecture that can be effectively implemented.

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    Article . 2021 . Peer-reviewed
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    Authors: orcid bw Di Lorenzo G.;
    Di Lorenzo G.
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    Abstract The paper proposes an innovative power-sharing model, i.e., a power-system architecture for aggregation of users able to share the power produced by common generators and energy services. The model is suitable for both multi-tenant buildings and groups of multiple buildings and it is applicable for both existing and new buildings. It is scalable for larger systems and suitable for an easier integration with storage systems. The novel principle of the model is that the energy produced by common generators can be shared among the end-users in a unidirectional way, so that each user remains passive towards the distributor, except a single active user that assumes the role of balance node. This key feature allows for easily implementing the model in all the residential and tertiary multi-units buildings in full compliance with national regulations, with the adoption of power sharing contracts as well. This paper discusses the feasibility of the model through a dynamic Matlab/Simulink model, which is used to show its effectiveness in several case studies. The significance of this work consists of approaching the energy sharing in buildings with a completely new strategy, based on an innovative system architecture that can be effectively implemented.

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    Renewable Energy
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