H

Traction loads are subjected to significant load changes and frequent voltage change of about 5%, which is usually unacceptable to the public electricity supply. This paper presents a comparative study of traction transformers such as Scott, YNvd, Leblanc and Impedance Matching Transformer for reducing the total harmonic distortion and thereby improving the power quality in a co-phase traction system. A dual converter with a compensator is employed together with special traction balanced transformers to reduce the harmonics, voltage unbalance, negative sequence current and reactive power problems. This scheme is implemented by using Matlab/Simulink R2009a software. The simulation results show that the performance of the Impedance Matching Transformer is better compared to other special traction transformers

Application of DSO algorithm for estimating the parameters of triple diode model-based solar PV system

Abstract Solar Photovoltaic (SPV) technology advancements are primarily aimed at decarbonizing and enhancing the resiliency of the energy grid. Incorporating SPV is one of the ways to achieve the goal of energy efficiency. Because of the nonlinearity, modeling of SPV is a very difficult process. Identification of variables in a lumped electric circuit model is required for accurate modeling of the SPV system. This paper presents a new state-of-the-art control technique based on human artefacts dubbed Drone Squadron Optimization for estimating 15 parameters of a three-diode equivalent model solar PV system. The suggested method simulates a nonlinear relationship between the P–V and I–V performance curves, lowering the difference between experimental and calculated data. To evaluate the adaptive performance in every climatic state, two different test cases with commercial PV cells, RTC France and photo watt-201, are used. The proposed method provides a more accurate parameter estimate. To validate the recommended approach's performance, the data are compared to the results of the most recent and powerful methodologies in the literature. For the RTC and PWP Photo Watt Cell, the DSO technique has the lowest Root Mean Square Error (RMSE) of 6.7776 × 10–4 and 0.002310324 × 10–4, respectively