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 outlines the potential role of Knowledge Discovery from massive Datasets in smart grid computing, presenting 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.
A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data
De Caro F.;Vaccaro A.;Villacci D.
2020-01-01
Abstract
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 outlines the potential role of Knowledge Discovery from massive Datasets in smart grid computing, presenting 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
