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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and MixedInteger Programming to the most modern methods based on bioinspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and MixedInteger Programming to the most modern methods based on bioinspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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This book includes the seven papers that contributed to the Special Issue of Mathematics entitled “Mathematical Methods in Applied Sciences”. The papers are authored by eminent specialists and aim at presenting to a broad audience some mathematical models which appear in different aspects of modern life. New results in Computational Mathematics are given as well. Emphasis is on Medicine and Public Health, in relation also with Social Sciences. The models in this collection apply in particular to the study of brain cells during a stroke, training management efficiency for elite athletes, and optimal surgical operation scheduling. Other models concern Industry and Economy, as well as Biology and Chemistry. Numerical Methods are represented in particular by scattered data interpolation, spectral collocation, and the use of eigenvalues and eigenvectors of the Laplacian matrix. This book will appeal to scientists, teachers, and graduate students in Mathematics, in particular Numerical Analysis, and will be of interest for scholars in Applied Sciences, particularly in Medicine and Public Health.
Laplacian matrix  power flow  admittance matrix  voltage profile  scheduling  operating room scheduling  goal programming  constraint programming  state hospital  spectral collocation method  population balance equation  Chebyshev points  crystallization  shift schedule  goal programming  labor  assignment  personnel  athletes’ condition  approximation  parameter estimation  least squares method  visualization  chemokines  cytokines  eigenvalue stability analysis  neurogenesis  numerical solution  system of ordinary differential equations  scattered data interpolation  cubic timmer triangular patches  cubic ball triangular patches  cubic Bezier triangular patches  convex combination
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The Special Issue Distributed Energy Resources Management 2018 includes 13 papers, and is a continuation of the Special Issue Distributed Energy Resources Management. The success of the previous edition shows the unquestionable relevance of distributed energy resources in the operation of power and energy systems at both the distribution level and at the wider power system level. Improving the management of distributed energy resources makes it possible to accommodate the higher penetration of intermittent distributed generation and electric vehicle charging. Demand response programs, namely the ones with a distributed nature, allow the consumers to contribute to the increased system efficiency while receiving benefits. This book addresses the management of distributed energy resources, with a focus on methods and techniques to achieve an optimized operation, in order to aggregate the resources namely in the scope of virtual power players and other types of aggregators, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as an enabler for their increased and efficient use.
clustering  demand Response  distributed generation  smart grids  demandside management  multiagent system  distributed coordination  distributed energy resources  swarm intelligence  virtual power plant  distributed energy resources  multiagent technology  bidding strategy  stackelberg dynamic game  aggregator  distribution system operator  distributed energy resources  local flexibility market  flexibility service  distributed energy  comprehensive benefits  multiagent synergetic estimation  synergistic optimization strategy  control system  faulttolerant control  algorithm design and analysis  IoT (Internet of Things)  nonlinear control  optimization  DSM  microgrid  solar  wind  teachinglearning  microgrid  energy storage system  distributed generator  frequency control  active power control  autonomous control  droop control  frequency bussignaling  batteries  energy storage  microgrids  optimal scheduling  particle swarm optimization  power system management  smart grid  supply and demand  trade agreements  low voltage networks  multiperiod optimal power flow  multitemporal optimal power flow  active distribution networks  unbalanced networks  indoor environment quality  occupant comfort  building climate control  healthy building  energy efficiency  adaptability  decentralized energy management system  local energy trading  multiagent system  optimization  smart grid  demand response  distributed generation  particle swarm optimization  prosumer  n/a
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This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.
