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Power converters and electric machines represent essential components in all fields of electrical engineering. In fact, we are heading towards a future where energy will be more and more electrical: electrical vehicles, electrical motors, renewables, storage systems are now widespread. The ongoing energy transition poses new challenges for interfacing and integrating different power systems. The constraints of space, weight, reliability, performance, and autonomy for the electric system have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this context, power converters and electric machines assume a key role in enabling higher performance of electrical power conversion. Consequently, the design and control of power converters and electric machines shall be developed accordingly to the requirements of the specific application, thus leading to more specialized solutions, with the aim of enhancing the reliability, fault tolerance, and flexibility of the next generation power systems.

Technology: general issues --- Energy industries & utilities --- power systems for renewable energy --- fault-tolerant photovoltaic inverter --- islanding detection --- energy storage system --- DC/AC converter --- voltage-source --- multilevel inverter --- PV systems --- neutral point clamped inverter --- flying capacitor inverter --- cascaded inverter --- renewable energy systems --- ultra-fast chargers --- input-series input-parallel output-series output-parallel multimodule converter --- cross feedback output current sharing --- reflex charging --- digital twin --- doubly-fed induction generator, electrical machines --- finite elements method --- monitoring --- real-time --- wound rotor induction machine --- subsynchronous control interaction --- super-twisting sliding mode --- variable-gain --- doubly fed induction generator --- photovoltaic system --- grid --- sliding mode control --- synergetic control --- fractional-order control --- converter–machine association --- direct drive machine --- Permanent Magnet Vernier Machine --- synchronous generator --- wind energy system for domestic applications --- renewable energy --- adaptive --- fuzzy --- feedback linearization --- photovoltaic (PV) grid inverter --- voltage source inverter (VSI) --- doubly-fed induction generator --- wind power system --- sensorless control --- full order observer --- field oriented control --- grid connected system --- lithium batteries --- los minimization --- Modular Multilevel Converters --- optimization methods

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• Reference Manager
• EndNote
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Power converters and electric machines represent essential components in all fields of electrical engineering. In fact, we are heading towards a future where energy will be more and more electrical: electrical vehicles, electrical motors, renewables, storage systems are now widespread. The ongoing energy transition poses new challenges for interfacing and integrating different power systems. The constraints of space, weight, reliability, performance, and autonomy for the electric system have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this context, power converters and electric machines assume a key role in enabling higher performance of electrical power conversion. Consequently, the design and control of power converters and electric machines shall be developed accordingly to the requirements of the specific application, thus leading to more specialized solutions, with the aim of enhancing the reliability, fault tolerance, and flexibility of the next generation power systems.

Technology: general issues --- Energy industries & utilities --- power systems for renewable energy --- fault-tolerant photovoltaic inverter --- islanding detection --- energy storage system --- DC/AC converter --- voltage-source --- multilevel inverter --- PV systems --- neutral point clamped inverter --- flying capacitor inverter --- cascaded inverter --- renewable energy systems --- ultra-fast chargers --- input-series input-parallel output-series output-parallel multimodule converter --- cross feedback output current sharing --- reflex charging --- digital twin --- doubly-fed induction generator, electrical machines --- finite elements method --- monitoring --- real-time --- wound rotor induction machine --- subsynchronous control interaction --- super-twisting sliding mode --- variable-gain --- doubly fed induction generator --- photovoltaic system --- grid --- sliding mode control --- synergetic control --- fractional-order control --- converter–machine association --- direct drive machine --- Permanent Magnet Vernier Machine --- synchronous generator --- wind energy system for domestic applications --- renewable energy --- adaptive --- fuzzy --- feedback linearization --- photovoltaic (PV) grid inverter --- voltage source inverter (VSI) --- doubly-fed induction generator --- wind power system --- sensorless control --- full order observer --- field oriented control --- grid connected system --- lithium batteries --- los minimization --- Modular Multilevel Converters --- optimization methods --- power systems for renewable energy --- fault-tolerant photovoltaic inverter --- islanding detection --- energy storage system --- DC/AC converter --- voltage-source --- multilevel inverter --- PV systems --- neutral point clamped inverter --- flying capacitor inverter --- cascaded inverter --- renewable energy systems --- ultra-fast chargers --- input-series input-parallel output-series output-parallel multimodule converter --- cross feedback output current sharing --- reflex charging --- digital twin --- doubly-fed induction generator, electrical machines --- finite elements method --- monitoring --- real-time --- wound rotor induction machine --- subsynchronous control interaction --- super-twisting sliding mode --- variable-gain --- doubly fed induction generator --- photovoltaic system --- grid --- sliding mode control --- synergetic control --- fractional-order control --- converter–machine association --- direct drive machine --- Permanent Magnet Vernier Machine --- synchronous generator --- wind energy system for domestic applications --- renewable energy --- adaptive --- fuzzy --- feedback linearization --- photovoltaic (PV) grid inverter --- voltage source inverter (VSI) --- doubly-fed induction generator --- wind power system --- sensorless control --- full order observer --- field oriented control --- grid connected system --- lithium batteries --- los minimization --- Modular Multilevel Converters --- optimization methods

