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All Journal Bulletin of Electrical Engineering and Informatics
Ramkumar Ravindran
Dhanalakshmi Srinivasan University
Electrical & Electronics Engineering

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Simulation of 3D-space vector modulation for neutral point clamped inverters Palanisamy Ramasamy; Ramkumar Ravindran; Neetu Gupta; Gunjan Sardana; Indumathi Sekar; Venugopala Aparna Marthanda; Selvakumar Kuppusamy
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4502

Abstract

This paper gives an idea to simulation of three-dimensional space vector modulation for neutral point clamped multilevel inverter. Three dimensional-space vector modulation (3D-SVM) algorithm is progressed method of two dimensional-space vector modulation (2D-SVM) algorithm; it leads to reduce the complexity in reference vector identification and switching time calculation, also it includes the various advantages of 2D-SVM like minimized total harmonic distortion, reduced EMI issues. A simple system for the assortment of switching state vectors to track the reference voltage vectors without using any redundant switching vectors. This proposed method tracks the reference vector by identifyinglsubcubes and prisms by using mathematicallconditions. Here the cost of the proposedltechnique is independentlof voltagellevels oflinverter. This paper realizes the accomplishment of 3D-SVM using a neutral point clamped inverter. The simulation results of the proposed method are verified using MATLAB/Simulink.
Enhancing solar power generation efficiency through chaotic beetle swarm optimization for constant power generation Sreenivasan Ramachandran; Ramkumar Ravindran
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11199

Abstract

The necessity for more and cleaner sustainable energy sources to generate power is increasing because of the reduction of fossil fuel supplies and their negative impacts on the environment. This research addresses the requiring crucial for optimized solar power systems in the weather change issues. In the beginning, the photovoltaic (PV) system’s voltage is enhanced by dual stage XBoost converter (DSXBC) with little voltage stress and maximum voltage gain. Also, the radial bias function neural network (RBFNN)maximum power point tracking (MPPT) tracks the PV system’s uppermost power and its parameters are fine-tuned by chaotic beetle swarm optimization (CBSO) algorithm. By integrating chaotic dynamics within the optimization process, CBSO runs a robust and efficient approach to navigating the complex search space related with MPPT. The MATLAB tool is utilized to reveal the efficacy of developed approach for allowing constant power generation in solar power generation systems with efficacy of 99.74% and tracking efficiency of 98.9% in steady state condition, thereby enabling continuous power generation.
Co-Authors Gunjan Sardana Indumathi Sekar Neetu Gupta Palanisamy Ramasamy Selvakumar Kuppusamy Sreenivasan Ramachandran Venugopala Aparna Marthanda