Performance of the Impedance Boundary Conditions for Eddy-Current Problems
Impedance boundary conditions are used to derive approximate expressions for the magnetic vector potential, field quantities, Joule losses and forces for conducting spheroids in the presence of circular turns carrying sinusoidal with time currents. Numerical results are generated to determine, by comparison with the results obtained applying the exact boundary conditions, the improvement achieved with the surface impedance model with respect to the simpler perfect conductor model and the range of validity of these models. The study performed is useful for evaluating various approximate numerical solutions for real world conductors
Approximate boundary conditions in electromagnetics
Non-metallic materials and composites are now commonplace in modern vehicle construction, and the need to compute scattering and other electromagnetic phenomena in the presence of material structures has led to the development of new simulation techniques. This book describes a variety of methods for the approximate simulation of material surfaces, and provides the first comprehensive treatment of boundary conditions in electromagnetics. The genesis and properties of impedance, resistive sheet, conductive sheet, generalised (or higher order) and absorbing (or non-reflecting) boundary conditions are discussed. Applications to diffraction by numerous canonical geometries and impedance (coated) structures are presented, and accuracy and uniqueness issues are also addressed, high frequency techniques such as the physical and geometrical theories of diffraction are introduced, and more than130 figures illustrate the results, many of which have not appeared previously in the literature. Written by two of the authorities m the field, this
graduate-level text should be of interest to all scientists and engineers concerned with the analytical and numerical solution of electromagnetic problems.
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.