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Data-Intensive Computing in Smart Microgrids

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...

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Enregistré dans:
Format: Online
Langue:anglais
Publié: MDPI - Multidisciplinary Digital Publishing Institute 2022
Sujets:
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
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Accès en ligne:ONIX_20220111_9783036516271_513
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