Intelligent Control in Energy Systems

• Príomhchruthaitheoir: Dounis, Anastasios (auth)
• Formáid: Leictreonach Caibidil leabhair
• Teanga: Béarla
• Foilsithe / Cruthaithe: MDPI - Multidisciplinary Digital Publishing Institute 2019
• Ábhair: 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
• Rochtain ar líne: DOAB: download the publication; DOAB: description of the publication

Achoimre

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.

Cur síos fisiciúil

1 electronic resource (508 p.)

ISBN

books978-3-03921-416-7
9783039214150
9783039214167

Rochtain

Open Access