This study reports the preparation of soft magnetic ribbons of Fe-based amorphous alloys using the single-roller melt-spinning technique. Ribbon width varied from 142 mm to 213 mm and, with a thickness of approximately 22 μm 2 μm. The microstructure and magnetic properties of the ribbons were characterized by differential scanning calorimeter (DSC), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and electrical resistivity measurements (ERM). The amorphous material properties dependence of the cooling rate and nozzle pressure have uneven surface in ribbon thicknesses are investigated. Magnetic measurement results indicate that some region of the ribbon exhibits good magnetic properties, higher saturation induction and lower coercivity. However, due to the uneven surface of 213 mm wide ribbon, the magnetic responses are not uniformly distributed. To understand the transformer magnetic performances, this study analyzes the measurements of a three-phase 2 MVA amorphous-cored transformer. Experimental results confirm that the transformer with a ribbon width of 142 mm has better magnetic properties in terms of lower core loss, exciting power, and audible noise.
The purpose of this paper is to improve electromagnetic characteristics on grounding grid by applying the conductive concrete. The conductive concrete in this study is under an extra high voltage (EHV, 345kV) system located in a high-tech industrial park or science park. Instead of surrounding soil of grounding grid, the application of conductive concrete can reduce equipment damage and body damage caused by switching surges. The focus of the two cases on the EHV distribution system in a high-tech industrial park is presented to analyze four soil material styles. By comparing several soil material styles, the study results have shown that the conductive concrete can effectively reduce the negative damages caused by electromagnetic transient. The adoption of the style of grounding grid located 1.0 (m) underground and conductive concrete located from the ground surface to 1.25 (m) underground can obviously improve the electromagnetic characteristics so as to advance protective efficiency.
This paper proposes the method combining artificial neural network with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. With the measurements of wind speed, rotor speed of wind generator and output power, the artificial neural network can be trained and the wind speed can be estimated. The proposed control system in this paper provides a manner for searching the maximum output power of wind generator even under the conditions of varying wind speed and load impedance.