This paper presents the Bee optimization method for harmonic elimination in a cascaded multilevel inverter. The main objective in selective harmonic elimination pulsewidth modulation strategy is eliminating low-order harmonics by solving nonlinear equations, while the fundamental component is satisfied. In this paper, the Bee algorithm (BA) is applied to a 7-level inverter for solving the equations. The algorithm is based on the food foraging behavior of a swarm of a honeybees and it performs a neighborhood search combined with a random search. This method has higher precision and probability of convergence than the genetic algorithm (GA). MATLAB software is used for optimization and comparison of GA and BA. Simulation results show superiority of BA over GA in attaining accurate global minima and higher convergence rate. Also, its performance in 10 times run is the same as in 1 time run. Finally, for verifying purposes, an experimental study is performed.

This paper examines a completely novel method for improving the transient stability of multi-VSG grids. In this method, it has been tried to control the oscillation of VSGs with respect to the center of inertia frequency (COI-frequency) of the grid, during short-circuit. It is also well demonstrated here that the proposed method is able to prevent the increase in irreversible distance angle of VSGs relative to each other, which is the main factor in preventing VSGs reaching to instability point. The method can enhance both the synchronizing and damping terms efficiently. Detailed analyzing of the direct Lyapunov method illustrates the non-linear proof of the method. Also, non-linear algebraic equations for a two-VSG system has been derived to prove the possibility of corroborating simulation results. Equal area criterion (EAC) is also used to clarify this method further. One interesting feature of the method is that there is no conflict between the requirements of the low voltage ride-through (LVRT) and transient stability improvement.

In urban electric railway transit systems, rails are used to navigate trains, as well as to provide the returning path of the train's electric current to the traction power substation (TPS). Due to electrical resistance of rails and the rail-to-ground conductivity, a part of the train's returning current to the TPS flows into the ground, which is called stray current, which causes different problems such as an increase of rail potential. In this regard, a model of an electric train with a TPS, running rail, and third rail is simulated in MATLAB/Simulink. In the simulated model, the amounts of stray currents in different soil types, with and without collection mats, are compared. Afterward, to calculate the amount of stray current in the presence of the stray current control method considering different soil types through finite-element (FE) method (FEM), a UIC54 rail with insulated fastening equipment is modeled in FEMM 4.2 and analyzed with 2-D FEM. Finally, a comparison of efficiency of stray current collection mats in different soil models for both simulation in MATLAB/Simulink and FEM is also presented. The obtained results verify the accuracy of the simulated and modeled system in real conditions of electric railways.

Network reconfiguration and capacitor placement have been widely employed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems. Reconfiguration method proposed in this paper is based on a simple branch exchange method of single loop. In this simple method of branch exchange, loops selection sequence affects the optimal configuration and the network loss. Therefore, this method has been improved by optimizing the sequence of loops selection for minimizing the energy losses in this paper. Also, a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction. For more practical application of the proposed method, different load patterns are considered and a fast method of total energy loss calculation is employed for the economic optimization of energy losses during the planning horizon. Discrete genetic algorithm (GA) is used to optimize the location and size of capacitors and the sequence of loops selection. In fact, the capacitor sizes have been considered as discrete variables. Simulated annealing (SA) is also applied to compare the performance of convergence. The proposed algorithm is effectively tested on a real life 77-bus distribution system with four different kinds of load patterns.