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This book comprises five peer-reviewed articles covering original research articles on the modeling and simulation of electricity systems for transport and energy storage. The topics include: 1 - Optimal siting and sizing methodology to design an energy storage system (ESS) for railway lines; 2 - Technical–economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems; 3 - How to improve electrical feeding substations, by changing transformer technology and by installing dedicated high-power-oriented storage systems; 4 - Algorithm applied to a vehicle-to-grid (V2G) technology. 5 - Thermal investigation and optimization of an air-cooled lithium-ion battery pack.

thermal management system --- optimal configuration --- air-cooling --- lithium-ion battery --- electric vehicles (EVs) --- photovoltaic (PV) systems --- vehicle-to-grid (V2G) --- smart grids (SGs) --- peak shaving --- amorphous transformer --- energy storage --- failure --- feeding substation --- tramway --- optimization --- energy storage system (ESS) --- siting --- sizing --- regenerative braking --- particle swarm optimization (PSO) algorithm --- net present value (NPV) --- railway network --- railway system --- lithium batteries --- supercapacitor --- Simulink --- catenary-free

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This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources.

photovoltaic --- parameter extraction --- single-diode model --- double-diode model --- swarm intelligence --- TSA --- wind energy --- renewable resources --- Black–Scholes model --- AC-DC converter --- shunt regulator --- full bridge rectifier --- electrostatic vibration energy harvesting --- fully integrated --- IoT --- charge pump --- energy harvesting --- thermoelectric --- energy storage system (ESS) --- battery management system (BMS) --- battery efficiency --- state of charge (SoC) --- state of health (SoH) --- on-chip integration --- power management --- supercapacitor --- storage unit --- unbalanced distribution networks --- linear loads --- non-linear loads --- total harmonic distortion --- harmonic power flow --- proton exchange membrane fuel cell --- parameter identification --- optimization --- energy storage --- arithmetic optimization --- microgrid --- PLL --- RTDS --- direct power control --- fuzzy logic --- voltage source inverter --- IoMT devices --- energy autonomous --- wearables --- energy-storage --- energy management --- fog edge computing --- task offloading --- deep learning --- reinforced learning --- IoMT --- sooty tern optimization --- distributed generation --- equilibrium optimization technique --- wind turbines --- photovoltaics --- biomass generators --- n/a --- Black-Scholes model

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The climate changes that are visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this book presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on energy internet, blockchain technology, and smart contracts, we hope that they are of interest to readers working in the related fields mentioned above.

irrigation system --- photovoltaic water pumping systems (PWPS) --- floating photovoltaic panels --- SCADA --- blockchain --- SolarCoin --- power factor --- reactive power --- capacitance --- harmonics --- telemetry --- Industry 4.0 --- battery management --- electric vehicle --- state of charge estimation --- Internet of Things --- smart contract --- Ethereum --- IOTA --- artificial intelligence --- information security --- UN sustainable development goals --- UN SDGs --- carbon trading --- dApp --- M2V --- IPFS --- charging scheduling --- Great-Circle Distance --- local electricity market --- smart grids --- energy crowdsourcing --- renewable energy sources --- prosumers --- blockchain technology --- energy poverty --- smart contracts --- hybrid power system --- nano-grid --- fuel cell --- fuel economy --- power tracking --- optimization --- droop control --- mesh microgrids --- power sharing --- synchronization --- system stability --- robustness analysis --- constant power load --- reconfiguration --- controller design analysis --- networked control systems (NCSs) --- network security --- delays --- sampling --- energy grids --- energy producers --- cold spinning reserve --- DLT --- brokerage --- SMEs --- energy optimisation --- interleaved boost converter --- DC/DC converter --- hybrid electric boat --- energy storage system (ESS) --- RST control

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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