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Intelligent Control in Energy Systems

The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submi...

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Hovedforfatter: Dounis, Anastasios
Format: Online
Sprog:engelsk
Udgivet: MDPI - Multidisciplinary Digital Publishing Institute 2021
Fag:
Q1-390
QC1-999
energy management system
artificial neural network
control architecture
intelligent buildings
sensitivity analysis
neural networks
active balance
photovoltaic system
fast frequency response
artificial intelligence
MPPT operation
model uncertainty
load frequency control
decision tree
multi-agent control
hybrid power plant
Fault Ride Through Capability
optimization
small scale compressed air energy storage (SS-CAES)
smart micro-grid
current distortion
hybrid electric vehicle
parameter estimation
railway
ANFIS
solar monitoring system
urban microgrids
phase-load balancing
model reduction
high-speed railway
energy internet
coordination of reserves
differential evolution
photovoltaic array
ancillary service
adjacent areas
instantaneous optimization minimum power loss
model predictive control
HVAC systems
sliding mode control
MPPT: maximum power point tracking
power oscillations
thyristor
interaction minimization
occupancy model
fuzzy logic controller
power transformer winding
RLS
integrated energy systems
vibration characteristics
battery safety
error estimation
error compensation
static friction
convolutional neural network
forecasting
continuous voltage control
medium voltage
bridgeless SEPIC PFC converter
building climate control
PEM fuel cell
proton exchange membrane fuel cell
compound structured permanent-magnet motor
occupancy-based control
four phases interleaved boost converter
long short term memory
line switching
lithium-ion battery pack
back propagation (BP) neural network
doubly-fed induction generator
double forgetting factors
current controller design
repetitive controller
exhaust gas recirculation (EGR) valve system
neural network controller
step-up boost converter
internal short circuit resistance
electric power consumption
electric vehicle
multiphysical field analysis
energy efficiency
multi-energy complementary
system identification
?-synthesis
network sensitivity
intelligent control
?-class function
frequency support
multi-step forecasting
frequency containment reserve
orthogonal least square
rule-based control
industrial process
hierarchical Petri nets
wind integrated power system
probabilistic power flow
voltage controlling
adaptive backstepping
AC-DC converters
line loss
demand side management
energy systems
short-circuit experiment
winding-fault characteristics
neutral section
stochastic power system operating point drift
neural network algorithm
operation limit violations
fractional order fuzzy PID controller
preventive control
AC static switch
battery packs
model-based fault detection
automotive application
nonlinear power systems
adaptive damping control
pilot point
energy management
position control
frequency control dead band
fuzzy
voltage violations
distribution network planning
frequency regulation
energy management strategy
multiple-point control
electric meter
polynomial expansion
commercial/residential buildings
system modelling
three-stage
soft internal short circuit
demand response
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Summary:The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust ?-synthesis for microgrids, and neuro-fuzzy systems in energy storage.

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