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Energies SI Book "Selected Papers from the ICEUBI2019 – International Congress on Engineering – Engineering for Evolution", groups six papers into fundamental engineering areas: Aeronautics and Astronautics, and Electrotechnical and Mechanical Engineering. ICEUBI—International Congress on Engineering is organized every two years by the Engineering Faculty of Beira Interior University, Portugal, promoting engineering in society through contact among researchers and practitioners from different fields of engineering, and thus encouraging the dissemination of engineering research, innovation, and development. All selected papers are interrelated with energy topics (fundamentals, sources, exploration, conversion, and policies), and provide relevant data for academics, research-focused practitioners, and policy makers.

HVAC --- water-cooled condenser --- air-cooled condenser --- evaporative --- TWI --- turbulence modeling --- supercritical injection --- Liquid Rocket Engines --- energy saving and efficiency --- aerodynamic coefficients --- propulsive efficiency --- bioenergetics --- biomimetics --- grid-tied inverter --- grey wolf optimizer --- PR controllers --- LCL filter --- passive damping --- propeller --- aircraft --- turboprop --- flight efficiency --- flight speed --- hydro-thermal coordination --- Lagrangian relaxation --- Lagrangian dual problem --- Lagrange multipliers --- subgradient methods --- step-size update algorithm

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Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms.

Technology: general issues --- global optimization --- cuckoo search algorithm --- Q-learning --- mutation --- self-adaptive step size --- evolutionary computation --- playtesting --- game feature --- game simulation --- game trees --- playtesting metric --- validation --- Pareto optimality --- h-index --- ranking --- dominance --- Pareto-front --- multi-indicators --- multi-metric --- multi-resources --- citation --- universities ranking --- swarm intelligence --- simulated annealing --- krill herd --- particle swarm optimization --- quantum --- elephant herding optimization --- engineering optimization --- metaheuristic --- constrained optimization --- multi-objective optimization --- single objective optimization --- differential evolution --- success-history --- premature convergence --- turning-based mutation --- opposition-based learning --- ant colony optimization --- opposite path --- traveling salesman problems --- whale optimization algorithm --- WOA --- binary whale optimization algorithm --- bWOA-S --- bWOA-V --- feature selection --- classification --- dimensionality reduction --- menu planning problem --- evolutionary algorithm --- decomposition-based multi-objective optimisation --- memetic algorithm --- iterated local search --- diversity preservation --- single-objective optimization --- knapsack problem --- travelling salesman problem --- seed schedule --- many-objective optimization --- fuzzing --- bug detection --- path discovery --- evolutionary algorithms (EAs) --- coevolution --- dynamic learning --- performance indicators --- magnetotelluric --- one-dimensional inversions --- geoelectric model --- optimization problem --- multi-task optimization --- multi-task evolutionary computation --- knowledge transfer --- assortative mating --- unified search space --- quantum computing --- grey wolf optimizer --- 0-1 knapsack problem --- green shop scheduling --- fuzzy hybrid flow shop scheduling --- discrete artificial bee colony algorithm --- minimize makespan --- minimize total energy consumption --- global optimization --- cuckoo search algorithm --- Q-learning --- mutation --- self-adaptive step size --- evolutionary computation --- playtesting --- game feature --- game simulation --- game trees --- playtesting metric --- validation --- Pareto optimality --- h-index --- ranking --- dominance --- Pareto-front --- multi-indicators --- multi-metric --- multi-resources --- citation --- universities ranking --- swarm intelligence --- simulated annealing --- krill herd --- particle swarm optimization --- quantum --- elephant herding optimization --- engineering optimization --- metaheuristic --- constrained optimization --- multi-objective optimization --- single objective optimization --- differential evolution --- success-history --- premature convergence --- turning-based mutation --- opposition-based learning --- ant colony optimization --- opposite path --- traveling salesman problems --- whale optimization algorithm --- WOA --- binary whale optimization algorithm --- bWOA-S --- bWOA-V --- feature selection --- classification --- dimensionality reduction --- menu planning problem --- evolutionary algorithm --- decomposition-based multi-objective optimisation --- memetic algorithm --- iterated local search --- diversity preservation --- single-objective optimization --- knapsack problem --- travelling salesman problem --- seed schedule --- many-objective optimization --- fuzzing --- bug detection --- path discovery --- evolutionary algorithms (EAs) --- coevolution --- dynamic learning --- performance indicators --- magnetotelluric --- one-dimensional inversions --- geoelectric model --- optimization problem --- multi-task optimization --- multi-task evolutionary computation --- knowledge transfer --- assortative mating --- unified search space --- quantum computing --- grey wolf optimizer --- 0-1 knapsack problem --- green shop scheduling --- fuzzy hybrid flow shop scheduling --- discrete artificial bee colony algorithm --- minimize makespan --- minimize total energy consumption

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Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms.

