Cover Image

Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization

In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced mo...

Full description

Saved in:
Bibliographic Details
Other Authors: Deschrijver, Dirk (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Technology: general issues
passive house
enclosure structure
heat transfer coefficient
energy consumption
turbo-propeller
regional
fuel
weight
range
design
CO2 reduction
multi-objective combinatorial optimization
meta-heuristics
ant colony optimization
non-intrusive load monitoring
appliance classification
appliance feature
recurrence graph
weighted recurrence graph
V-I trajectory
convolutional neural network
energy baselines
machine learning
clustering
neural methods
smart intelligent systems
building energy consumption
building load forecasting
energy efficiency
thermal improved of buildings
anti-icing
heat and mass transfer
heating power distribution
heat load reduction
optimization method
experimental validation
big data process
predictive maintenance
fracturing roofs to maintain entry (FRME)
field measurement
numerical simulation
side abutment pressure
strata movement
energy
manufacturing
prediction
forecasting
modelling
n/a
Online Access:DOAB: download the publication
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems.
Physical Description:1 electronic resource (201 p.)
ISBN:books978-3-0365-1206-8
9783036512075
9783036512068
Access:Open Access

Similar Items