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Design and Harmonic Elimination of sinusoidal pulse width modulation (SPWM) Based Five Level Cascaded H-Bridge Multilevel Inverter for Photovoltaic System for Educational Purposes Ganthia, Bibhu Prasad; Praveen, B. M.
Indonesian Journal of Teaching in Science Vol 3, No 2 (2023): IJOTIS: September 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijotis.v3i2.60750

Abstract

In this modern era, the electrical power system faces a shortage of fossil fuel-based energy sources. To overcome this problem, people more focus on giving towards renewable energy sources like solar energy, wind energy, and nuclear energy sources. This also can be used to overcome global warming and reduce pollution by fossil fuels. This study used a photovoltaic (PV) array to give supply to the Multilevel Inverter (MLI) with different irradiance values, which can be used for educational purposes. The sinusoidal pulse width modulation (SPWM) method is used here to control the converter. SPWM technique is the easiest technique than the other types of pulse width modulation (PWM) technique. In this technique the switching loss is very low, therefore efficiency is high. After the simulation, the output waveforms are similar to the sinusoidal waveform for the resistive load. In this topology, after simulation, the total harmonic distortion (THD) contents were found to be less by using an LC filter. The model is simulated in MATLAB/Simulink. The analysis of output voltage waveforms is discussed with the reduced THD.
Artificial Neural Network Optimized Load Forecasting of Smartgrid using MATLAB Ganthia, Bibhu Prasad; Mohanty, Monalisa; Mohapatra, Sushree Shataroopa; Pradhan, Rosalin; Satapathy, Subhasmita; Patra, Shilpa; Pahadasingh, Sunita Pahadasingh
Control Systems and Optimization Letters Vol 1, No 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i1.14

Abstract

The motivation behind the research is the requirement of error-free load prediction for the power industries in India to assist the planners in making important decisions on unit commitments, energy trading, system security reliability, and optimal reserve capacity. The objective is to produce a desktop version of a personal computer-based complete expert system that can be used to forecast the future load of a smart grid. Using MATLAB, we can provide adequate user interfaces in graphical user interfaces. This paper devotes a study of load forecasting in smart grids, a detailed study of the architecture and configuration of Artificial Neural Network (ANN), Mathematical modeling and implementation of ANN using MATLAB, and a detailed study of load forecasting using the backpropagation algorithm.