RISHABH DEV SHUKLA
@cuchd.in
Professor & Head- ECE and EE Department
Chandigarh University Mohali Punjab India
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Modeling and Simulation, Multidisciplinary
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Rishabh Dev Shukla and Subhajit Roy
CRC Press
Aparna Unni, Manjeet Singh, and Rishabh Dev Shukla
IEEE
Noor Ahmmad, Shilpa Gupta, and Rishabh Dev Shukla
IEEE
Sunny Vig, Rishabh Dev Shukla, Rahul, and Akarshit Barwal
IEEE
Adhir Baran Chattopadhyay, Sunanda Hazra, Rishabh Dev Shukla, and Sudeshna Nath
CRC Press
Rishabh Dev Shukla, Subhajit Roy, Dulal Chandra Das, and H. Ravishankar Kamath
Elsevier
Amritjot Kaur, Manjeet Singh, Rishabh Dev Shukla, and Praveen Kumar Mishra
IEEE
Gaurav Aggarwal, Ashutosh Tripathi, Himani Goyal Sharma, Tripti Sharma, and Rishabh Dev Shukla
CRC Press
Subhajit Roy, Dulal Chandra Das, R. D. Shukla, V. Siva Brahmaiah, P. Bhowmik, and Suryashmi Ghosh
Springer Nature Singapore
Subhajit Roy, Rajesh Kumhar, Tarkesh Kumar Mahato, Ritwik Priya, Babli Kumari, and Rishabh Dev Shukla
CRC Press
Subhajit Roy, Dulal Chandra Das, Nidul Sinha, Rishabh Dev Shukla, Rajesh Kumhar, K. K. Pavan Kumar, V. S. R. Brahmaiah, and Ashok Kr Shaw
Wiley
Amritjot Kaur, Manjeet Singh, D Purnachandra, and Rishabh Dev Shukla
IEEE
The growth in electric vehicle (EV) implementation has created a need for precise battery modeling to expect performance, enhance control strategies, and ensure protection. This paper proposed a comprehensive approach to modeling EV batteries using Sirnulink, focusing on creating realistic symbols of battery performance under various operating circumstances. The model includes key features of battery dynamics, such as temperature properties, and charge/discharge rates, to simulate the multifaceted interactions in an EV environment. Leveraging Simulink's abilities, we simulate various drive cycles, regenerative braking situations, and load demands, providing perceptions into battery aging, energy efficiency, and capacity decline. The model's accuracy and adaptability are validated through a series of tests comparing simulated outputs with actual performance data. This research lays the foundation for emerging efficient battery management systems (BMS) that enhance EV performance and reliability, while contributing valuable visions into sustainable energy applications in transportation.
Sunanda Hazra, Rishabh Dev Shukla, Provas Kumar Roy, and Supradip Metia
IEEE
Renewable wind energy has always been extremely helpful to minimizing generation costs as well as reducing emissions to develop green/clean environments, in response to the environmental challenges. The high-proportional integration of renewable power presents challenges to the safe and stable operation of power networks because of its randomness, intermittency, and volatility. However, renewable wind power integrated hydro-thermal power plant is a complex optimization problem due to the water discharge rate, variable wind speed, water transport delay, valve point effect, scheduling time linkage and constraints related with hydraulic continuity and generational limits. The stochastic wind speed is evaluated using Weibull probability density function (W-pdf). For resolving complex economic problems, an effective chemical reaction optimization (CRO) is introduced, for the Hydro-Thermal-Wind (HTW) scheduling problem. Additionally, opposition-based learning (OBL) is integrated with the primary CRO algorithm to increase the solution superiority and convergence speed. The proposed optimization (OCRO) is applied to four hydro, three thermal, and two wind power plants systems. Moreover, proposed technique is compared to other current approaches and the suggested method is determined to be more effective than other methods described in the literature. Lastly, the output of cascade hydropower plants is stable, highly adjustable, and responds quickly.
Subhajit Roy, Dulal Chandra Das, Nidul Sinha, and Rishabh Dev Shukla
IEEE
This article discusses islanding detection strategies in microgrids in depth. Microgrids, which generate and distribute electricity locally, are critical for grid resilience and renewable energy integration. Unintended islanding, which occurs when a microgrid functions autonomously, poses operational and safety issues. As a result, accurate and quick islanding detection techniques (IDMs) are critical.The article investigates passive and active techniques to identifying islanding events. Active approaches apply disturbances and study system responses, whereas passive methods monitor parameters such as frequency and voltage variations. The ideas, implementation, and performance of various approaches are discussed in this article in comprehensive manner. Different approaches are evaluated using performance parameters such as sensitivity, selectivity, false positives/negatives, detection time, and resilience against disturbances. The review also investigates the effect of system characteristics, communication delays, and distributed energy resource integration. Apart from the conventional islanding techniques the article discusses about modern & intelligent islanding techniques enabled with computational intelligence.This in-depth analysis is an excellent reference for experts interested in islanding detection in microgrids.
