Data-Intensive Computing in Smart Microgrids

• Autres auteurs: Herodotou, Herodotos (Éditeur intellectuel)
• Format: Électronique Chapitre de livre
• Langue: anglais
• Publié: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Sujets: Technology: general issues; electricity load forecasting; smart grid; feature selection; Extreme Learning Machine; Genetic Algorithm; Support Vector Machine; Grid Search; AMI; TL; SG; NB-PLC; fog computing; green community; resource allocation; processing time; response time; green data center; microgrid; renewable energy; energy trade contract; real time power management; load forecasting; optimization techniques; deep learning; big data analytics; electricity theft detection; smart grids; electricity consumption; electricity thefts; smart meter; imbalanced data; data-intensive smart application; cloud computing; real-time systems; multi-objective energy optimization; renewable energy sources; wind; photovoltaic; demand response programs; energy management; battery energy storage systems; demand response; scheduling; automatic generation control; single/multi-area power system; intelligent control methods; virtual inertial control; soft computing control methods; n/a
• Accès en ligne: DOAB: download the publication; DOAB: description of the publication

Microgrids have recently emerged as the building block of a smart grid, combining distributed renewable energy sources, energy storage devices, and load management in order to improve power system reliability, enhance sustainable development, and reduce carbon emissions. At the same time, rapid adva...