seawater pumped storage  renewable energy  active distribution networks  twostage  scheduling  distributed generation  storage device  MILP  ToU tariff  optimization  daily consumption curve  peak/offpeak  programmable appliances  smart grid  smart energy  sustainability  values  technology acceptance  technology adoption  smart grid  Smart Grid Station  renewable energy sources  energy management system  smart metering  feedback  households  energy and water consumption  theories of social practice  smart grid  differentiation  development demand  comprehensive evaluation  energy management system  energy storage system  semantic web technologies  rules  ontology  engineering support  smart grid architecture model  model driven architecture  IEC 61850  IEC 61499  energy storage system  electricity charge discount program  peak reduction  economic feasibility analysis  policy effectiveness evaluation  occupant behavior  singleperson household  energy consumption  Korean Time Use Survey  EnergyPlus  data mining  Kmodes clustering  support vector machine  Gaussian process regression  combined dispatch (CD) strategy  optimization  HOMER  net present cost (NPC)  sensitivity analysis  renewable energy  solar power generation prediction  smart grid  photovoltaic power  machine learning  electrical distribution system  graph theory  micro grids  heuristic  optimization  planning  unbalanced threephase distribution networks  optimal power flows  genetic algorithm  holomorphic embedding load flow method  simulation  forecasting  solar generation  storage capacity  game theory  nash equilibrium  distributed energy management algorithm  micro grid  meta heuristic techniques  R&  D planning  patent analysis  sustainable smart grid technology  R&  D strategy  STEEP analysis  scenario planning  electric vehicle charging technology  multilayer perceptron neural network  support vector machine  cyberattacks  optimal power flow  smart grid security  intruder detection system
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Electrical power systems are evolving at the generation, transmission, and distribution levels. At distribution level, small generating and storage units—the socalled distributed energy sources (DERs)—are being installed close to consumption sites. The expansion of DERs is empowering renewable energy source integration and, as a consequence, new actors are appearing in electrical systems. Among them, the prosumer is a gamechanger; the fruit of the behavior transformation of the consumer who has not only the ability to consume power but also to produce it. Microgrids can be understood as DER installations that have the capability of both gridconnected and gridisolated operation. During the last decades, there has been a significant deployment of microgrids (e.g., in countries like the United States, Switzerland, and Denmark) and a consequent increase in renewable energy generation. This is contributing to the decarbonization of electrical power systems. However, the variability and intermittency of renewable sources introduce uncertainty, which implies a more complex operation and control. Taking into account that existing and future planned microgrids are being/going to be interconnected to the current electrical network, challenges in terms of design, operation, and control at power system level need to be addressed, considering existing regulations.
demandside management  optimization  deterministic optimization  stochastic optimization  residential users  devices scheduling  renewable sources  storage systems  electric energy market  power quality  chaos synchronization detection  extension theory  direct search method (DSM)  microgrid (MG)  distributed energy resources (DERs)  distributed generation (DG)  optimal dispatch  microgrids  multiagent  coordinated control  IEC 61850 Standard  generic object oriented substation event (GOOSE) communication  power quality disturbances  Stransform  multiresolution  particle swarm optimization  decision tree  reliability evaluation  microgrid  distributed generation  battery storage  vehicletogrid  ruleless EV  regular EV  combined power generation system  microgrid  coordinative optimization of energy  predictive control  genetic algorithm  distributed generation (DG)  microgrid  microgrid stability controller (MSC)  total slidingmode control  hierarchical control scheme  maximum electrical efficiency  nonlinear programming  solid oxide fuel cell  electric vehicle (EV)  vehicletogrid (V2G)  isolated grid  load frequency control (LFC)  multivariable generalized predictive control (MGPC)  current harmonic reduction  active filter  power quality  buckboost converter  renewable energy source  optimal capacity  reliability  renewable  energy storage  genetic algorithm  DC microgrid  communication delay  droop control  load power sharing  mesh configuration  radial configuration  electric vehicle  energy management system  peakshift  peakcut  vehicle information system  photovoltaic feasibility  flexible generation  distributed energy resources  power quality  DC distribution  DC microgrid  inrush current  grounding  DC architectures  datacenter  residential power systems  telecommunication power management  smart grids  microgrid  network planning  power distribution  grid independence  distributed energy resources  microgrid  IEC 61850  plug and play  operation  smallscale standalone microgrid  HESS  ESS effective rate  coordinated control strategy  cost and life  technical and economic optimization  microgrid  flywheel energy storage (FES)  doubly fed induction machine  frequency control  smoothing wind power  distributed generation  congestion problems  mediumvoltage networks  curtailment  flexibility  microgrid test facility  distributed generation  integrated electrical and thermal grids  flexible and configurable architecture  energy efficiency  distributed optimization  optimal power flow  microgrids  embedded system  smart grid  smart inverter  distributed energy resource  power quality
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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 neurofuzzy systems in energy storage.