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Power network operators are rapidly incorporating wind power generation into their power grids to meet the widely accepted carbon neutrality targets and facilitate the transition from conventional fossil-fuel energy sources to clean and low-carbon renewable energy sources. Complex stability issues, such as frequency, voltage, and oscillatory instability, are frequently reported in the power grids of many countries and regions (e.g., Germany, Denmark, Ireland, and South Australia) due to the substantially increased wind power generation. Control techniques, such as virtual/emulated inertia and damping controls, could be developed to address these stability issues, and additional devices, such as energy storage systems, can also be deployed to mitigate the adverse impact of high wind power generation on various system stability problems. Moreover, other wind power integration aspects, such as capacity planning and the short- and long-term forecasting of wind power generation, also require careful attention to ensure grid security and reliability. This book includes fourteen novel research articles published in this Energies Special Issue on Wind Power Integration into Power Systems: Stability and Control Aspects, with topics ranging from stability and control to system capacity planning and forecasting.

Technology: general issues --- Energy industries & utilities --- DFIG --- ES --- virtual inertia control --- capacity allocation --- fuzzy logic controller --- wind power generation --- multi-model predictive control --- fuzzy clustering --- virtual synchronous generator --- doubly fed induction generator --- sub-synchronous resonance --- impedance modeling --- renewable energy sources (RESs) --- regional RoCoF --- model-based operational planning --- linear sensitivity-based method (LSM) --- cumulant-based method (CBM) --- collaborative capacity planning --- distributed wind power (DWP) --- energy storage system (ESS) --- optimization --- variable-structure copula --- Reynolds-averaged Navier-Stokes method --- wind turbine wake model --- 3D aerodynamic model --- turbulence model --- correction modules --- hybrid prediction model --- wavelet decomposition --- long short-term memory --- scenario analysis --- weak grids --- full-converter wind --- active power output --- control parameters --- subsynchronous oscillation --- eigenvalue analysis --- doubly fed induction generator (DFIG) --- wind generation --- frequency control --- artificial neural network (ANN) --- error following forget gate-based long short-term memory --- ultra-short-term prediction --- wind power --- load frequency control (LFC) --- wind farm --- particle swarm optimization --- kinetic energy --- inertial response --- low inertia --- the center of inertia --- frequency response metrics --- wind integration --- PSS/E --- FORTRAN --- electromechanical dynamics --- FCWG dynamics --- strong interaction --- electromechanical loop correlation ratio (ELCR) --- FCWG dynamic correlation ratio (FDCR) --- quasi- electromechanical loop correlation ratio (QELCR) --- permanent magnet synchronous generator (PMSG) --- supercapacitor energy storage (SCES) --- rotor overspeed control --- low voltage ride through (LVRT) --- capacity configuration of SCES --- DFIG --- ES --- virtual inertia control --- capacity allocation --- fuzzy logic controller --- wind power generation --- multi-model predictive control --- fuzzy clustering --- virtual synchronous generator --- doubly fed induction generator --- sub-synchronous resonance --- impedance modeling --- renewable energy sources (RESs) --- regional RoCoF --- model-based operational planning --- linear sensitivity-based method (LSM) --- cumulant-based method (CBM) --- collaborative capacity planning --- distributed wind power (DWP) --- energy storage system (ESS) --- optimization --- variable-structure copula --- Reynolds-averaged Navier-Stokes method --- wind turbine wake model --- 3D aerodynamic model --- turbulence model --- correction modules --- hybrid prediction model --- wavelet decomposition --- long short-term memory --- scenario analysis --- weak grids --- full-converter wind --- active power output --- control parameters --- subsynchronous oscillation --- eigenvalue analysis --- doubly fed induction generator (DFIG) --- wind generation --- frequency control --- artificial neural network (ANN) --- error following forget gate-based long short-term memory --- ultra-short-term prediction --- wind power --- load frequency control (LFC) --- wind farm --- particle swarm optimization --- kinetic energy --- inertial response --- low inertia --- the center of inertia --- frequency response metrics --- wind integration --- PSS/E --- FORTRAN --- electromechanical dynamics --- FCWG dynamics --- strong interaction --- electromechanical loop correlation ratio (ELCR) --- FCWG dynamic correlation ratio (FDCR) --- quasi- electromechanical loop correlation ratio (QELCR) --- permanent magnet synchronous generator (PMSG) --- supercapacitor energy storage (SCES) --- rotor overspeed control --- low voltage ride through (LVRT) --- capacity configuration of SCES