Subhajit Roy, Rishabh Dev Shukla, Pritam Bhowmik, Nivendu Nandy, Alok Kole, and Kuntal Ghosh
IEEE
This paper proposes a predictive modelling approach for vehicle-to-grid (V2G) systems using Hidden Markov Algorithm (HMA). V2G systems allow electric vehicles (EVs) to be used as a source of energy for the grid, enabling bidirectional power flow and offering a range of benefits, such as improved energy management and reduced greenhouse gas emissions. The proposed predictive modelling approach uses HMA to model the stochastic behavior of EVs and their charging and discharging patterns. The HMA-based model is trained on historical data and can be used to predict future charging and discharging events of EVs connected to the grid. The proposed approach aims to optimize the performance of V2G systems by predicting the energy demand and supply in advance, and accordingly scheduling the charging and discharging events of EVs to balance the energy supply and demand. The proposed approach is evaluated using a real-world dataset of EVs connected to the grid. The experimental results show that the HMA-based model can accurately predict the future charging and discharging events of EVs with high accuracy. The predicted results are then used to optimize the energy management of the V2G system, which leads to improved energy efficiency and reduced operational costs. Overall, this research demonstrates the effectiveness of using HMA for the predictive modelling of V2G systems, which can help in optimizing the performance of the V2G systems and facilitating the integration of renewable energy sources into the microgrid.
Rishabh Dev Shukla, Navdeep Singh, and Subhajit Roy
WORLD SCIENTIFIC (EUROPE)
Rishabh Dev Shukla, Subhaiit Roy, and Gautam Sarkar
IEEE
This paper proposes a control technique for an autonomous DFIG-DC wind energy generation system. In autonomous DFIG-DC wind energy generation system, the stator and the rotor are connected to a dc load or micro-grid by a diode bridge rectifier and a controller power electronics converter respectively. DC voltage regulation is visibly necessary for stand-alone operation and DC micro-grid connected operation. The stator frequency and the DC side voltage regulation are achieved by an indirect control scheme, where maintaining constant DC voltage and frequency through a controller which is designed in polar coordinate frame rotating at slip frequency. Compared to other conventional techniques such as field-oriented control, the presented control technique is very simple and easy to implement. The hysteresis current controller provides the control pulses for rotor side controlled power electronics converter by the actuated by the error signal calculated between actual and reference rotor currents. The reference rotor currents are calculated by the presented indirect control scheme. The autonomous DFIG-DC wind energy generation system is designed MATLab and Simulink software platform. The performances of the system are verified by the simulations of different possible cases.
Subhajit Roy, Rishabh Dev Shukla, Rupendranath Chakrabarti, Sudeshna Nath, Ananya De, and Abhishek Pandev
IEEE
The current critical condition of fossil fuel crisis is rapidly increasing day to day and its harmful impact to the climate and environment is serious matter to take care. Thus, green energy or renewable energy is the only possible solution coming out of this context and solar energy is one of the most effective energy resources of these green energy system. In this manuscript we have discussed about a PV (photovoltaic) generation system with battery and capable of extracting maximum power output by using P&O type MPPT technique and it is working in isolated mode. As per the information given above, we have built a prototype of the system using a PV module capable of generating 1kW energy and the MPPT method has been implemented with the mean of using P&O technique. As the efficiency of the PV generation system is always a matter of concern the MPPT technique has been used to extract maximum power output from the PV array at any environmental condition. Here we used DC-DC converters as MPP trackers. A detailed model of the system first simulated using MATLAB/Simulink and later on the results have been validated to check effectiveness and suitability in the point of view of performance of the prototype has been added to this article. In each step of our designing of the prototype we tried to make it a cost-effective, simple and efficient model than the other existing models found in market.
Rishabh Dev Shukla and Ramesh Kumar Tripathi
Elsevier BV
Utkarsh Jadli, Padmanabh Thakur, and Rishabh Dev Shukla
Institute of Electrical and Electronics Engineers (IEEE)
The accuracy in electrical model parameters of solar photovoltaic (PV), such as photon current, the diode dark saturation current, series resistance, shunt resistance, and diode ideality factor, are desirable to predict the real performance characteristics of solar PV under varying environment conditions. First, this paper derives mathematical model of solar PV, in terms of two unknown, namely, series resistance and ideality factor. Then, using combination of analytical method, simulated annealing method, and derived model, a new parameter estimation technique has been proposed. Finally, performance indices, such as PV characteristics curve, relative maximum power error, root mean square deviation, and normalized root mean square deviation are estimated for the various solar PV panels, using proposed and existing methods, to reveal the effectiveness of the proposed method. Also, experimental data have been considered for the validation. Finally, through the comparative analysis of the results, it is revealed that the proposed method offers solar PV characteristics more closer to the real characteristics than the other existing methods.
Rishabh Dev Shukla, Ramesh Kumar Tripathi, and Padmanabh Thakur
Elsevier BV
Nitin Singh, Soumya Ranjan Mohanty, and Rishabh Dev Shukla
Elsevier BV
Rishabh Dev Shukla and Ramesh Kumar Tripathi
Elsevier BV
Rishabh Dev Shukla and Ramesh Kumer Tripathi
IEEE
This paper investigates the application of the hysteresis current control technique to control the voltage and frequency of a variable speed-constant frequency autonomous DFIG based wind energy system by using Direct Voltage Control method. The DFIG feeds an isolated R-L load. A diode bridge rectifier and a power electronics converter (called rotor side converter) having common dc link is connected between the stator and rotor of the DFIG. The control strategy uses the speed-sensorless control for the rotor side converter designed for low-to-medium wind speeds. To regulate the voltage and frequency at stator terminals, the error between the actual rotor currents and the reference rotor currents is given to the hysteresis controller. The reference currents are obtained by the direct voltage control technique. The control pulses for the rotor side converter are supplied by the hysteresis controller which is operated on the error signal. A 2 MVA Wind energy system is designed by using DFIG prototype in MATLab/Simulink. Simulation outcome obtained from the 2 MVA system are presented and discussed in this paper.
Rishabh Dev Shukla and Ramesh Kumar Tripathi
Elsevier BV