Calculated versus measured iron losses and instantaneous magnetization power functions of electrical steel
Magnetic energy loss of soft magnetic laminations like SiFe sheets tends to be expressed through an integral over the power product · d/d. Already in earlier papers, we stressed that distinctions are needed for the quantities and . However, they are not considered in practically consistent ways, in the so far literature. Here, we discuss these distinctions in closer ways, comparing loss determination by calculation and measurement, respectively. A physically consistent procedure is described for the determination of loss and magnetization power functions through measurement of bi-located quantities and (S surface, C cross section). On the other hand, it is concluded that corresponding quantitative calculations-based on co-located quantities and -are impeded by the high amount of technological parameters of modern steel products. For example, they result from chemical additions, and-in particular-also from specific technologies of rolling, annealing, coating or scribing.
ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter
The multidimensional purposes of grid-tied hybrid renewable system such as tracking of maximum power, increasing the power conversion efficiency, reducing the harmonic distortions in the injected current and control over power injected into the grid are presented in this paper by developing a laboratory-scale setup. To ensure continuous current operation at the shoot through mode of grid connected inverter, a switched Z-source converter is utilized at the PV side. The PWM rectifier connected with the wind turbine transforms AC power into dc. Individual power converters with conventional PI controllers have been dedicated for each power source, and control strategy uses only one reference voltage so as to increase the maximum power tracking speed from both PV and wind sources. The battery energy management is performed by artificial neural network (ANN) to enhance the stable power flow and increase the lifespan of the storage system. Finally, the voltage at the point of common coupling is fed to ANN-based space vector-modulated three-phase inverter and the converted AC power is injected to the grid. The overall system performance is measured by estimating the quality of injected power. A stable operation of the proposed microgrid system is verified by varying input and load at the grid. A continuous-time simulation model is realized in MATLAB and is validated using experimental prototype. This benchmark system provides various research scopes for the future smart grids.
Optimal placement of distributed generation based on DISCO's financial benefit with loss and emission reduction using hybrid Jaya-Red Deer optimizer
The optimal location of distributed generation (DG) is a critical challenge for distribution firms in order to keep the distribution network running smoothly. The optimal placement of DG units is an optimization challenge in which the objective function is to maximize distribution firms' financial benefit owing to reduced active power losses and emissions in the network. Bus voltage limits and feeder thermal limits are considered as constraints. To overcome the problem of trapping the solution toward the local optimal point and to achieve strong local and global searching capabilities, a new hybrid Jaya-Red Deer optimizer is proposed as an optimization approach in this study to determine the best placement and size of distributed generating units. In the MATLAB environment, the suggested method is implemented on IEEE 15 and PG & E 69 bus distribution systems and validated with Red Deer Optimizer, Dragonfly Algorithm, Genetic Algorithm, Particle Swarm Optimization, Jaya Algorithm and Black Widow Optimizer. Based on the simulation results, distribution firms may operate their networks with the greatest financial advantage by properly positioning and sizing their DG units.