Article Per Year (5 Year)
p-Index From 2019 - 2024
0.61
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Indonesian Journal of Electrical Engineering and Computer Science
Rudranarayan Senapati
KIIT Deemed to be University
Control & Systems Engineering Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Comparison of DC-DC converters for solar power conversion system Debani Prasad Mishra; Rudranarayan Senapati; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp648-655

Abstract

This paper covers the comparison between four different DC-DC converters for solar power conversion. The four converters are buck converter, buck-boost converter, boost converter, and noninverting buck-boost converter. An MPPT algorithm is designed to calculate battery voltage, current of PV array, the voltage of PV array, power of PV array, output power. It is observed that the non-inverting buck-boost converter is the finest converter for solar power conversion. The final circuit design has the results of 12.2V battery voltage, 0.31A current of PV array, 34V voltage of PV array, 23mW power of PV panel, and 21.8mW of output power. The efficiency of this system is nearly 95%. All four circuits are simulated in MATLAB/Simulink R2020b.
Global solar radiation forecast using an ensemble learning approach Debani Prasad Mishra; Subhrajit Jena; Rudranarayan Senapati; Atman Panigrahi; Surender Reddy Salkuti
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i1.pp496-505

Abstract

With the increase in demand for solar power, a solar power forecasting model is of maximum importance to allow a higher level of integration of non-conventional energy into the existing electricity grid. With the advancement in data availability, there’s a good time to use data-driven algorithms for enhanced prediction of solar energy generation. Gathering and analyzing data can predict solar energy generation and mitigate the impact of solar intermittency. During this research, we explore automatically creating prediction models that are site-specific utilizing machine learning to generate solar radiation from meteorological station weather forecast reports, and from the predicted solar radiation corresponding solar power output can be calculated depending upon the characteristics of the solar PV system used. The challenge is to enhance the accuracy of the forecast. Ensemble techniques like random forest (RF) and extreme gradient boosting (XGBoost) are well suited for solar radiation prediction as they improve stability as well as combine several machine learning models to reduce variation and bias which outperforms the majority of models, as a result making them a perfect model in the field of solar energy prediction.
Distribution networks power loss allocation with various power factors Debani Prasad Mishra; Rudranarayan Senapati; Arun Kumar Sahoo; Jayanta Kumar Sahu; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1234-1241

Abstract

The users of power distribution and transmission networks are generally guided to sustain advanced power factor (PF) of load as it is affecting the power loss of a feeder network where it separately owns major influence on electric charges layout. Therefore, some cautious loss allotment schemes are to be incorporated and an acceptable satisfying/penalizing policy for advanced/less PF users, independently. Keeping this in view, the mentioned article proposed a new scheme, i.e., the active power loss allocation (APLA) procedure which allows power loss to the system distributors by considering the load demands, topographical localities, and PFs. A newly modified procedure assigns inducements hardly to all the involved utilizers against change in load PF continuously, where it is evaluated via proper mathematical and statistical study. The efficiency of the newly modified APLA scheme is explored in two dissimilar frameworks of low PF using 33 bus system radially distributed network (RDN). The interpretation is in favor of examined transmitted, distributed, and allows generated PF to be verified subsequently. Comparatively, the results achieved highlight the originality of the present method compared with different standard schemes/frameworks.
Co-Authors Arun Kumar Sahoo Atman Panigrahi Debani Prasad Mishra Jayanta Kumar Sahu Subhrajit Jena Surender Reddy Salkuti