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This book focuses on the recent development of forecasting and risk management techniques for electricity markets. In addition, we discuss research on new trading platforms and environments using blockchain-based peer-to-peer (P2P) markets and computer agents. The book consists of two parts. The first part is entitled “Forecasting and Risk Management Techniques” and contains five chapters related to weather and electricity derivatives, and load and price forecasting for supporting electricity trading. The second part is entitled “Peer-to-Peer (P2P) Electricity Trading System and Strategy” and contains the following five chapters related to the feasibility and enhancement of P2P energy trading from various aspects.
Technology: general issues --- History of engineering & technology --- electricity markets --- non-parametric regression --- minimum variance hedge --- spline basis functions --- cyclic cubic spline --- weather derivatives --- n/a --- distributed energy resources (DER) --- P2P energy trading --- cooperative mechanism --- renewable energy --- multi agent system --- blockchain --- cashflow management of electricity businesses --- electricity derivatives and forwards --- retailers and power producers --- solar power and thermal energy --- optimal hedging using nonparametric techniques --- empirical simulations --- peer-to-peer energy trading --- distributed energy resources --- microgrid --- digital grid --- bidding strategy --- electricity price --- electricity load --- electricity price forecasting --- wind energy --- day-ahead market --- intra-day market --- balancing power market --- peer to peer energy market --- hardware control --- demonstration experiment --- home energy management systems --- electric vehicles --- bidding agent --- electric vehicle --- functional autoregressive model --- functional principle component analysis --- vector autoregressive model --- functional final prediction error (FFPE) --- naive method --- P2P electricity market --- market maker --- liquidity --- price fluctuation --- artificial market simulation
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In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics.
History of engineering & technology --- fluid–structure interaction --- monolithic method --- Updated Lagrangian --- Arbitrary Lagrangian Eulerian --- computational aerodynamics --- Kutta condition --- compressible flow --- stream function --- non-linear Schrödinger equation --- cubic B-spline basis functions --- Galerkin method --- pressure tunnel --- hydraulic fracturing --- transient flow --- finite element method (FEM) --- Abaqus Finite Element Analysis (FEA) --- computational fluid dynamics --- RANS closures --- uncertainty quantification --- Reynolds stress tensor --- backward-facing step --- OpenFOAM --- large eddy simulations (LES) --- shock capturing --- adaptive filter --- explicit filtering --- jet --- proper orthogonal decomposition --- coherent structures --- turbulence --- vector flow fields --- PIV --- buildings --- urban area --- pollution dispersion --- Large Eddy Simulation (LES) --- multiple drop impact --- computational fluid dynamics (CFD) simulation --- volume-of-fluid --- crater dimensions --- vorticity --- transient incompressible Navier-Stokes --- meshless point collocation method --- stream function-vorticity formulation --- strong form --- explicit time integration --- wall layer model --- LES --- separated flow --- body fitted --- immersed boundary --- reduced order modeling --- Kolmogorov n-width --- Galerkin projection --- turbulent flows --- reduced order model --- closure model --- variational multiscale method --- deep residual neural network --- internal combustion engines --- liquid-cooling system --- heat transfer --- n/a --- fluid-structure interaction --- non-linear Schrödinger equation
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In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics.
fluid–structure interaction --- monolithic method --- Updated Lagrangian --- Arbitrary Lagrangian Eulerian --- computational aerodynamics --- Kutta condition --- compressible flow --- stream function --- non-linear Schrödinger equation --- cubic B-spline basis functions --- Galerkin method --- pressure tunnel --- hydraulic fracturing --- transient flow --- finite element method (FEM) --- Abaqus Finite Element Analysis (FEA) --- computational fluid dynamics --- RANS closures --- uncertainty quantification --- Reynolds stress tensor --- backward-facing step --- OpenFOAM --- large eddy simulations (LES) --- shock capturing --- adaptive filter --- explicit filtering --- jet --- proper orthogonal decomposition --- coherent structures --- turbulence --- vector flow fields --- PIV --- buildings --- urban area --- pollution dispersion --- Large Eddy Simulation (LES) --- multiple drop impact --- computational fluid dynamics (CFD) simulation --- volume-of-fluid --- crater dimensions --- vorticity --- transient incompressible Navier-Stokes --- meshless point collocation method --- stream function-vorticity formulation --- strong form --- explicit time integration --- wall layer model --- LES --- separated flow --- body fitted --- immersed boundary --- reduced order modeling --- Kolmogorov n-width --- Galerkin projection --- turbulent flows --- reduced order model --- closure model --- variational multiscale method --- deep residual neural network --- internal combustion engines --- liquid-cooling system --- heat transfer --- n/a --- fluid-structure interaction --- non-linear Schrödinger equation
Choose an application
In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics.
History of engineering & technology --- fluid-structure interaction --- monolithic method --- Updated Lagrangian --- Arbitrary Lagrangian Eulerian --- computational aerodynamics --- Kutta condition --- compressible flow --- stream function --- non-linear Schrödinger equation --- cubic B-spline basis functions --- Galerkin method --- pressure tunnel --- hydraulic fracturing --- transient flow --- finite element method (FEM) --- Abaqus Finite Element Analysis (FEA) --- computational fluid dynamics --- RANS closures --- uncertainty quantification --- Reynolds stress tensor --- backward-facing step --- OpenFOAM --- large eddy simulations (LES) --- shock capturing --- adaptive filter --- explicit filtering --- jet --- proper orthogonal decomposition --- coherent structures --- turbulence --- vector flow fields --- PIV --- buildings --- urban area --- pollution dispersion --- Large Eddy Simulation (LES) --- multiple drop impact --- computational fluid dynamics (CFD) simulation --- volume-of-fluid --- crater dimensions --- vorticity --- transient incompressible Navier-Stokes --- meshless point collocation method --- stream function-vorticity formulation --- strong form --- explicit time integration --- wall layer model --- LES --- separated flow --- body fitted --- immersed boundary --- reduced order modeling --- Kolmogorov n-width --- Galerkin projection --- turbulent flows --- reduced order model --- closure model --- variational multiscale method --- deep residual neural network --- internal combustion engines --- liquid-cooling system --- heat transfer
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