Senthilrani Shanmugavelu
@vcet.ac.in
Associate Professor
Velammal College of Engineering and Technology
EDUCATION
• Ph.D in Information & Communication Engineering from Anna University Chennai in March 2017.
• M.Tech in VLSI Design with CGPA of 7.41 from SASTRA University in May 2005.
• B.E in Electrical and Electronics Engineering with an aggregate of 73.4 % from Madurai Kamaraj University in April 2003.
RESEARCH INTERESTS
Semiconductor device modelling and image processing.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ashok Kumar B., Senthilrani S., Rajeswari J., and T. Rajapandi
EDP Sciences
In many developing countries, meeting the energy demand has become a major challenge. Such problem is more prominent in rural and remote areas of the country. The load requirements in these areas are less and the same can be addressed with renewable energy sources. The proposed work deals with a MPPT based standalone PV system using a priority controller. The system can be used to meet out the critical load demands in rural areas. Due to change in weather conditions, an unregulated output in PV array is observed. Hence, maximum power is tracked using a DC-DC converter, where the tracked data is with respect to temperature and irradiance levels. To acquire the maximum power point (MPP), an incremental conductance (IC) algorithm is employed and it is executed by controlling the duty cycle of DC-DC boost convertor. Thus, the attainment of energy management in loads and battery storage is supported by priority load control algorithm. The proposed system assures better energy management and supplies energy for critical loads. The entire system has been simulated and validated using MATLAB/SIMULINK.
A. Sivaranjani and S. Senthilrani
World Scientific Pub Co Pte Ltd
In this paper, a computer vision-based cashew nut grading system has been designed and implemented for classifying different grades of cashew nuts using combined features and machine learning approaches. The important task in the cashew nut grading system is to classify the whole and split down cashew nuts. Since these cashew nuts look very similar from the top view, it is a challenging task to classify the whole cashew nut and split down cashew nuts. Hence, a single-view image of cashew nut has been captured by placing a camera with a distance of 17[Formula: see text]cm (from the right side of the conveyor belt). The captured red, blue and green images are normalized and converted into hue, saturation and value color space. S channel from HSV image is used for segmentation process using Otsu threshold technique. The total numbers of features extracted are 275 and the features are texture (180), color (90), and shape (5). The constrained optimization-based feature selection method is used and 30 features are selected for further process. The Support Vector Machine (SVM) classifier is used for the classification, and the results obtained from different kernel functions are computed and compared. The 8-layer convolutional neural network (CNN) has been developed in this work for classification and to analyze the performance and accuracy. The accuracy of different machine learning classifiers like SVM 1-1, SVM 1-All and CNN model is also evaluated and compared. The overall accuracy obtained by SVM 1-All with kernel function radial basis for classification is 98.93%.
B. Ashok Kumar, G. Shanmukasri, S. Senthilrani, and S. Satheesh Kumar
IEEE
The growing number of electric vehicles (EVs) imposes greater stress on the power grid. One prospective remedy for this issue is the installation of a bidirectional charger that is also adept at aiding the power grid. The charging and discharging of the battery in an EV are both accomplished by bidirectional converters, one of which is an AC-DC and the other is a DC-DC. Changing the operating mode of a DC-DC converter can lead to it behaving differently. The plug-in hybrid electric car (PHEV) might work as an automobile that transmits power from "vehicle to grid." (V2G). Electric car batteries can engage in bidirectional electricity exchange with the grid. The objective of the paperwork is to design a control approach for efficient power flow for V2G and G2V in EV. Peak load reduction, load balancing, voltage control, and enhanced electrical system stability can be achieved as a consequence. The utility grid can absorb the distributed stored power provided by V2G equipment in the manner of rotatory reserve power. The ability to transfer battery energy back to the power grid through V2G technology contributes to the enhancement of electrical system stability. If there is a bidirectional discharging circuit available, there is also an opportunity to supply power from the grid. In the framework of G2V and V2G in EVs, the research effort focuses on the battery parameter, the voltage of the inverter, and the grid. We will be designing and building bidirectional charges for the battery in EV using MATLAB Simulink for this present work. The simulation focuses on two primary modes of operation: - V2G and G2V. Both of these modes are depicted.
