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This research investigates the dynamic performance of a multi-terminal DC (MTDC) network linked to a wind farm side converter. The suggested approach is based on loop shaping, mutual quality decomposition, and an effective H controller architecture (MQDM). The transfer function was built as the wind power plant shifted from the Master-Slave control approach to the conventional feedback control method. The singular value curves of the original open-loop system and the suggested solution are compared in order to derive the weighting functions of the robust H controller. The control gain is then calculated by utilizing the MQDM approach to get the system's transfer function from the state space. By using the single value order reduction approach and frequency response analysis to generate a robust controller's gain, the suggested methodology was put into practice. The suggested method for controlling the DC grid voltage on the MTDC converter on the wind farm side has now been implemented in the MATLAB environment. Applying various uncertainties to the DC grid, wind turbines, and AC grid using simulation data demonstrates how reliable the suggested approach is. [ABSTRACT FROM AUTHOR]

In this paper, a positive output DC/DC converter with low total switching device power in dual working modes is introduced. One working mode is a step-up mode (boost), and other is a step-up/down mode (buck-boost). The proposed converter in step-up mode has high voltage gain ratio, low stress on switches, and continuous input current. In other working mode, the buck-boost converter with six relevant DC/DC converters is compared. By this comparison, it can be seen that the proposed converter has a lower voltage gain ratio, but instead the converter characteristics such as voltage stress on power switches and charge pump capacitors are in good condition for this mode. The proposed converter is analyzed in terms of the continuous conduction mode (CCM), steady state and efficiency with replacement of parasitic resistance effects. To validate the performance of the proposed converter experiments are conducted in the laboratory to claim the theoretical waveforms obtained from the PLECS simulation. [ABSTRACT FROM AUTHOR]

This paper presents an effective hybrid evolutionary approach for multi-objective optimisation of reinforced concrete (RC) retaining walls. The proposed algorithm combines an adaptive gravitational search algorithm (AGSA) with pattern search (PS) called AGSA–PS. In the resulting hybrid approach, the PS algorithm is employed as a local search algorithm around the global solution found by AGSA. The proposed algorithm was tested on a set of five well-known benchmark functions and simulation results demonstrate the superiority of the new method compared with the standard algorithm. Thereafter, the proposed AGSA–PS is applied for multi-objective optimisation of RC retaining walls. Two objective functions include total cost and embedded CO2emissions of retaining wall are considered. The reliability and efficiency of the AGSA–PS for multi-objective optimisation of retaining structures are investigated by considering two design examples of retaining walls. Experimental results demonstrate that the resulting algorithm has high viability, accuracy and significantly outperforms the original algorithm and some other methods in the literature. [ABSTRACT FROM AUTHOR]

In this study, a new particle swarm optimisation (PSO) approach is proposed for evaluating the factor of safety (FS) in a slope stability analysis based on the limit equilibrium method. The safety factors of the general slip surfaces are calculated using a concise algorithm of the Morgenstern–Price method, which satisfies both the force and the moment equilibriums. Each new slip surface is randomly generated by a straight-line technique. The performance of the proposed algorithm is evaluated using a set of three benchmark functions and three slope stability problems from the literature. The results indicate that the new method can provide high-quality, accurate and efficient solutions for computing the FS. Moreover, this method can predict a more critical failure mechanism of earth slope and outperform both the other methods in the literature and the standard PSO. [ABSTRACT FROM AUTHOR]