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Power network operators are rapidly incorporating wind power generation into their power grids to meet the widely accepted carbon neutrality targets and facilitate the transition from conventional fossil-fuel energy sources to clean and low-carbon renewable energy sources. Complex stability issues, such as frequency, voltage, and oscillatory instability, are frequently reported in the power grids of many countries and regions (e.g., Germany, Denmark, Ireland, and South Australia) due to the substantially increased wind power generation. Control techniques, such as virtual/emulated inertia and damping controls, could be developed to address these stability issues, and additional devices, such as energy storage systems, can also be deployed to mitigate the adverse impact of high wind power generation on various system stability problems. Moreover, other wind power integration aspects, such as capacity planning and the short- and long-term forecasting of wind power generation, also require careful attention to ensure grid security and reliability. This book includes fourteen novel research articles published in this Energies Special Issue on Wind Power Integration into Power Systems: Stability and Control Aspects, with topics ranging from stability and control to system capacity planning and forecasting.

DFIG --- ES --- virtual inertia control --- capacity allocation --- fuzzy logic controller --- wind power generation --- multi-model predictive control --- fuzzy clustering --- virtual synchronous generator --- doubly fed induction generator --- sub-synchronous resonance --- impedance modeling --- renewable energy sources (RESs) --- regional RoCoF --- model-based operational planning --- linear sensitivity-based method (LSM) --- cumulant-based method (CBM) --- collaborative capacity planning --- distributed wind power (DWP) --- energy storage system (ESS) --- optimization --- variable-structure copula --- Reynolds-averaged Navier–Stokes method --- wind turbine wake model --- 3D aerodynamic model --- turbulence model --- correction modules --- hybrid prediction model --- wavelet decomposition --- long short-term memory --- scenario analysis --- weak grids --- full-converter wind --- active power output --- control parameters --- subsynchronous oscillation --- eigenvalue analysis --- doubly fed induction generator (DFIG) --- wind generation --- frequency control --- artificial neural network (ANN) --- error following forget gate-based long short-term memory --- ultra-short-term prediction --- wind power --- load frequency control (LFC) --- wind farm --- particle swarm optimization --- kinetic energy --- inertial response --- low inertia --- the center of inertia --- frequency response metrics --- wind integration --- PSS/E --- FORTRAN --- electromechanical dynamics --- FCWG dynamics --- strong interaction --- electromechanical loop correlation ratio (ELCR) --- FCWG dynamic correlation ratio (FDCR) --- quasi- electromechanical loop correlation ratio (QELCR) --- permanent magnet synchronous generator (PMSG) --- supercapacitor energy storage (SCES) --- rotor overspeed control --- low voltage ride through (LVRT) --- capacity configuration of SCES --- n/a --- Reynolds-averaged Navier-Stokes method

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Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering.

Technology: general issues --- doubly fed induction generator --- PI tuning --- LCL-filter --- passive damping --- advanced metaheuristics --- Bonferroni-Dunn and Friedman's tests --- resistance spot welding --- dynamic resistance model --- adaptive control --- energy savings --- adaptive disturbance rejection controller --- hybrid systems --- state constraint --- worm robot --- bio-inspired robots --- Streeter-Phelps model --- fractional-order control --- high observers --- river monitoring --- 3 DOF crane --- convex systems --- fault-tolerant control --- robust control --- qLPV systems --- Takagi-Sugeno systems --- chaos --- synchronization --- FPGA --- UDS --- distillation column heating actuator --- Buck-Boost converter --- Takagi-Sugeno model --- fuzzy observer with sliding modes --- nonlinear optimization --- turbulent flow --- friction factor --- pipe roughness --- minor losses --- PID control and variants --- Intelligent control techniques --- neural control --- brushless DC electric motors --- sensors and virtual instruments --- analysis and treatment of signals --- doubly fed induction generator --- PI tuning --- LCL-filter --- passive damping --- advanced metaheuristics --- Bonferroni-Dunn and Friedman's tests --- resistance spot welding --- dynamic resistance model --- adaptive control --- energy savings --- adaptive disturbance rejection controller --- hybrid systems --- state constraint --- worm robot --- bio-inspired robots --- Streeter-Phelps model --- fractional-order control --- high observers --- river monitoring --- 3 DOF crane --- convex systems --- fault-tolerant control --- robust control --- qLPV systems --- Takagi-Sugeno systems --- chaos --- synchronization --- FPGA --- UDS --- distillation column heating actuator --- Buck-Boost converter --- Takagi-Sugeno model --- fuzzy observer with sliding modes --- nonlinear optimization --- turbulent flow --- friction factor --- pipe roughness --- minor losses --- PID control and variants --- Intelligent control techniques --- neural control --- brushless DC electric motors --- sensors and virtual instruments --- analysis and treatment of signals