Ashok Kumar B, Rajeswari J, Senthilrani S, Abilashini M, and Shivani N
IEEE
Internet of Things (IoT) has really signified the possibilities of wireless communication. IoT is not only used to send, receive signals between compatible but also used to automate the devices from a remote distance. Chatbot is the virtual bot used as an interactive agent with many added functionalities. It really eases the specific job and makes it more effective and efficient. Smart speakers are really a perfect example of automation done using a virtual assistant (Chatbot). Additionally, when people work with large databases it becomes quite difficult to manage tasks. Searching about information on internet, opening files or documents manually can sometimes be hectic tasks. . The objectives of a voice-based virtual assistant, or chatbot, generally encompass several key areas to improving User experience there primary goal is to enhance user interactions by offering a smooth and intuitive experience through voice commands, ensuring ease and convenience in accessing information and completing tasks. Streamlining Task Automation is a automating repetitive tasks and procedures to enable users to perform tasks more effectively and save valuable time accurate.In a stressed condition, if there is any assistant that can perform all the tasks just through our voice command, then it will be much easier and comfortable. Based on individual verbal commands, the virtual assistant can perform defined tasks. Thus, human speech interpretation is responded via synthesized voices. The implementation of new trend of Intelligent Personal Assistant (IPA) facilitates easy navigation through sites for users.
S Satheesh Kumar, B Ashok Kumar, and S Senthilrani
SAGE Publications
This review article gives a comprehensive review of existing research on renewable solar photovoltaic (PV) nanogrid, which is described from small-scale power system with a single domain for reliability, control, and power quality (PQ) for electric vehicle (EV) charging. A primary feeder on the Microgrid is connected to a nanogrid test bed that includes PV as power source, a battery energy storage system (BESS), smart-inverter multiple and EV charging stations (EVCS). The control algorithms are graded on four metrics: (1) voltage profiles, (2) renewable penetration, (3) PV curtailed and (4) net power flows. To investigate the local power quality, a steady-state power flow model of the nano-grid is created. The control algorithms successfully employ the battery to shift the nano-grid peak load while limiting the nano-grid demand to set level. Furthermore, an increasing emphasis is being placed on commonly used strategies for addressing the characteristics of each renewable system. This review paper characterizes the dynamic operation of 4 distinct BESS control algorithms for solar EV charging nanogrid: (1) peak load shifting, (2) reduce peak period impact, (3) cap demand, and (4) photovoltaic capture. These control modes are executed and analyzed on real-world nano-grid site, and optimal BESS control modes are assessed in terms of (1) solar electric vehicle charging, (2) power quality, (3) grid net demand, (4) photovoltaic curtailment, and (5) solar penetration. Finally, the problems highlight research gaps, and discussions on future trends are critical for enhancing the general technology of the renewable solar photovoltaic nano-grid for EV charging.
T.S Bagavat Perumaal, Parthasarathy Seshadri, B. Ashok Kumar, and S. Senthilrani
Informa UK Limited
ABSTRACT This work focuses on developing a mathematical model to forecast the performance of solar PV. In the present scenario, solar photovoltaic performance has been envisaged by considering the impact of limited variables subject to certain assumptions and conditions and the current work drives the attention toward the effect of temperature, relative humidity, wind velocity, and panel aging effects. There hasn’t been any breakthrough in the previous research so far while collectively analyzing the efficiency loss in solar photovoltaic, due to the aforementioned parameters. Hence, this work aims to develop a mathematical model in view of the above-mentioned parameters. This work has been experimented using MATLAB software and online simulation tools are used to validate the results. The results are favorable with the deviation of efficiency between the online simulation tool and the proposed mathematical model being 2–4%. Furthermore, a real-time case study has been carried out at a solar power plant installed at Thiagarajar College of Engineering, Madurai, Tamilnadu, to validate the proposed mathematical model. It is observed that the absolute difference in power between the simulation and the actual meter reading is between 30 and 60 Watts with an RMSE between 5 and 16% and MPE of 675 Watts.
