A Grid Connected HRES using Seven Level Inverter - A Hybrid MFO-RBFNN Technique
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2020 by IJETT Journal|
|Year of Publication : 2020|
|Authors : Mr. Anem Apparo, Dr. G. Chandra Sekhar
|DOI : 10.14445/22315381/IJETT-V68I7P209S|
MLA Style: Mr. Anem Apparo, Dr. G. Chandra Sekhar "A Grid Connected HRES using Seven Level Inverter - A Hybrid MFO-RBFNN Technique" International Journal of Engineering Trends and Technology 68.7(2020):56-68.
APA Style:Mr. Anem Apparo, Dr. G. Chandra Sekhar. A Grid Connected HRES using Seven Level Inverter - A Hybrid MFO-RBFNN Technique International Journal of Engineering Trends and Technology, 68(7),56-68.
This manuscript proposes an innovative seven-level inverter scheme for grid-connected hybrid renewable energy system (HRES) that comprises wind and photovoltaic (PV) generation subsystems. The proposed controller denotes joint implementation of Moth Flame Optimization (MFO) as well as Radial Base Function Neural Network (RBFNN) and hence it is named as MFO-RBFNN. The purpose of proposed controller is to meet the load power demand and preserve the power regulation (or) maximal energy conversion of wind as well as photovoltaic subsystems. At proposed controller, RBFNN learning process is improved by using MFO algorithm in perspective of minimal error objective function. Here, MFO is utilized to evaluate the optimal gain parameter in view of the variety of source currents from the normal value. It can be useful for building up the optimal control signals dataset. In light of fulfilled dataset, RBFNN performs and forecasts most optimal control signals of seven-level inverter. MFO-RBFNN technique is actualized on MATLAB/Simulink as well as outcomes are examine by two test cases and compared by several solution methods such as base controller, 5 level inverter scheme and MFO-7 level inverter scheme. The comparison results demonstrate that superiority of MFO-RBFNN method and confirm their potential to solve the issue.
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Seven level inverter, grid connected hybrid renewable energy system, converter switching states, wind and photovoltaic generation subsystems.