lithiumion battery pack  soft internal short circuit  modelbased fault detection  battery safety  internal short circuit resistance  load frequency control  model uncertainty  ?synthesis  differential evolution  decision tree  preventive control  Fault Ride Through Capability  doublyfed induction generator  ancillary service  frequency regulation  demand response  commercial/residential buildings  HVAC systems  model predictive control  rulebased control  position control  static friction  exhaust gas recirculation (EGR) valve system  automotive application  hybrid electric vehicle  compound structured permanentmagnet motor  energy management strategy  instantaneous optimization minimum power loss  back propagation (BP) neural network  power transformer winding  vibration characteristics  multiphysical field analysis  shortcircuit experiment  windingfault characteristics  occupancy model  occupancybased control  model predictive control  energy efficiency  building climate control  solar monitoring system  photovoltaic array  energy management  demand side management  operation limit violations  probabilistic power flow  network sensitivity  neural networks  railway  highspeed railway  neutral section  medium voltage  thyristor  AC static switch  adaptive backstepping  nonlinear power systems  sliding mode control  error compensation  ?class function  energy internet  multienergy complementary  integrated energy systems  distribution network planning  electric power consumption  multistep forecasting  long short term memory  convolutional neural network  system identification  parameter estimation  system modelling  model reduction  polynomial expansion  orthogonal least square  industrial process  electric vehicle  battery packs  active balance  model predictive control  hierarchical Petri nets  urban microgrids  phaseload balancing  fuzzy logic controller  MPPT: maximum power point tracking  photovoltaic system  stepup boost converter  proton exchange membrane fuel cell  four phases interleaved boost converter  neural network controller  ACDC converters  bridgeless SEPIC PFC converter  repetitive controller  current distortion  current controller design  stochastic power system operating point drift  wind integrated power system  power oscillations  adaptive damping control  continuous voltage control  multiplepoint control  interaction minimization  pilot point  adjacent areas  ANFIS  artificial neural network  fuzzy  small scale compressed air energy storage (SSCAES)  voltage controlling  electric meter  error estimation  line loss  RLS  double forgetting factors  hybrid power plant  control architecture  coordination of reserves  frequency support  frequency control dead band  fast frequency response  frequency containment reserve  line switching  voltage violations  threestage  fractional order fuzzy PID controller  neural network algorithm  PEM fuel cell  MPPT operation  sensitivity analysis  intelligent control  artificial intelligence  energy management system  smart microgrid  energy systems  intelligent buildings  forecasting  multiagent control  optimization
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This book is a collection of scientific papers concerning multilevel inverters examined from different points of view. Many applications are considered, such as renewable energy interface, power conditioning systems, electric drives, and chargers for electric vehicles. Different topologies have been examined in both new configurations and wellestablished structures, introducing novel and particular modulation strategies, and examining the effect of modulation techniques on voltage and current harmonics and the total harmonic distortion.
DC–DC conversion  interleaved buck  parasitic switching states  threelevel converter  simplified PWM strategy  redundant switching combination  voltage balance control  modular multilevel converter  IGBT shortcircuit  fault detection  fault location  Differential Comparison LowVoltage Detection Method (DCLVDM)  Continuous Wavelet Transform  digital controller  digital signal processors (DSP)  modular multilevel converters (MMC)  multiterminal DC network (MTDC)  MMCMTDC  hybrid modulated model predictive control  optimal output voltage level  multipoint DC control  neutralpointclamped (NPC) inverter  dclink capacitor voltage balance  offset voltage injection  harmonic component  modular multilevel converters  capacitor voltage balancing  sorting networks  fieldprogrammable gate array  lowharmonic DC icemelting device  transmission line  voltage fluctuation  harmonic  dynamic reactive  substation’s voltage stability  alternating current (AC) motor drive  current estimation  current reconstruction method  current unmeasurable areas  total harmonic distortion (THD)  single shunt resistor  space vector pulse width modulation (SVPWM)  shift method  minimum voltage injection (MVI) method  threelevel neutral point clamped inverter (NPCI)  threelevel boost  automatic current balance  threeloop  voltage imbalance  DClink voltage balancing  fieldoriented control  fieldprogrammable gate array  multilevel activeclamped converter  motor drive  buckchopper  PVsimulator  Ttype converter  real time simulator  threelevel boost DCDC converter  small signal modeling  voltage balance control  multilevel converter  selected harmonic elimination  genetic algorithm  imperialist competitive algorithm  voltage ripple  voltage source inverter  threephase inverter  DClink capacitor design  Cascaded Hbridge multilevel inverter (CHBMI)  fieldprogrammable gate array  total harmonic distortion (THD)  modulation techniques  multilevel converter  electric vehicle  onboard battery charger  power factor correction  power quality  smart grid  model predictive control  singlephase threelevel NPC converter  commutation  modular multilevel converter (MMC)  Submodule (SM) fault  faulttolerant control  Phase Disposition PWM  finite control set model predictive control  Ttype inverter  computational cost  LC filter  DClink capacitor voltage balancing  multilevel converter  DC side fault blocking  predictive control  battery energy storage system (BESS)  modular multilevel converter (MMC)  stateofcharge (SOC) balancing control  tolerance for battery power unbalance  model predictive control (MPC)  computational burden  reverse prediction  modular multilevel converter (MMC)  multilevel inverters  total harmonic distortion  levelshifted PWM  phaseshifted PWM  electrical drives  energy saving  multilevel power converters  permanent magnet synchronous generator  openend winding configuration  voltage balancing  power factor  improved PQ algorithm  power flow analysis  threephase to singlephase cascaded converter  ACTPSS  NPC/H Bridge  fivelevel  Balance of capacitor voltage  Suppression of CMV  SVPWM  multilevel converter  multimotor drive  harmonic mitigation  active filter  open end winding motor  high efficiency drive  high reliability applications
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