B. Ashok Kumar, T. S. Bagavat Perumaal, S. Senthilrani, and Parthasarathy Seshadri
Springer Nature Singapore
B. Ashok Kumar, A. Sivaranjani, S. Senthilrani, and A. Senthil Murugan
Springer Nature Singapore
A Sivaranjani, S Senthilrani, B Ashok kumar, and A Senthil Murugan
Informa UK Limited
B Ashok Kumar, Parthasarathy Seshadri, S Senthilrani, and T S Bagavat Perumal
IOP Publishing
Abstract This work is focused on developing a model for a Battery management unit for a Solar PV based off grid standalone system and implementing the same using MATLAB tool. A secondary storage device in form a battery is essential to provide an energy backup in any autonomous system. In this work Lithium ion (Li Ion) battery has been considered for modeling as it offers good charge and discharge profile, high power density, occupies less space and less maintenance. It is essential to ensure secure function of such batteries by closely monitoring and control of their State of Charge (SOC). Determination of SOC ensures the remaining energy available in the battery which further helps in discharging the same based on system requirements. The major components of this work include representation of PV source, employing MPPT, regulating the DC output via boost converter, inverter and controlling the flow of energy between the source to battery, load and vice versa.
Parthasarathy Seshadri, Bagavat Perumaal T.S., Ashok Kumar B., Keerthana H., Kavinmathi G., and Senthilrani S.
Informa UK Limited
Abstract The increase in penetration of solar photovoltaics into the traditional grid and the accelerating growth of smart grids have introduced new challenges to grid stability. Forecasting the output power from solar PV systems and time-based analysis for the performance characteristics of solar PV under different weather conditions is essential to improve the grid stability. The generated PV power is intermittent in nature and is influenced by meteorological parameters such as pressure, temperature, relative humidity, and solar zenith angle. With the influence of the above parameters, a novel power forecasting model has been developed using Supervised Machine Learning Algorithm. The historical weather data of a given location have been fetched from National Solar Radiation Database (NSRDB) with the corresponding location coordinates. Multivariate data are used as inputs to train a Decision Tree Regression Model in order to predict the solar irradiance parameters such as Global Horizontal Irradiance, Direct Normal Irradiance, and Diffuse Horizontal Irradiance which are essential to calculate the output power harnessed from the grid-connected PV system. The results are favorable for the application and have depicted minimal deviation with an average accuracy of 86.02%. This technique also rules out the need of hardware power prediction modules, favoring a cost-efficient methodology.
B. Ashok Kumar, S. Senthilrani, and H. Keerthana
Springer Singapore
A. Senthil Murugan, S. Manoj Kumar, S. Senthilrani, and A. Sivaranjani
Springer Singapore
B. Ashok Kumar, R. Jeyabharathi, S. Surendhar, S. Senthilrani, and S. Gayathri
IEEE
The four tank process is a non-linear process and it is the de-facto standard for the multiple input and multiple output(MIMO) process. It usually consists of four tanks which are interconnected each other with their inputs and output. Usually in the MIMO process the controlling of the output by changing the single input is difficult. So, the four tank process is a non-linear process. It consists of two pumps which acts as input to the quadruple tank process. The Model Predictive Control (MPC) is a suitable technique for predicting the state of output by using the current values of input. The advantage of using the Model Predictive Control in the non-linear quadruple process is by changing the inputs and output simultaneously. It can stabilize the linear process effectively and it can also be applied to the non-linear process to stabilize the output. The result obtained in the Model Predictive Control will be within the limited tolerance value while stabilizing the output of the non-linear tank process. In Model Predictive Control, it consists of Predictive control ‘P’ and Horizon control ‘M’. By changing or tuning the P and M, the optimized result can be obtained. The results of the above non-linear process is simulated using MATLAB and results shows the good tracking performance.
A. Sivaranjani, S. Senthilrani, B. Ashokumar, and A. Senthil Murugan
IEEE
Since there is a great demand for the quality of agricultural products in the global market. It is very important to improve the quality and standards of agricultural products to competent in the business world. Furthermore cashew is a significant produce in India as well as it takes the major part in the global export market for cashew nut. But the most of the methods proposed for grading system is wouldn’t reach the better accuracy. Hence to improve the performance, we proposed the optimized cashew nut grading using Deep CNN and Data augmentation. This CashNet-15 work consists of totally 15 layers of CNN. Here we used 8 convolution layer and 4 Max-poolong layer for feature extraction and remaining are 1 fully connected layer, 1activation function and 1dropout layer. To attain the better performance we used data augmentation methods. To optimize the network, hyperparameter like SGD with Beta momentum and Leaky rectified linear unit was used to reduce the loss function and to obtain the non-linear property.
