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In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria.

Unsicherheit Quantifizierung, generalized polynomial chaos, verteilt-parametrische Systeme, Sensitivitätsanalyse, ParameterschätzungUncertainty Quantification, generalized polynomial chaos, Distributed Parameter Systems, Sensitivity Analysis, Parameter estimation

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Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.

defect detection --- glass insulator --- localization --- self-shattering --- spatial features --- particle swarm optimization --- particle update mode --- inertia weight --- reactive power optimization --- Combustion efficiency --- NOx emissions constraints --- boiler load constraints --- least square support vector machine --- differential evolution algorithm --- model predictive control --- incipient cable failure --- VMD --- feature extraction --- CNN --- economic load dispatch --- emission dispatch --- combined economic emission/environmental dispatch --- particle swarm optimization --- genetic algorithm --- penalty factor approach --- long short term memory (LSTM) --- genetic algorithm (GA) --- short term load forecasting (STLF) --- electricity load forecasting --- multivariate time series --- grid observability --- active distribution system --- meter allocation --- parameter estimation

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In recent years, entropy has been used as a measure of the degree of chaos in dynamical systems. Thus, it is important to study entropy in nonlinear systems. Moreover, there has been increasing interest in the last few years regarding the novel classification of nonlinear dynamical systems including two kinds of attractors: self-excited attractors and hidden attractors. The localization of self-excited attractors by applying a standard computational procedure is straightforward. In systems with hidden attractors, however, a specific computational procedure must be developed, since equilibrium points do not help in the localization of hidden attractors. Some examples of this kind of system are chaotic dynamical systems with no equilibrium points; with only stable equilibria, curves of equilibria, and surfaces of equilibria; and with non-hyperbolic equilibria. There is evidence that hidden attractors play a vital role in various fields ranging from phase-locked loops, oscillators, describing convective fluid motion, drilling systems, information theory, cryptography, and multilevel DC/DC converters. This Special Issue is a collection of the latest scientific trends on the advanced topics of dynamics, entropy, fractional order calculus, and applications in complex systems with self-excited attractors and hidden attractors.

new chaotic system --- multiple attractors --- electronic circuit realization --- S-Box algorithm --- chaotic systems --- circuit design --- parameter estimation --- optimization methods --- Gaussian mixture model --- chaotic system --- empirical mode decomposition --- permutation entropy --- image encryption --- hidden attractors --- fixed point --- stability --- nonlinear transport equation --- stochastic (strong) entropy solution --- uniqueness --- existence --- multiscale multivariate entropy --- multistability --- self-reproducing system --- chaos --- hidden attractor --- self-excited attractor --- fractional order --- spectral entropy --- coexistence --- multistability --- chaotic flow --- hidden attractor --- multistable --- entropy --- core entropy --- Thurston’s algorithm --- Hubbard tree --- external rays --- chaos --- Lyapunov exponents --- multiple-valued --- static memory --- strange attractors --- fractional discrete chaos --- entropy --- projective synchronization --- full state hybrid projective synchronization --- generalized synchronization --- inverse full state hybrid projective synchronization --- inverse generalized synchronization --- multichannel supply chain --- service game --- chaos --- entropy --- BOPS --- Hopf bifurcation --- self-excited attractors --- multistability --- sample entropy --- PRNG --- Non-equilibrium four-dimensional chaotic system --- entropy measure --- adaptive approximator-based control --- neural network --- uncertain dynamics --- synchronization --- fractional-order --- complex-variable chaotic system --- unknown complex parameters --- chaotic map --- fixed point --- chaos --- approximate entropy --- implementation --- hidden attractor --- hyperchaotic system --- multistability --- entropy analysis --- hidden attractor --- complex systems --- fractional-order --- entropy --- chaotic maps --- chaos --- spatial dynamics --- Bogdanov Map --- chaos --- laser --- resonator

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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 Mixed-Integer Programming to the most modern methods based on bio-inspired 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 --- day-ahead load forecasting --- modular predictor --- feature selection --- micro-phasor measurement unit --- mutual information theory --- stochastic state estimation --- two-point estimation method --- JAYA algorithm --- multi-population 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 heat-electricity energy management --- eight searching sub-regions --- islanded microgrid --- dragonfly algorithm --- metaheuristic --- optimal power flow --- particle swarm optimization --- CCHP system --- energy storage --- off-design 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 --- pumped-hydro energy storage --- off-grid --- optimization --- HOMER software --- rural electrification --- sub-Saharan 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 --- multi-stakeholders --- discrete wind driven optimization --- multiobjective optimization --- optimal power flow --- metaheuristic --- wind energy --- photovoltaic --- smart grid --- transformer-fault 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 --- optimizing-scenarios method --- power flow --- wind power --- active distribution system --- virtual power plant --- stochastic optimization --- decentralized and collaborative optimization --- genetic algorithm --- multi-objective particle swarm optimization algorithm --- artificial bee colony --- IEEE Std. 80-2000 --- Schwarz’s equation --- fuzzy algorithm --- radial basis function --- neural network --- ETAP --- distributed generations (DGs) --- distribution network reconfiguration --- runner-root algorithm (RRA) --- inter-turn shorted-circuit 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 --- cross-entropy --- the genetic algorithm based P system --- the biomimetic membrane computing --- transient stability --- two-stage feature selection --- particle encoding method --- fitness function --- power factor compensation --- non-sinusoidal circuits --- geometric algebra --- evolutionary algorithms --- electric power contracts --- electric energy costs --- cost minimization --- evolutionary computation --- bio-inspired algorithms --- congestion management --- low-voltage networks --- multi-objective 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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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.

lithium-ion battery pack --- soft internal short circuit --- model-based fault detection --- battery safety --- internal short circuit resistance --- load frequency control --- model uncertainty --- ?-synthesis --- differential evolution --- decision tree --- preventive control --- Fault Ride Through Capability --- doubly-fed induction generator --- ancillary service --- frequency regulation --- demand response --- commercial/residential buildings --- HVAC systems --- model predictive control --- rule-based control --- position control --- static friction --- exhaust gas recirculation (EGR) valve system --- automotive application --- hybrid electric vehicle --- compound structured permanent-magnet motor --- energy management strategy --- instantaneous optimization minimum power loss --- back propagation (BP) neural network --- power transformer winding --- vibration characteristics --- multiphysical field analysis --- short-circuit experiment --- winding-fault characteristics --- occupancy model --- occupancy-based 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 --- high-speed railway --- neutral section --- medium voltage --- thyristor --- AC static switch --- adaptive backstepping --- nonlinear power systems --- sliding mode control --- error compensation --- ?-class function --- energy internet --- multi-energy complementary --- integrated energy systems --- distribution network planning --- electric power consumption --- multi-step 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 --- phase-load balancing --- fuzzy logic controller --- MPPT: maximum power point tracking --- photovoltaic system --- step-up boost converter --- proton exchange membrane fuel cell --- four phases interleaved boost converter --- neural network controller --- AC-DC 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 --- multiple-point control --- interaction minimization --- pilot point --- adjacent areas --- ANFIS --- artificial neural network --- fuzzy --- small scale compressed air energy storage (SS-CAES) --- 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 --- three-stage --- fractional order fuzzy PID controller --- neural network algorithm --- PEM fuel cell --- MPPT operation --- sensitivity analysis --- intelligent control --- artificial intelligence --- energy management system --- smart micro-grid --- energy systems --- intelligent buildings --- forecasting --- multi-agent control --- optimization