Technology: general issues --- global optimization --- cuckoo search algorithm --- Q-learning --- mutation --- self-adaptive step size --- evolutionary computation --- playtesting --- game feature --- game simulation --- game trees --- playtesting metric --- validation --- Pareto optimality --- h-index --- ranking --- dominance --- Pareto-front --- multi-indicators --- multi-metric --- multi-resources --- citation --- universities ranking --- swarm intelligence --- simulated annealing --- krill herd --- particle swarm optimization --- quantum --- elephant herding optimization --- engineering optimization --- metaheuristic --- constrained optimization --- multi-objective optimization --- single objective optimization --- differential evolution --- success-history --- premature convergence --- turning-based mutation --- opposition-based learning --- ant colony optimization --- opposite path --- traveling salesman problems --- whale optimization algorithm --- WOA --- binary whale optimization algorithm --- bWOA-S --- bWOA-V --- feature selection --- classification --- dimensionality reduction --- menu planning problem --- evolutionary algorithm --- decomposition-based multi-objective optimisation --- memetic algorithm --- iterated local search --- diversity preservation --- single-objective optimization --- knapsack problem --- travelling salesman problem --- seed schedule --- many-objective optimization --- fuzzing --- bug detection --- path discovery --- evolutionary algorithms (EAs) --- coevolution --- dynamic learning --- performance indicators --- magnetotelluric --- one-dimensional inversions --- geoelectric model --- optimization problem --- multi-task optimization --- multi-task evolutionary computation --- knowledge transfer --- assortative mating --- unified search space --- quantum computing --- grey wolf optimizer --- 0-1 knapsack problem --- green shop scheduling --- fuzzy hybrid flow shop scheduling --- discrete artificial bee colony algorithm --- minimize makespan --- minimize total energy consumption

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This book offers a collection of 30 scientific papers which address the problems associated with the use of power electronic converters in renewable energy source-based systems. Relevant problems associated with the use of power electronic converters to integrate renewable energy systems to the power grid are presented. Some of the covered topics relate to the integration of photovoltaic and wind energy generators into the rest of the system, and to the use of energy storage to mitigate power fluctuations, which are a characteristic of renewable energy systems. The book provides a good overview of the abovementioned topics.

n/a --- washout filter --- turbine and generator --- unbalanced power grid --- PV --- transient dynamics --- multi-input single output (MISO) --- permanent magnet synchronous generator (PMSG) --- static frequency characteristics --- impedance analysis --- FACTS devices --- coordinated control --- improved additional frequency control --- experiment --- resonant controller --- two-stage photovoltaic power --- voltage cancellation --- energy --- power matching --- LCL filter --- adaptive-MPPT (maximum power point tracking) --- VSC --- active power filter --- perturb and observe --- coordination control --- voltage-type control --- multiple VSGs --- wind power prediction --- linear quadratic regulator --- multiport converter (MPC) --- grid support function --- power ripple elimination --- adaptive resonant controller --- phase space reconstruction --- sliding mode control --- impedance emulation --- photovoltaic systems --- grid-connected converter --- SVM --- photovoltaic generators --- power grid --- active front-end converter --- THD --- type-4 wind turbine --- inertia --- ROCOF --- microgrid --- coupled oscillators --- multilevel power converter --- DC-AC power converters --- internal model --- back-to-back converter --- duty-ratio constraints --- selective harmonic mitigation --- parallel inverters --- discontinuous conduction mode --- droop control --- step size --- grid-connected --- inverter --- short-circuit fault --- energy router --- oscillation mitigation --- improved-VSG (virtual synchronous generator) --- source and load impedance --- synchronverter --- digital signal processor (DSP) TMS320F28335 --- operation optimization --- battery-energy storage --- generator speed control --- electrical power generation --- virtual impedance --- weak grid --- doubly-fed induction generator --- grid synchronization --- Energy Internet --- open circuit voltage --- state-of-charge balancing --- renewable power system --- control strategies --- adaptive notch filter (ANF) --- renewable energy --- hardware in the loop (HIL) --- energy storage --- microgrids --- inertia and damping characteristics --- electric vehicle --- multi-energy complementary --- static compensator --- stability --- battery energy storage system --- power-hardware-in- the-loop --- electricity price --- notch filter --- time series --- distorted grid --- oscillation suppression --- phase-locked loop (PLL) --- modules --- organic Rankine cycle --- failure zone --- Opal-RT Technologies® --- distributed generation --- modular multilevel converter --- governor --- microgrid (MG) --- second-life battery --- thermoelectric generator --- stability analysis --- wind energy system --- variable coefficient regulation --- single ended primary inductor converter (SEPIC) --- error --- soft switching --- power electronics --- PLL --- SPWM --- virtual synchronous generator --- perturbation frequency --- phase shifted --- grid-connected inverter --- cloud computing --- low inertia --- boost converter --- impedance reshaping --- small-signal and transient stability --- speed control --- multivariate linear regression --- photovoltaic --- adaptive control --- frequency regulation --- variable power tracking control --- power converters --- maximum power point tracking --- virtual admittance --- synchronization --- peak-current-mode control --- dynamic modeling --- discontinuous operation mode --- demand response