B. Ashok Kumar, S. Gayathri, S. Surendhar, S. Senthilrani, and R. Jeyabharathi
IEEE
Helicopter is a non-linear model which contain uncertainties and it will have non-linearity in operation. It has some uncertainty and external perturbation while in operation. These parameters are considered with control laws while designing. Using Lagrange’s equations the mathematical modeling of the 2-DOF helicopter is done. For the attitude control performances of pitch and yaw, the Robust attitude control problem for helicopters are investigated. The model of the pitch and yaw angular dynamics are measured as a nominal single-input single-output linear system with equivalent disturbances which contain nonlinear uncertainties, coupling-effects, parameter perturbations, and external disturbances. A decentralized controller is considered for cross coupled Single Input Single Output Twin rotor aero dynamic system (TRAS). The H-infinity controller is used to control a 2-DOF and the evaluation of performance is performed using MATLAB.
A. Sivaranjani, S. Senthilrani, B. Ashokumar, and A. Senthil Murugan
IEEE
Computer vision is becoming popular at the present days in agricultural area with an assortment of technological improvements for grading, sorting, classification. Though there are much technical advancement, cashew grading and sorting are still difficult task in daily market. In this research work we discussed about the computer vision based grading system and also an overview of deep Convolution Neural Network (CNN). The CNN with deep layer has tremendous achievement in many image classification applications. The deep CNN which itself extract the features of the image for classification was the added advantage. In this work the various parameters are considered for optimization of CNN. This work portrays the importance grading cashew nut and also proposed a framework for computer vision based grading system for cashew nut using deep CNN.
M.A.J. Priya, B. Ashok Kumar, and S. Senthilrani
IEEE
In this article, a grid tied PV conversion topology which is synchronized to the grid using PLL. Initially, photovoltaic module is designed and analyzed using different parameters like irradiation, temperature, and series current. Proposed Enhanced PLL enables faster synchronization during inverter start-up. It is used in high power master-slave based centralized inverters which are being used in large PV power plant. All the solar cell, MPPT, boost converter, the inverter and the phase locked loop are modeled using SimPower Systems blocks and simulated in MATLAB/SIMULINK
P. GAYATHRI, B. ASHOK KUMAR, and S. SENTHILRANI
IEEE
This paper presents simulation and modeling of standalone PV system under varying atmospheric conditions. This system composed of PV module; converter, controller and DC load. A converter is used to vary the output voltage to the required level and to raise the efficiency of the converter for PV. Along with the converter the Maximum Power Point Tracking (MPPT) control techniques using IC (Incremental Conductance) method are used in Photovoltaic (PV) system to get a maximum resulting revenue of photovoltaic array output power. That are proposed then simulated using MATLAB SIMULINK.
S. Senthilrani and M. Suganthi
American Scientific Publishers
S. Senthilrani and M. Suganthi
American Scientific Publishers
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
Publications
Publications Books
1. Smart Grids (GTU syllabus), Technical Publication, Pune, October 2021.
2. Smart Grid(AU syllabus),Technical Publications, Pune, April 2021
3. Lifetime aware device design using failure mechanism analysis , ISBN-13: 978-3-330-08693-7, ISBN-10: 3330086939, EAN: 9783330086937, Book language: English,LAP LAMBERT Academic Publishing (2017-05-16 ).
Book Chapters
1. Computer Vision-Based Vehicle Detection and Tracking, Springer Link - Lecture Notes in Electrical Engineering book series (LNEE),March 2021
2. Thermal Aware Device Design Using Hotspot Analysis, Springer Link - Lecture Notes in Electrical Engineering book series (LNEE),March 2021
3. Big Data Analytics and Intelligent Techniques for Smart Cities : “ Optimum Placement of Multiple Distributed Generators in Distribution Systems for Loss mitigation considering load growth”, CRC Press - Taylor & Francis Group November 2020.,Agreement signed
GRANT DETAILS
• Received Grant of for SPICES scheme , AICTE during March 2021.
• Received Grant of Tamilnadu State Council For Science And Technology Student Project Scheme 2019- during March 2020.
• Received Grant of for Six days Anna University Sponsored FDTP on Transmission and distribution during November 2019.
• Received Grant of for Energy awareness camp from TNSCST during May 2019.
• Received Grant of for National Seminar from Institution of Engineers(India) during August 2017.
• Received Grant of for “Entrepreneurship Awareness Camp” sponsored by Entrepreneurship Development Institute of India, Ahmedabad under the Department of Science & Technology, Govt. of India on Nov 2015.